National Atlas of Spain - User contributions [en]

Talk:Putting resources into action

2022-03-10T16:25:03Z

Usr1:

{{ANEEtiqueta|palabrasclave=covid-19, pandemia, covid19, camas en UCI, hoteles medicalizados, fuerzas armadas en la pandemia, Twitter|descripcion=Estudio cartográfico de los recursos movilizados|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Putting resources into action}}

The resources put into action to fight against the COVID-19 pandemic are hard to be quantified because of the many different stakeholders involved, the heterogeneity of the actions taken and their sometimes intangible nature; proof of the latter was the significant solidarity movement that took place during the hardest times of the first wave of the pandemic (see chapter on ''[[Solidarity Actions | Solidarity Actions]]''). This chapter focuses, however, on two aspects that may help understand the swift response of the public administrations to the extraordinary situation from March 2020. It first shows some indicators on the effort made in the health field as well as the experience at ''Lozano Blesa University Hospital'' in Saragossa (Zaragoza). Second, the text delves into how the Armed Forces participated in this deployment, what took place under Operation Balmis.

There is no reliable record of which new resources were put into action during the first wave of the pandemic aimed at fighting the coronavirus and reducing its impact. Some decisive links in the process of building an effective response were for instance the financial efforts of the public administration, the initiatives that came from within society both individually and in groups, the dedication of the medical staff and the donations from companies.

<div><ul style="text-align: left; float:right">

<li style="display: inline-block">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Evolution in the number of ICU beds during the first wave of the pandemic. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Beds in medicalised hotels during the first wave of the pandemic. 2020. Spain.]]
</li>
</ul></div>
A first indicator depicting the changes that took place in hospitals was the increased availability of Intensive Care Unit (ICU) beds, which is shown by regions on the map ''[[:File:Evolution in the number of ICU beds during the first wave of the pandemic|Evolution in the number of ICU beds during the first wave of the pandemic]]''. There were 150% more ICU beds (excluding newborns) towards the beginning of April 2020 than in January 2020 in the public and private healthcare systems –including both beds with and without respirators–. After the peak of the first wave of the pandemic, a decrease was registered in early June; even so, there were 78% more ICU beds occupied at the end of the first semester of 2020 than at the beginning of the year.

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Mensajes en Twitter solidarios con el hospital de IFEMA. 2020. España.]]

Some other actions were also taken in order to increase the capacity to accommodate the growing number of infected people requiring hospital admission, e.g. hotel beds were medicalised and field hospitals were built as presented on the map on ''[[:File:Beds in medicalised hotels during the first wave of the pandemic|Beds in medicalised hotels during the first wave of the pandemic]]'' shows the result of this action, with a large number of beds being made available in non-medical centres.
Regional authorities strove to multiply the capacity to care for patients requiring hospital admission. For example, the Region of Madrid set up the facilities at Madrid Trade Fair as a field hospital. The particular impact of the first wave of the pandemic on this territory shall be taken into account. Nearly 5,000 patients were admitted and more than 1,200 healthcare professionals worked from 23 March to 1 May 2020 in Halls 5 and 7 at Madrid Trade Fair.
There was also an intense solidarity movement based on social initiatives. Social networks served to connect demands and offers; details on the flow of messages on Twitter referring to solidarity deployed in this field hospital at Madrid Trade Fair are shown on the graph.

{{ANEAutoria|Autores= José Sancho Comíns}}

{{ANETextoDestacado|titulo=«LOZANO BLESA» UNIVERSITY HOSPITAL IN SARAGOSSA (ZARAGOZA)|contenido=This note is a brief summary of the experience at Lozano Blesa University Hospital in Saragossa (Zaragoza) which may be understood as an example of the situation in many hospitals in Spain during the first wave of the pandemic. This hospital covers a large healthcare area including a population heavily affected by COVID-19 as well as a large number of nursing homes. The COVID-19 Group was created in January 2020 at this hospital and included professionals from Preventive Medicine, Occupational Risk Prevention, Emergency, Microbiology, Internal Medicine, Infectious Diseases and Intensive Care departments, together with representatives from the hospital medical and nursing management teams. This COVID-19 group drew up a Contingency Plan for the hospital, whose forecasts were soon largely exceeded. The first COVID-19 case was detected on 3 March 2020.
Special care was taken to ensure that the actions triggered were supported from both a human and a technical perspective. With regard to the former, the high level of professionalism of all health and non-health workers at hospital shall be highlighted: doctors, nurses, laboratory technicians, cleaning staff, technicians who control ventilation circuits and many other professionals worked double shifts, overtime, etc. Protective measures were increased at hospital. All possible scenarios as well as the protective equipment to be worn were defined. Special attention was paid to staff protection training. The so-called Extended Universal Precautions were extended to the entire hospital in order to protect other patients and hospital employees. The workflow was modified and professionals who had never worked together before started to form multidisciplinary teams: neurologists, allergists, haematologists, anaesthesiologists, etc. started to work side by side with internists and intensivists.
From a technical point of view, decisions were made based on new data received. The health system was not prepared for a phenomenon of such magnitude and so long-lasting. Nevertheless, efforts were multiplied to adapt the hospital structure, equipment and organisation. A new intensive care unit was built in record time. The Surgical Block was adapted to accommodate COVID-19 patients and non-COVID-19 patients, the inpatient area was reorganised with exclusive areas for COVID-19 patients, a separate circuit was set up in the emergency department for possible infected patients, etc.
.}}
{{ANEAutoria|Autores= María José Amorín Calzada}}
{{ANETextoEpigrafe|epigrafe=Operation BALMIS}}

[[File:Logo Monografía.jpg|left|thumb|300px|Illustration: Datos generales de la Operación BALMIS. 2020. España.]]

The intervention of the Armed Forces in the fight against the COVID-19 pandemic under Operation Balmis was an example of the so-called new missions of the Navy, the Army and the Air Force, as a key tool for solving all kinds of crisis. The missions allotted to the Armed Forces were set forth in Spanish Organic Law 5/2005 on National Defence, which states: “The Armed Forces, together with the National Institutions and the Public Administrations, must preserve the security and well-being of citizens in case of serious risk, catastrophe, calamity and other public needs, in accordance with current legislation.” However, the first time that the Armed Forces took on this task was with Operation Balmis, as part of the effort to defeat COVID-19 (except for interventions of the Military Emergency Unit and 43 Air Force Group as well as minor interventions by some other units in recent years). Operation Balmis, which involved over 188,000 military professionals, was the largest peacetime effort in the history of the Spanish Armed Forces.

Spanish Royal Decree 463/2020 from 14 March 2020, on the state of alarm, was the legal framework for involving the Armed Forces in the fight against the pandemic. As soon as the political directives were received, it was decided to launch a military operation conducted by the Armed Forces. The Operations Command and the Joint Chiefs of Staff began planning and, almost simultaneously, executing Operation Balmis. It was named after the Spanish military doctor who had the insight to effectively bring the smallpox vaccine from Europe to the Americas in the 19th century.

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under operation Balmis by location. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under Operation Balmis by type. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

Several factors were key to the success of Operation Balmis. The unit of command was adapted, the chain of command was simplified, and procedures were streamlined from requests for assistance to their fulfillment. All available assets worked under the Operations Command, organised into five Component Commands: Land, Sea, Air, Emergency and Military Health. Even the operation logistics were centralised.

Requests for support were forwarded directly to the Operations Command through the Government Delegates (the highest representatives of the national government in the different regions), who then forwarded them to the different ministries to manage the crisis. This support was validated, assigned and ordered in a systematic and simple process that allowed the requests to be fulfilled quickly. Basically, four main areas of support were considered: logistics, health, security and infrastructures. The most common tasks were disinfection, transfer of the sick, building field hospitals, transport of medical equipment by air and land, and presence to contribute to public security.

This last task was one of the first to be scaled down after the initial phase, as the population accepted the instructions for total mass lockdown. Nevertheless, patrols were maintained to support the police in border controls and critical infrastructure security until the end of the Operation.

The most delicate task for the soldiers was to transfer and guard the deceased in the temporary morgues set up during the period when the capacity of funeral services was overwhelmed. Initially, the Military Emergency Unit was in charge of this mission, which was later joined by other military professionals. One of the most common and critical tasks were military interventions in nursing homes (5,301), given the vulnerability of this population and the great extent to which it was affected by the pandemic. Initially, major activities included disinfections (11,061), although civilian professionals were also trained in the final stages in this task and were able to take over from the military units.

Transport was another key requirement, especially in the early stages, when medical material was brought from China to Spain in military aircrafts. Also of major importance is the support given to food pantries, which used military means to distribute food to the most deprived people.

<div><ul style="text-align: center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Interventions under Operation Balmis. 2020. España.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Geographical footprint of the armed forces under Operation Balmis. 2020. España.]]

</li>
</ul></div>
{{ANEAutoria|Autores= Miguel Ángel Villaroya Vilalta}}

{{ANESubirArriba}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

{{ANETextoEpigrafe|epigrafe=Recursos relacionados}}

{{#ask:

[[Tiene palabra clave::~*camas*]] OR

[[Tiene palabra clave::unidad militar de emergencias]] OR [[Tiene palabra clave::~*solidarios*]] OR

[[Tiene ID serie temporal::13081]]

|mainlabel=Vista previa
|?Tiene título alternativo 1#=Título
|?Pertenece a subtema=Subtema
|?Tiene JPG=JPG
|?Tiene versión interactiva=Interactivo
|?Tiene extensión temporal=Extensión temporal
|?Tiene datos brutos publicados#Si,No=Datos a descarga
|?Tiene más información=Descarga completa

|headers=plain
|link=all
|limit=1000
|sort=Tiene título alternativo 1
|order=ascending
|class=datatable
}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

[[Categoría:Servicios y equipamientos sociales]]

Talk:Putting resources into action

2022-03-10T16:24:38Z

Usr1:

{{ANEEtiqueta|palabrasclave=covid-19, pandemia, covid19, camas en UCI, hoteles medicalizados, fuerzas armadas en la pandemia, Twitter|descripcion=Estudio cartográfico de los recursos movilizados|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Putting resources into action}}

The resources put into action to fight against the COVID-19 pandemic are hard to be quantified because of the many different stakeholders involved, the heterogeneity of the actions taken and their sometimes intangible nature; proof of the latter was the significant solidarity movement that took place during the hardest times of the first wave of the pandemic (see chapter on ''[[Solidarity Actions | Solidarity Actions]]''). This chapter focuses, however, on two aspects that may help understand the swift response of the public administrations to the extraordinary situation from March 2020. It first shows some indicators on the effort made in the health field as well as the experience at ''Lozano Blesa University Hospital'' in Saragossa (Zaragoza). Second, the text delves into how the Armed Forces participated in this deployment, what took place under Operation Balmis.

There is no reliable record of which new resources were put into action during the first wave of the pandemic aimed at fighting the coronavirus and reducing its impact. Some decisive links in the process of building an effective response were for instance the financial efforts of the public administration, the initiatives that came from within society both individually and in groups, the dedication of the medical staff and the donations from companies.

<div><ul style="text-align: left; float:right">

<li style="display: inline-block">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Evolution in the number of ICU beds during the first wave of the pandemic. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Beds in medicalised hotels during the first wave of the pandemic. 2020. Spain.]]
</li>
</ul></div>
A first indicator depicting the changes that took place in hospitals was the increased availability of Intensive Care Unit (ICU) beds, which is shown by regions on the map ''[[:File:Evolution in the number of ICU beds during the first wave of the pandemic]]''. There were 150% more ICU beds (excluding newborns) towards the beginning of April 2020 than in January 2020 in the public and private healthcare systems –including both beds with and without respirators–. After the peak of the first wave of the pandemic, a decrease was registered in early June; even so, there were 78% more ICU beds occupied at the end of the first semester of 2020 than at the beginning of the year.

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Mensajes en Twitter solidarios con el hospital de IFEMA. 2020. España.]]

Some other actions were also taken in order to increase the capacity to accommodate the growing number of infected people requiring hospital admission, e.g. hotel beds were medicalised and field hospitals were built as presented on the map on ''[[:File:Beds in medicalised hotels during the first wave of the pandemic|Beds in medicalised hotels during the first wave of the pandemic]]'' shows the result of this action, with a large number of beds being made available in non-medical centres.
Regional authorities strove to multiply the capacity to care for patients requiring hospital admission. For example, the Region of Madrid set up the facilities at Madrid Trade Fair as a field hospital. The particular impact of the first wave of the pandemic on this territory shall be taken into account. Nearly 5,000 patients were admitted and more than 1,200 healthcare professionals worked from 23 March to 1 May 2020 in Halls 5 and 7 at Madrid Trade Fair.
There was also an intense solidarity movement based on social initiatives. Social networks served to connect demands and offers; details on the flow of messages on Twitter referring to solidarity deployed in this field hospital at Madrid Trade Fair are shown on the graph.

{{ANEAutoria|Autores= José Sancho Comíns}}

{{ANETextoDestacado|titulo=«LOZANO BLESA» UNIVERSITY HOSPITAL IN SARAGOSSA (ZARAGOZA)|contenido=This note is a brief summary of the experience at Lozano Blesa University Hospital in Saragossa (Zaragoza) which may be understood as an example of the situation in many hospitals in Spain during the first wave of the pandemic. This hospital covers a large healthcare area including a population heavily affected by COVID-19 as well as a large number of nursing homes. The COVID-19 Group was created in January 2020 at this hospital and included professionals from Preventive Medicine, Occupational Risk Prevention, Emergency, Microbiology, Internal Medicine, Infectious Diseases and Intensive Care departments, together with representatives from the hospital medical and nursing management teams. This COVID-19 group drew up a Contingency Plan for the hospital, whose forecasts were soon largely exceeded. The first COVID-19 case was detected on 3 March 2020.
Special care was taken to ensure that the actions triggered were supported from both a human and a technical perspective. With regard to the former, the high level of professionalism of all health and non-health workers at hospital shall be highlighted: doctors, nurses, laboratory technicians, cleaning staff, technicians who control ventilation circuits and many other professionals worked double shifts, overtime, etc. Protective measures were increased at hospital. All possible scenarios as well as the protective equipment to be worn were defined. Special attention was paid to staff protection training. The so-called Extended Universal Precautions were extended to the entire hospital in order to protect other patients and hospital employees. The workflow was modified and professionals who had never worked together before started to form multidisciplinary teams: neurologists, allergists, haematologists, anaesthesiologists, etc. started to work side by side with internists and intensivists.
From a technical point of view, decisions were made based on new data received. The health system was not prepared for a phenomenon of such magnitude and so long-lasting. Nevertheless, efforts were multiplied to adapt the hospital structure, equipment and organisation. A new intensive care unit was built in record time. The Surgical Block was adapted to accommodate COVID-19 patients and non-COVID-19 patients, the inpatient area was reorganised with exclusive areas for COVID-19 patients, a separate circuit was set up in the emergency department for possible infected patients, etc.
.}}
{{ANEAutoria|Autores= María José Amorín Calzada}}
{{ANETextoEpigrafe|epigrafe=Operation BALMIS}}

[[File:Logo Monografía.jpg|left|thumb|300px|Illustration: Datos generales de la Operación BALMIS. 2020. España.]]

The intervention of the Armed Forces in the fight against the COVID-19 pandemic under Operation Balmis was an example of the so-called new missions of the Navy, the Army and the Air Force, as a key tool for solving all kinds of crisis. The missions allotted to the Armed Forces were set forth in Spanish Organic Law 5/2005 on National Defence, which states: “The Armed Forces, together with the National Institutions and the Public Administrations, must preserve the security and well-being of citizens in case of serious risk, catastrophe, calamity and other public needs, in accordance with current legislation.” However, the first time that the Armed Forces took on this task was with Operation Balmis, as part of the effort to defeat COVID-19 (except for interventions of the Military Emergency Unit and 43 Air Force Group as well as minor interventions by some other units in recent years). Operation Balmis, which involved over 188,000 military professionals, was the largest peacetime effort in the history of the Spanish Armed Forces.

Spanish Royal Decree 463/2020 from 14 March 2020, on the state of alarm, was the legal framework for involving the Armed Forces in the fight against the pandemic. As soon as the political directives were received, it was decided to launch a military operation conducted by the Armed Forces. The Operations Command and the Joint Chiefs of Staff began planning and, almost simultaneously, executing Operation Balmis. It was named after the Spanish military doctor who had the insight to effectively bring the smallpox vaccine from Europe to the Americas in the 19th century.

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under operation Balmis by location. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under Operation Balmis by type. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

Several factors were key to the success of Operation Balmis. The unit of command was adapted, the chain of command was simplified, and procedures were streamlined from requests for assistance to their fulfillment. All available assets worked under the Operations Command, organised into five Component Commands: Land, Sea, Air, Emergency and Military Health. Even the operation logistics were centralised.

Requests for support were forwarded directly to the Operations Command through the Government Delegates (the highest representatives of the national government in the different regions), who then forwarded them to the different ministries to manage the crisis. This support was validated, assigned and ordered in a systematic and simple process that allowed the requests to be fulfilled quickly. Basically, four main areas of support were considered: logistics, health, security and infrastructures. The most common tasks were disinfection, transfer of the sick, building field hospitals, transport of medical equipment by air and land, and presence to contribute to public security.

This last task was one of the first to be scaled down after the initial phase, as the population accepted the instructions for total mass lockdown. Nevertheless, patrols were maintained to support the police in border controls and critical infrastructure security until the end of the Operation.

The most delicate task for the soldiers was to transfer and guard the deceased in the temporary morgues set up during the period when the capacity of funeral services was overwhelmed. Initially, the Military Emergency Unit was in charge of this mission, which was later joined by other military professionals. One of the most common and critical tasks were military interventions in nursing homes (5,301), given the vulnerability of this population and the great extent to which it was affected by the pandemic. Initially, major activities included disinfections (11,061), although civilian professionals were also trained in the final stages in this task and were able to take over from the military units.

Transport was another key requirement, especially in the early stages, when medical material was brought from China to Spain in military aircrafts. Also of major importance is the support given to food pantries, which used military means to distribute food to the most deprived people.

<div><ul style="text-align: center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Interventions under Operation Balmis. 2020. España.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Geographical footprint of the armed forces under Operation Balmis. 2020. España.]]

</li>
</ul></div>
{{ANEAutoria|Autores= Miguel Ángel Villaroya Vilalta}}

{{ANESubirArriba}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

{{ANETextoEpigrafe|epigrafe=Recursos relacionados}}

{{#ask:

[[Tiene palabra clave::~*camas*]] OR

[[Tiene palabra clave::unidad militar de emergencias]] OR [[Tiene palabra clave::~*solidarios*]] OR

[[Tiene ID serie temporal::13081]]

|mainlabel=Vista previa
|?Tiene título alternativo 1#=Título
|?Pertenece a subtema=Subtema
|?Tiene JPG=JPG
|?Tiene versión interactiva=Interactivo
|?Tiene extensión temporal=Extensión temporal
|?Tiene datos brutos publicados#Si,No=Datos a descarga
|?Tiene más información=Descarga completa

|headers=plain
|link=all
|limit=1000
|sort=Tiene título alternativo 1
|order=ascending
|class=datatable
}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

[[Categoría:Servicios y equipamientos sociales]]

Talk:Putting resources into action

2022-03-10T16:24:02Z

Usr1:

{{ANEEtiqueta|palabrasclave=covid-19, pandemia, covid19, camas en UCI, hoteles medicalizados, fuerzas armadas en la pandemia, Twitter|descripcion=Estudio cartográfico de los recursos movilizados|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Putting resources into action}}

The resources put into action to fight against the COVID-19 pandemic are hard to be quantified because of the many different stakeholders involved, the heterogeneity of the actions taken and their sometimes intangible nature; proof of the latter was the significant solidarity movement that took place during the hardest times of the first wave of the pandemic (see chapter on ''[[Solidarity Actions | Solidarity Actions]]''). This chapter focuses, however, on two aspects that may help understand the swift response of the public administrations to the extraordinary situation from March 2020. It first shows some indicators on the effort made in the health field as well as the experience at ''Lozano Blesa University Hospital'' in Saragossa (Zaragoza). Second, the text delves into how the Armed Forces participated in this deployment, what took place under Operation Balmis.

There is no reliable record of which new resources were put into action during the first wave of the pandemic aimed at fighting the coronavirus and reducing its impact. Some decisive links in the process of building an effective response were for instance the financial efforts of the public administration, the initiatives that came from within society both individually and in groups, the dedication of the medical staff and the donations from companies.

<div><ul style="text-align: left; float:right">

<li style="display: inline-block">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Evolution in the number of ICU beds during the first wave of the pandemic. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Beds in medicalised hotels during the first wave of the pandemic. 2020. Spain.]]
</li>
</ul></div>
A first indicator depicting the changes that took place in hospitals was the increased availability of Intensive Care Unit (ICU) beds, which is shown by regions on the map ''[[:File:Evolution in the number of ICU beds during the first wave of the pandemic|Evolution of ICU beds during the first wave of the pandemic]]''. There were 150% more ICU beds (excluding newborns) towards the beginning of April 2020 than in January 2020 in the public and private healthcare systems –including both beds with and without respirators–. After the peak of the first wave of the pandemic, a decrease was registered in early June; even so, there were 78% more ICU beds occupied at the end of the first semester of 2020 than at the beginning of the year.

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Mensajes en Twitter solidarios con el hospital de IFEMA. 2020. España.]]

Some other actions were also taken in order to increase the capacity to accommodate the growing number of infected people requiring hospital admission, e.g. hotel beds were medicalised and field hospitals were built as presented on the map on ''[[:File:Beds in medicalised hotels during the first wave of the pandemic|Beds in medicalised hotels during the first wave of the pandemic]]'' shows the result of this action, with a large number of beds being made available in non-medical centres.
Regional authorities strove to multiply the capacity to care for patients requiring hospital admission. For example, the Region of Madrid set up the facilities at Madrid Trade Fair as a field hospital. The particular impact of the first wave of the pandemic on this territory shall be taken into account. Nearly 5,000 patients were admitted and more than 1,200 healthcare professionals worked from 23 March to 1 May 2020 in Halls 5 and 7 at Madrid Trade Fair.
There was also an intense solidarity movement based on social initiatives. Social networks served to connect demands and offers; details on the flow of messages on Twitter referring to solidarity deployed in this field hospital at Madrid Trade Fair are shown on the graph.

{{ANEAutoria|Autores= José Sancho Comíns}}

{{ANETextoDestacado|titulo=«LOZANO BLESA» UNIVERSITY HOSPITAL IN SARAGOSSA (ZARAGOZA)|contenido=This note is a brief summary of the experience at Lozano Blesa University Hospital in Saragossa (Zaragoza) which may be understood as an example of the situation in many hospitals in Spain during the first wave of the pandemic. This hospital covers a large healthcare area including a population heavily affected by COVID-19 as well as a large number of nursing homes. The COVID-19 Group was created in January 2020 at this hospital and included professionals from Preventive Medicine, Occupational Risk Prevention, Emergency, Microbiology, Internal Medicine, Infectious Diseases and Intensive Care departments, together with representatives from the hospital medical and nursing management teams. This COVID-19 group drew up a Contingency Plan for the hospital, whose forecasts were soon largely exceeded. The first COVID-19 case was detected on 3 March 2020.
Special care was taken to ensure that the actions triggered were supported from both a human and a technical perspective. With regard to the former, the high level of professionalism of all health and non-health workers at hospital shall be highlighted: doctors, nurses, laboratory technicians, cleaning staff, technicians who control ventilation circuits and many other professionals worked double shifts, overtime, etc. Protective measures were increased at hospital. All possible scenarios as well as the protective equipment to be worn were defined. Special attention was paid to staff protection training. The so-called Extended Universal Precautions were extended to the entire hospital in order to protect other patients and hospital employees. The workflow was modified and professionals who had never worked together before started to form multidisciplinary teams: neurologists, allergists, haematologists, anaesthesiologists, etc. started to work side by side with internists and intensivists.
From a technical point of view, decisions were made based on new data received. The health system was not prepared for a phenomenon of such magnitude and so long-lasting. Nevertheless, efforts were multiplied to adapt the hospital structure, equipment and organisation. A new intensive care unit was built in record time. The Surgical Block was adapted to accommodate COVID-19 patients and non-COVID-19 patients, the inpatient area was reorganised with exclusive areas for COVID-19 patients, a separate circuit was set up in the emergency department for possible infected patients, etc.
.}}
{{ANEAutoria|Autores= María José Amorín Calzada}}
{{ANETextoEpigrafe|epigrafe=Operation BALMIS}}

[[File:Logo Monografía.jpg|left|thumb|300px|Illustration: Datos generales de la Operación BALMIS. 2020. España.]]

The intervention of the Armed Forces in the fight against the COVID-19 pandemic under Operation Balmis was an example of the so-called new missions of the Navy, the Army and the Air Force, as a key tool for solving all kinds of crisis. The missions allotted to the Armed Forces were set forth in Spanish Organic Law 5/2005 on National Defence, which states: “The Armed Forces, together with the National Institutions and the Public Administrations, must preserve the security and well-being of citizens in case of serious risk, catastrophe, calamity and other public needs, in accordance with current legislation.” However, the first time that the Armed Forces took on this task was with Operation Balmis, as part of the effort to defeat COVID-19 (except for interventions of the Military Emergency Unit and 43 Air Force Group as well as minor interventions by some other units in recent years). Operation Balmis, which involved over 188,000 military professionals, was the largest peacetime effort in the history of the Spanish Armed Forces.

Spanish Royal Decree 463/2020 from 14 March 2020, on the state of alarm, was the legal framework for involving the Armed Forces in the fight against the pandemic. As soon as the political directives were received, it was decided to launch a military operation conducted by the Armed Forces. The Operations Command and the Joint Chiefs of Staff began planning and, almost simultaneously, executing Operation Balmis. It was named after the Spanish military doctor who had the insight to effectively bring the smallpox vaccine from Europe to the Americas in the 19th century.

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under operation Balmis by location. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under Operation Balmis by type. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

Several factors were key to the success of Operation Balmis. The unit of command was adapted, the chain of command was simplified, and procedures were streamlined from requests for assistance to their fulfillment. All available assets worked under the Operations Command, organised into five Component Commands: Land, Sea, Air, Emergency and Military Health. Even the operation logistics were centralised.

Requests for support were forwarded directly to the Operations Command through the Government Delegates (the highest representatives of the national government in the different regions), who then forwarded them to the different ministries to manage the crisis. This support was validated, assigned and ordered in a systematic and simple process that allowed the requests to be fulfilled quickly. Basically, four main areas of support were considered: logistics, health, security and infrastructures. The most common tasks were disinfection, transfer of the sick, building field hospitals, transport of medical equipment by air and land, and presence to contribute to public security.

This last task was one of the first to be scaled down after the initial phase, as the population accepted the instructions for total mass lockdown. Nevertheless, patrols were maintained to support the police in border controls and critical infrastructure security until the end of the Operation.

The most delicate task for the soldiers was to transfer and guard the deceased in the temporary morgues set up during the period when the capacity of funeral services was overwhelmed. Initially, the Military Emergency Unit was in charge of this mission, which was later joined by other military professionals. One of the most common and critical tasks were military interventions in nursing homes (5,301), given the vulnerability of this population and the great extent to which it was affected by the pandemic. Initially, major activities included disinfections (11,061), although civilian professionals were also trained in the final stages in this task and were able to take over from the military units.

Transport was another key requirement, especially in the early stages, when medical material was brought from China to Spain in military aircrafts. Also of major importance is the support given to food pantries, which used military means to distribute food to the most deprived people.

<div><ul style="text-align: center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Interventions under Operation Balmis. 2020. España.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Geographical footprint of the armed forces under Operation Balmis. 2020. España.]]

</li>
</ul></div>
{{ANEAutoria|Autores= Miguel Ángel Villaroya Vilalta}}

{{ANESubirArriba}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

{{ANETextoEpigrafe|epigrafe=Recursos relacionados}}

{{#ask:

[[Tiene palabra clave::~*camas*]] OR

[[Tiene palabra clave::unidad militar de emergencias]] OR [[Tiene palabra clave::~*solidarios*]] OR

[[Tiene ID serie temporal::13081]]

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|?Tiene título alternativo 1#=Título
|?Pertenece a subtema=Subtema
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|?Tiene extensión temporal=Extensión temporal
|?Tiene datos brutos publicados#Si,No=Datos a descarga
|?Tiene más información=Descarga completa

|headers=plain
|link=all
|limit=1000
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{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

[[Categoría:Servicios y equipamientos sociales]]

Talk:Putting resources into action

2022-03-10T16:21:54Z

Usr1:

{{ANEEtiqueta|palabrasclave=covid-19, pandemia, covid19, camas en UCI, hoteles medicalizados, fuerzas armadas en la pandemia, Twitter|descripcion=Estudio cartográfico de los recursos movilizados|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Putting resources into action}}

The resources put into action to fight against the COVID-19 pandemic are hard to be quantified because of the many different stakeholders involved, the heterogeneity of the actions taken and their sometimes intangible nature; proof of the latter was the significant solidarity movement that took place during the hardest times of the first wave of the pandemic (see chapter on ''[[Solidarity Actions | Solidarity Actions]]''). This chapter focuses, however, on two aspects that may help understand the swift response of the public administrations to the extraordinary situation from March 2020. It first shows some indicators on the effort made in the health field as well as the experience at ''Lozano Blesa University Hospital'' in Saragossa (Zaragoza). Second, the text delves into how the Armed Forces participated in this deployment, what took place under Operation Balmis.

There is no reliable record of which new resources were put into action during the first wave of the pandemic aimed at fighting the coronavirus and reducing its impact. Some decisive links in the process of building an effective response were for instance the financial efforts of the public administration, the initiatives that came from within society both individually and in groups, the dedication of the medical staff and the donations from companies.

<div><ul style="text-align: left; float:right">

<li style="display: inline-block">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Evolution in the number of ICU beds during the first wave of the pandemic. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Beds in medicalised hotels during the first wave of the pandemic. 2020. Spain.]]
</li>
</ul></div>
A first indicator depicting the changes that took place in hospitals was the increased availability of Intensive Care Unit (ICU) beds, which is shown by regions on the map ''[[:File:Evolution of ICU beds during the first wave of the pandemic|Evolution of ICU beds during the first wave of the pandemic]]''. There were 150% more ICU beds (excluding newborns) towards the beginning of April 2020 than in January 2020 in the public and private healthcare systems –including both beds with and without respirators–. After the peak of the first wave of the pandemic, a decrease was registered in early June; even so, there were 78% more ICU beds occupied at the end of the first semester of 2020 than at the beginning of the year.

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Mensajes en Twitter solidarios con el hospital de IFEMA. 2020. España.]]

Some other actions were also taken in order to increase the capacity to accommodate the growing number of infected people requiring hospital admission, e.g. hotel beds were medicalised and field hospitals were built as presented on the map on ''[[:File:Beds in medicalised hotels during the first wave of the pandemic|Beds in medicalised hotels during the first wave of the pandemic]]'' shows the result of this action, with a large number of beds being made available in non-medical centres.
Regional authorities strove to multiply the capacity to care for patients requiring hospital admission. For example, the Region of Madrid set up the facilities at Madrid Trade Fair as a field hospital. The particular impact of the first wave of the pandemic on this territory shall be taken into account. Nearly 5,000 patients were admitted and more than 1,200 healthcare professionals worked from 23 March to 1 May 2020 in Halls 5 and 7 at Madrid Trade Fair.
There was also an intense solidarity movement based on social initiatives. Social networks served to connect demands and offers; details on the flow of messages on Twitter referring to solidarity deployed in this field hospital at Madrid Trade Fair are shown on the graph.

{{ANEAutoria|Autores= José Sancho Comíns}}

{{ANETextoDestacado|titulo=«LOZANO BLESA» UNIVERSITY HOSPITAL IN SARAGOSSA (ZARAGOZA)|contenido=This note is a brief summary of the experience at Lozano Blesa University Hospital in Saragossa (Zaragoza) which may be understood as an example of the situation in many hospitals in Spain during the first wave of the pandemic. This hospital covers a large healthcare area including a population heavily affected by COVID-19 as well as a large number of nursing homes. The COVID-19 Group was created in January 2020 at this hospital and included professionals from Preventive Medicine, Occupational Risk Prevention, Emergency, Microbiology, Internal Medicine, Infectious Diseases and Intensive Care departments, together with representatives from the hospital medical and nursing management teams. This COVID-19 group drew up a Contingency Plan for the hospital, whose forecasts were soon largely exceeded. The first COVID-19 case was detected on 3 March 2020.
Special care was taken to ensure that the actions triggered were supported from both a human and a technical perspective. With regard to the former, the high level of professionalism of all health and non-health workers at hospital shall be highlighted: doctors, nurses, laboratory technicians, cleaning staff, technicians who control ventilation circuits and many other professionals worked double shifts, overtime, etc. Protective measures were increased at hospital. All possible scenarios as well as the protective equipment to be worn were defined. Special attention was paid to staff protection training. The so-called Extended Universal Precautions were extended to the entire hospital in order to protect other patients and hospital employees. The workflow was modified and professionals who had never worked together before started to form multidisciplinary teams: neurologists, allergists, haematologists, anaesthesiologists, etc. started to work side by side with internists and intensivists.
From a technical point of view, decisions were made based on new data received. The health system was not prepared for a phenomenon of such magnitude and so long-lasting. Nevertheless, efforts were multiplied to adapt the hospital structure, equipment and organisation. A new intensive care unit was built in record time. The Surgical Block was adapted to accommodate COVID-19 patients and non-COVID-19 patients, the inpatient area was reorganised with exclusive areas for COVID-19 patients, a separate circuit was set up in the emergency department for possible infected patients, etc.
.}}
{{ANEAutoria|Autores= María José Amorín Calzada}}
{{ANETextoEpigrafe|epigrafe=Operation BALMIS}}

[[File:Logo Monografía.jpg|left|thumb|300px|Illustration: Datos generales de la Operación BALMIS. 2020. España.]]

The intervention of the Armed Forces in the fight against the COVID-19 pandemic under Operation Balmis was an example of the so-called new missions of the Navy, the Army and the Air Force, as a key tool for solving all kinds of crisis. The missions allotted to the Armed Forces were set forth in Spanish Organic Law 5/2005 on National Defence, which states: “The Armed Forces, together with the National Institutions and the Public Administrations, must preserve the security and well-being of citizens in case of serious risk, catastrophe, calamity and other public needs, in accordance with current legislation.” However, the first time that the Armed Forces took on this task was with Operation Balmis, as part of the effort to defeat COVID-19 (except for interventions of the Military Emergency Unit and 43 Air Force Group as well as minor interventions by some other units in recent years). Operation Balmis, which involved over 188,000 military professionals, was the largest peacetime effort in the history of the Spanish Armed Forces.

Spanish Royal Decree 463/2020 from 14 March 2020, on the state of alarm, was the legal framework for involving the Armed Forces in the fight against the pandemic. As soon as the political directives were received, it was decided to launch a military operation conducted by the Armed Forces. The Operations Command and the Joint Chiefs of Staff began planning and, almost simultaneously, executing Operation Balmis. It was named after the Spanish military doctor who had the insight to effectively bring the smallpox vaccine from Europe to the Americas in the 19th century.

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under operation Balmis by location. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

[[File:Logo Monografía.jpg|right|thumb|200px|Statistical graph: Interventions under Operation Balmis by type. 2020. Spain.]]

[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of interventions under Operation Balmis. 2020. Spain.]]

Several factors were key to the success of Operation Balmis. The unit of command was adapted, the chain of command was simplified, and procedures were streamlined from requests for assistance to their fulfillment. All available assets worked under the Operations Command, organised into five Component Commands: Land, Sea, Air, Emergency and Military Health. Even the operation logistics were centralised.

Requests for support were forwarded directly to the Operations Command through the Government Delegates (the highest representatives of the national government in the different regions), who then forwarded them to the different ministries to manage the crisis. This support was validated, assigned and ordered in a systematic and simple process that allowed the requests to be fulfilled quickly. Basically, four main areas of support were considered: logistics, health, security and infrastructures. The most common tasks were disinfection, transfer of the sick, building field hospitals, transport of medical equipment by air and land, and presence to contribute to public security.

This last task was one of the first to be scaled down after the initial phase, as the population accepted the instructions for total mass lockdown. Nevertheless, patrols were maintained to support the police in border controls and critical infrastructure security until the end of the Operation.

The most delicate task for the soldiers was to transfer and guard the deceased in the temporary morgues set up during the period when the capacity of funeral services was overwhelmed. Initially, the Military Emergency Unit was in charge of this mission, which was later joined by other military professionals. One of the most common and critical tasks were military interventions in nursing homes (5,301), given the vulnerability of this population and the great extent to which it was affected by the pandemic. Initially, major activities included disinfections (11,061), although civilian professionals were also trained in the final stages in this task and were able to take over from the military units.

Transport was another key requirement, especially in the early stages, when medical material was brought from China to Spain in military aircrafts. Also of major importance is the support given to food pantries, which used military means to distribute food to the most deprived people.

<div><ul style="text-align: center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Interventions under Operation Balmis. 2020. España.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Geographical footprint of the armed forces under Operation Balmis. 2020. España.]]

</li>
</ul></div>
{{ANEAutoria|Autores= Miguel Ángel Villaroya Vilalta}}

{{ANESubirArriba}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

{{ANETextoEpigrafe|epigrafe=Recursos relacionados}}

{{#ask:

[[Tiene palabra clave::~*camas*]] OR

[[Tiene palabra clave::unidad militar de emergencias]] OR [[Tiene palabra clave::~*solidarios*]] OR

[[Tiene ID serie temporal::13081]]

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|?Tiene extensión temporal=Extensión temporal
|?Tiene datos brutos publicados#Si,No=Datos a descarga
|?Tiene más información=Descarga completa

|headers=plain
|link=all
|limit=1000
|sort=Tiene título alternativo 1
|order=ascending
|class=datatable
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{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos|anterior=[[First COVID-19 cases]]|siguiente=[[The rising phase of the pandemic]]}}

[[Categoría:Servicios y equipamientos sociales]]

Socio-economic and environmental impact worldwide and on the European Union

2022-03-10T15:41:25Z

Usr1:

{{ANEEtiqueta|palabrasclave=sección de la Monografía covid-19, sección I, pandemia, covid19, trabajo en el mundo, pobreza laboral en el mundo, horas de trabajo perdidas por COVID-19 en el mundo, PIB en el mundo, PIB en la Unión Europea, población parada en la Unión Europea, población ocupada en la Unión Europea, gases de efecto invernadero, emisiones de dióxido de carbono en el mundo, contaminación mundial en la pandemia|descripcion= Presentación cartográfica de los efectos sociales, económicos y ambientales en el mundo y en la Unión Europea|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Estructura temática (monografía COVID-19)|Estructura temática]]|seccion=[[Global context of the COVID-19 pandemic|Global context of the COVID-19 pandemic]]|capitulo=Socio-economic and environmental impact worldwide and on the European Union}}

The COVID-19 pandemic entailed a standstill to mobility and economic activities during the first half of 2020 that led to both an acute global economic recession and a short-term reduction in the environmental impact of human activities.

{{ANETextoEpigrafe|epigrafe=Socio-economic impact}}
<div><ul style="text-align: left; float:right; margin-left:0px; margin-right:0px">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|right|thumb|300px|Map: Gross Domestic Product per capita. 2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Producto-Interior-Bruto-per-capita-en-el-mundo_2020_mapa_18057_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Producto-Interior-Bruto-per-capita-en-el-mundo_2020_mapa_18057_spa.zip Datos].]]
</li>
<li style="display: inline-block; vertical-align: top">
[[File:Logo Monografía.jpg|right|thumb|300px|Map:Variation in Gross Domestic Product in the European Union. 2019-2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-del-Producto-Interior-Bruto-en-la-Union-Europea_2019-2020_mapa_18086_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-del-Producto-Interior-Bruto-en-la-Union-Europea_2019-2020_mapa_18086_spa.zip Datos].]]
</li>
</ul></div>
The [[:Archivo:Mundo_Producto-Interior-Bruto-per-capita-en-el-mundo_2020_mapa_18057_spa.jpg| ''Gross Domestic Product per capita'']] map reveals the contrast between the most developed countries, located in Europe, North America and Oceania, and the least developed ones, concentrated mainly in Africa. The impact of the 2020 economic crisis was uneven, with different implications for various parts of the world. Europe and the United States experienced a sharp drop in GDP as mobility restrictions and temporary company shutdowns curbed their economic activity. In contrast, despite successfully managing to control the pandemic, China, Australia and New Zealand experienced economic downturns mainly caused by the decline in exports due to the significant decrease in international trade.

With regard to Europe, the map showing the [[:Archivo:Europa_Variacion-del-Producto-Interior-Bruto-en-la-Union-Europea_2019-2020_mapa_18086_spa.jpg|''Variation in Gross Domestic Product in the European Union'']] shows two complementary variables, i.e. the 2020 GDP per capita by State and the variation in GDP between mid-2019 and mid-2020. In terms of GDP per capita, the States with the highest incomes were those located in Scandinavia, the Benelux, Germany, France, Austria and Ireland, whilst those with the lowest incomes were in Eastern Europe, especially Romania and Bulgaria. In terms of variation, however, the States that suffered the most severe economic contractions during the first half of 2020 were those on the shores of the Mediterranean, along with Belgium, Hungary and Romania. At the other end of the scale, Ireland, Luxembourg and the Scandinavian and Baltic States were the least impacted.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Lost working hours due to COVID-19. 2019-2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Horas-de-trabajo-perdidas-por-COVID--19-en-el-mundo_2019-2020_mapa_18065_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Horas-de-trabajo-perdidas-por-COVID--19-en-el-mundo_2019-2020_mapa_18065_spa.zip Datos]]]

The labour market is depicted by two graphs. Firstly, the graph on the [[:Archivo:Mundo_Evolucion-del-mercado-de-trabajo-en-el-mundo_2000-2020_graficoestadistico_18082_spa.jpg|''Evolution of the labour market worldwide'']] shows the evolution of global employment in the medium term, from 2000 to 2020. Only few significant variations are visible in this type of graph. However, it does show a decrease in the total number of workers and a moderate rise in unemployment during the transition from 2019 to 2020. For its part, the graph illustrating the [[:Archivo:Mundo_Distribucion-de-los-trabajadores-con-pobreza-laboral-en-el-mundo_2010-2020_graficoestadistico_18083_spa.jpg|''Global distribution of workers in poverty'']] confirms that a large part of the labour force in the least developed countries is living in poverty –particularly in Sub-Saharan Africa–, whilst moderate poverty spans throughout East Asia, South Asia and North Africa.

<div><ul style="text-align: left; float:right; margin-left:0px; margin-right:0px">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Evolution of the labour market worldwide. 2000-2020. World.]]
</li>
<li style="display: inline-block; vertical-align: top">
[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Global distribution of workers in poverty. 2010-2020. World.]]
</li>
</ul></div>

One statistic that is clearly indicative of the pandemic’s impact on business activity is the number of lost working hours. The map depicting the number of [[:Archivo:Mundo_Horas-de-trabajo-perdidas-por-COVID--19-en-el-mundo_2019-2020_mapa_18065_spa.jpg|''Lost working hours Due to COVID-19'']] shows the heavier burden of the crisis in Andean America (from Colombia to Argentina), part of Central America, the United Kingdom, several southerly EU Member States (Spain, Italy, Greece), South Africa, Morocco, Oman, Turkey, the Caucasus, the Indian subcontinent and the Philippines. Generally speaking, these territories were also the ones most affected by the pandemic, many of which already had fragile labour markets. At the other end of the scale are some of the countries that successfully managed to contain the virus, such as China, Australia and New Zealand, some countries in Indochina, Sub-Saharan Africa, Europe (Switzerland, Norway and Belarus) and several EU Member States (the Netherlands, Denmark, Estonia, Latvia, Poland and the Czech Republic).

<div><ul style="text-align: right; float:left; margin-left:0px; margin-right:0px">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Unemployment rates in the European Union in 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-paro-en-la-Union-Europea_2020_mapa_18102_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-paro-en-la-Union-Europea_2020_mapa_18102_spa.zip Datos].]]
</li>
<li style="display: inline-block; vertical-align: top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Employment rates in the European Union in 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-ocupacion-en-la-Union-Europea_2020_mapa_18103_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-ocupacion-en-la-Union-Europea_2020_mapa_18103_spa.zip Datos].]]
</li>
</ul></div>

Another analysis relevant to the study of how the crisis impacted the labour market is shown on the map depicting the [[:Archivo:Europa_Tasa-de-paro-en-la-Union-Europea_2020_mapa_18102_spa.jpg|'' Unemployment rates in the European Union in 2020'']]. Figures were clearly high for Spain, Greece and some Scandinavian and Baltic States. The Eastern States, Belgium, the Netherlands, Ireland and Portugal, however, had lower unemployment rates. Generally speaking, unemployment increased to a greater extent in States that previously had fragile labour markets and were therefore more exposed to the crisis. It is also worth mentioning that the relatively high data for Scandinavia could be linked to the fact that the these States tend to have better social protection schemes for the unemployed than the rest of the Union. Lastly, it should be noted that the temporary job protection measures succeeded in tempering the final figures for all EU Member States.

The last map related to the labour market shows the [[:Archivo:Europa_Tasa-de-ocupacion-en-la-Union-Europea_2020_mapa_18103_spa.jpg|''Employment rates in the European Union in 2020'']]. The highest employment rates were in the north and the lowest in the south. This map shows certain structural behaviours, such as the greater or lesser insertion of women in the labour market. Statistics for 2020 were heavily influenced by the furlough policies that most States introduced to counteract the pandemic’s impact on the labour market. The States with the highest employment rates were Sweden and the Netherlands, where full employment of both men and women in the context of a moderately ageing population may be pointed out. By contrast, Spain, Italy and Greece had the lowest employment figures, with high ageing and fewer women and young people in the labour market.

To summarise, the pandemic plunged humanity into a severe economic recession that was temporarily tempered by increased cash injections from the Central Banks (with the European Union and the United States leading the way), a notable rise in public spending as well as some other instruments, such as furlough policies. Nonetheless, as the world starts to overcome the worst of the crisis, each country shall address its level of indebtedness and face up to the effects the pandemic has had on employment.

{{ANETextoEpigrafe|epigrafe=Environmental impact}}
The COVID-19 pandemic had some effects on environment as well. The initial lockdowns and consequent reductions in business activity had a direct impact on air and water pollution as well as on greenhouse gas emissions in many developed countries.
Water quality in rivers and seas clearly improved due to a drastic reduction in industrial discharges. The difference was particularly remarkable in North America and Europe, where, for example, clear water in Venice’s canals could be seen. Wild animals were also quick to take advantage of the absence of humans on the streets and could be spotted roaming the avenues in some major European cities.
Energy demand fell globally by 4% and CO<sub>2</sub> emissions decreased by 5.8% in 2020, a fall the likes of which had not been seen since the Second World War. This prompted several international organisations, such as the International Energy Agency (IEA) and the World Meteorological Organisation (WMO), to revise their projections for greenhouse gas emissions during the third decade of the 21st century downwards from their pre-pandemic figures.

Unfortunately, however, if data are analysed by country or world region, there is not much cause for optimism. In China, air pollution and greenhouse gas emissions fell drastically during the first half of 2020 but began to recover before summer. In fact, figures for 2020 show in large cities, such as Beijing and Shanghai, a 5% increase in CO<sub>2</sub> emissions and polluting particles into the atmosphere compared to 2019. In the European Union and the United States, the fall in polluting emissions was very notable from March to May 2020 (between -20% and -25%), and also the remainder of the year also stayed below 2019 values.
The analysis by economic activities shows that the pollution caused by industry and energy decreased in the first half of 2020 and increased again during the second half of the year. By contrast, CO<sub>2</sub> emissions due to land and air transport also fell during the first half of 2020 but did not recover towards the end of the year.
<div><ul style="text-align: center;float:center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Variation in global CO<sub>2</sub> emissions due to the COVID-19 lockdown. 2019-2020. World.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Illustration: Forecast of global GHG emissions due to COVID-19. 2015-2030. World.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Variation in NO<sub>2</sub> concentration in Europe due to the COVID-19 Lockdown. 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-de-la-concentracion-de-NO2-debido-al-confinamiento-en-Europa_2020_mapa_18121_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-de-la-concentracion-de-NO2-debido-al-confinamiento-en-Europa_2020_mapa_18121_spa.zip Datos].]]
</li>
</ul></div>
{{ANEAutoria|Autores= Carlos Baños Castiñeira, Agustín Gámir Orueta, Rubén C. Lois González y Jorge Olcina Cantos}}
{{ANESubirArriba}}
{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanos
|anterior=[[Impact of the pandemic in the European Union]]
|siguiente=[[Población, poblamiento y comorbilidad]]
}}

[[Categoría:España en el mundo]]

Talk:Impact of the pandemic on the European Union

2022-03-10T15:40:43Z

Usr1:

{{ANEEtiqueta|palabrasclave=sección de la Monografía covid-19, sección I, pandemia, covid19, casos de COVID-19 en la Unión Europea, personal sanitario en la Unión Europea, mortalidad por COVID-19 en la Unión Europea, estructura demográfica en Europa, aeropuertos de la Unión Europea, ciudades de Europa, dinámica demográfica en Europa|descripcion= Análisis de la afección de la pandemia en la Unión Europea a través de mapas y gráficos estadísticos del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Estructura temática (monografía COVID-19)|Estructura temática]]|seccion=[[Global context of the COVID-19 pandemic]]|capitulo=Impact of the pandemic on the European Union}}

The European Union is very heterogeneous from a geographical point of view. Four different geographical aspects show this complexity and warrant analysis: population density, population age, urban system and main airports. This geographical diversity becomes a key explanatory factor when studying the pandemic’s differing impact on the different States, regions and municipalities.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Population density in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.zip Datos].]]

The first map shows the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Population density in the European Union'']]. There is a sharp contrast between some very densely populated areas and other less inhabited areas. However, it shall be borne in mind that densities are conditioned by the size of the territorial units represented. At one end of the scale, some regions have a density over 500 inhabitants/km<sup>2</sup>. One of these areas is the axis that runs from the Netherlands to northern Italy, encompassing a set of highly urbanised and developed territories that also happen to be the wealthiest and most urbanised area in Europe; these are the regions that French geographer Roger Brunet named the ''Blue Banana'' at the end of the 1980s. At the other end of the scale, some regions have a density under 50 inhabitants/km<sup>2</sup>, and although they may be few in number, they occupy large territories in the north of the continent (much of Sweden, Finland and the Baltic States), in the southwest [the inland regions in Spain, Alentejo region in Portugal, and Limousin and Corsica (Corse) in France], in the southeast (various parts of Greece and Bulgaria) and in the northwest of Ireland. A priori, it seems reasonable to set a direct relationship between high population density and the ease at which any infectious disease may spread. And the most densely populated areas of the Union did, indeed, record a high number of COVID-19 cases. However, within the most populated regions, the different speed with which the decision on lockdowns was taken led to the effects of the pandemic being more severe in some regions [e.g. Lombardy (Lombardia), Île de France…] than in others [e.g. Baden-Württemberg, Bavaria (Bayern)…].

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Population over the age of 65 in the European Union. 2019. Europe.[//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.zip Datos]. ]]
The population density map shall be combined with the [[Archivo:Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.jpg|''Population over the age of 65 in the European Union'']] map, which shows a part of the population that, if infected, has a higher morbidity rate due to the age. This map is clearly different to the population density map. The regions that stand out for having a higher number of people over the age of 65 are those that form the Iberian Atlantic Arc [especially Alentejo, Galicia, Asturias and Castile and León (Castilla y León)], the hinterland of France (especially Poitou-Charentes and Limousin), the north of Italy [more specifically Piedmont (Piemonte), Liguria, Friuli-Venezia-Giulia, Tuscany (Toscana) and Umbria], several regions in eastern Germany [Saxony (Sachsen), Saxony-Anhalt (Sachsen-Anhalt) and Thuringia (Thüringen)], a couple in Greece [Epirus (Épeiros) and the Ionian Islands (Iónia nisiá)] and one in Bulgaria (Northwest). In the case of the Iberian regions, older sex-age pyramids are combined with low demographic densities and a highly dispersed population, making the provision of healthcare for older adults even more challenging.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Most populous cities in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.zip Datos].]]
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Main airports in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.zip Datos].]]]
If we look at the map showing the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Most populous cities in the European Union'']], we may observe that the high rates of urbanisation in Europe translate to a network of numerous medium-sized (by global standards) cities in close proximity to one another. This urban pattern is totally different to the megacities in Asia, Africa, and the Americas. It is particularly prominent in the aforementioned Blue Banana, where several cities with over half a million inhabitants are located just a short distance from one another and are included in different Member States. The density of flows between these cities played a significant role in easing the spread of the virus across the continent, which led to the roll-out of coordinated measures throughout the twenty-seven EU States. However, unlike
in other continents, the size and morphology of the European urban system allowed the Authorities to quarantine the cities and neighbourhoods with the highest incidence of infection with relative ease, and this helped to control the pandemic in the heart of Europe.

The map showing the [[:Archivo:Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.jpg|''Main airports in the European Union'']] tries to highlight the virus’ points of access to the Union from abroad, i.e. the international airports where measures were gradually introduced to slow down the arrival of passengers, first from Asia, then from South Africa, Brazil and the United Kingdom. It also shows the other airports in the network, which subsequently helped to spread the pandemic internally. Air transport flows in the European Union have two main components: business travel and leisure travel. Travel for work-related reasons is more common in the airports located in the main urban areas. Falls in the number of passengers at these airports as a result of lockdowns and reduced mobility were considerable. Frankfurt airport went from 70 million passengers in 2019 to 19 million in 2020; Madrid from 60 million in 2019 to 17 million in 2020; and Munich (München) from 48 million in 2019 to 11 million in 2020. By contrast, airports on the Mediterranean coast and the Canary Islands (islas Canarias) rely heavily on tourism. However, given that the outbreak of the virus happened in winter, during months of low tourist activity, these airports were less impacted by restrictions on mobility during the initial weeks of the pandemic. In June 2020, when the incidence of the virus had been reduced, lockdown measures were scaled-back and the summer tourist season began, some regional administrations in these areas –particularly the island regions– ventured to test tourist corridors, in which virus control systems at airports played a crucial role.

[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Evolución de casos COVID-19 en la Unión Europea. 2020. Europa.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Casos de COVID-19 en la Unión Europea. 2020. Europa. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.zip Datos].]]]
Having analysed the four geographical aspects that show the internal heterogeneity of the European Union and played a decisive role in the way the COVID-19 pandemic impacted the different territories to varying degrees, the statistics have been synthesised on the maps and graphs included on the next page to show the impact of the pandemic across the European Union.

The map showing the [[:Archivo:Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.jpg|''COVID-19 cases in the European Union'']] reveals how the pandemic spread throughout the territory from January to June 2020. The growth of the disease was explosive during the month of March and the worst figures were registered in April. This may possibly be related to the fact that the European Union had underestimated the risk of a new virus emerging in China, so by the time the pandemic was declared, European health and governance systems were overwhelmed. However, the decision to impose a policy of strict lockdowns in the vast majority of Member States gradually succeeded in reducing the number of infections afterwards. An analysis of the impact by State shows that the severity of the pandemic was uneven: the eastern States were less affected (Slovakia and Hungary recorded the lowest figures); western States that reacted quickly were able to limit the impact (e.g. Portugal, Germany and France); other western States recorded the highest figures (Spain, Ireland, Belgium and Sweden had the highest incidence rates).

The map showing the [[:Archivo:Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.jpg|''Deaths from COVID-19 in the European Union'']] reveals a general trend that correlates with the patterns for COVID-19 cases. However, the number of deaths lags behind the number of cases by a couple of weeks. The only significant variation is to be found in Italy, which was the first State to register a community transmission. They reacted quickly and, therefore, managed to limit the transmission figures somewhat. Nevertheless, Italy recorded very high death rates. This is because there were few means to combat the disease during the first weeks of the pandemic, which meant the number of seriously ill and deceased was particularly high at this early stage (at one point, the mortality rate in Italy lied over 50 per 100,000 inhabitants).

The last map shows the number of [[:Archivo:Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.jpg|''Healthcare workers in the European Union'']]. In general, Europe is globally renowned for having solid and well-equipped healthcare systems, which translate to the continent’s high level of well-being. However, the availability of doctors and nurses is uneven: higher in the northern States (Finland, Sweden, Ireland, Germany, Belgium, Estonia and Lithuania), and lower in the southern and eastern States (for this indicator, Spain and Italy have similar figures to Bulgaria, possibly as a result of the cuts on their health budgets in the wake of the double recession from 2008-2013).

<div><ul style="text-align: center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of deaths from COVID-19 in the European Union. 2020. Europe.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Deaths from COVID-19 in the European Union. 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.zip Datos].]]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Healthcare workers in the European Union. 2018. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.zip Datos].]]]
</li>
</ul></div>

{{ANEAutoria|Autores= Agustín Gámir Orueta, Rubén C. Lois González, Ángel Miramontes Carballada y Ana Paula Santana Rodrigues}}
{{ANESubirArriba}}
{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanos
|anterior=[[Origin and global diffusion of the pandemic]]
|siguiente=[[Socio-economic and environmental impact worldwide and on the European Union]]
}}

[[Category:Spain in the World]]

Talk:Impact of the pandemic on the European Union

2022-03-10T15:39:45Z

Usr1:

{{ANEEtiqueta|palabrasclave=sección de la Monografía covid-19, sección I, pandemia, covid19, casos de COVID-19 en la Unión Europea, personal sanitario en la Unión Europea, mortalidad por COVID-19 en la Unión Europea, estructura demográfica en Europa, aeropuertos de la Unión Europea, ciudades de Europa, dinámica demográfica en Europa|descripcion= Análisis de la afección de la pandemia en la Unión Europea a través de mapas y gráficos estadísticos del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Estructura temática (monografía COVID-19)|Estructura temática]]|seccion=[[Impact of the pandemic in the European Union|Impact of the pandemic in the European Union]]|capitulo=Impact of the pandemic on the European Union}}

The European Union is very heterogeneous from a geographical point of view. Four different geographical aspects show this complexity and warrant analysis: population density, population age, urban system and main airports. This geographical diversity becomes a key explanatory factor when studying the pandemic’s differing impact on the different States, regions and municipalities.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Population density in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.zip Datos].]]

The first map shows the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Population density in the European Union'']]. There is a sharp contrast between some very densely populated areas and other less inhabited areas. However, it shall be borne in mind that densities are conditioned by the size of the territorial units represented. At one end of the scale, some regions have a density over 500 inhabitants/km<sup>2</sup>. One of these areas is the axis that runs from the Netherlands to northern Italy, encompassing a set of highly urbanised and developed territories that also happen to be the wealthiest and most urbanised area in Europe; these are the regions that French geographer Roger Brunet named the ''Blue Banana'' at the end of the 1980s. At the other end of the scale, some regions have a density under 50 inhabitants/km<sup>2</sup>, and although they may be few in number, they occupy large territories in the north of the continent (much of Sweden, Finland and the Baltic States), in the southwest [the inland regions in Spain, Alentejo region in Portugal, and Limousin and Corsica (Corse) in France], in the southeast (various parts of Greece and Bulgaria) and in the northwest of Ireland. A priori, it seems reasonable to set a direct relationship between high population density and the ease at which any infectious disease may spread. And the most densely populated areas of the Union did, indeed, record a high number of COVID-19 cases. However, within the most populated regions, the different speed with which the decision on lockdowns was taken led to the effects of the pandemic being more severe in some regions [e.g. Lombardy (Lombardia), Île de France…] than in others [e.g. Baden-Württemberg, Bavaria (Bayern)…].

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Population over the age of 65 in the European Union. 2019. Europe.[//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.zip Datos]. ]]
The population density map shall be combined with the [[Archivo:Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.jpg|''Population over the age of 65 in the European Union'']] map, which shows a part of the population that, if infected, has a higher morbidity rate due to the age. This map is clearly different to the population density map. The regions that stand out for having a higher number of people over the age of 65 are those that form the Iberian Atlantic Arc [especially Alentejo, Galicia, Asturias and Castile and León (Castilla y León)], the hinterland of France (especially Poitou-Charentes and Limousin), the north of Italy [more specifically Piedmont (Piemonte), Liguria, Friuli-Venezia-Giulia, Tuscany (Toscana) and Umbria], several regions in eastern Germany [Saxony (Sachsen), Saxony-Anhalt (Sachsen-Anhalt) and Thuringia (Thüringen)], a couple in Greece [Epirus (Épeiros) and the Ionian Islands (Iónia nisiá)] and one in Bulgaria (Northwest). In the case of the Iberian regions, older sex-age pyramids are combined with low demographic densities and a highly dispersed population, making the provision of healthcare for older adults even more challenging.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Most populous cities in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.zip Datos].]]
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Main airports in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.zip Datos].]]]
If we look at the map showing the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Most populous cities in the European Union'']], we may observe that the high rates of urbanisation in Europe translate to a network of numerous medium-sized (by global standards) cities in close proximity to one another. This urban pattern is totally different to the megacities in Asia, Africa, and the Americas. It is particularly prominent in the aforementioned Blue Banana, where several cities with over half a million inhabitants are located just a short distance from one another and are included in different Member States. The density of flows between these cities played a significant role in easing the spread of the virus across the continent, which led to the roll-out of coordinated measures throughout the twenty-seven EU States. However, unlike
in other continents, the size and morphology of the European urban system allowed the Authorities to quarantine the cities and neighbourhoods with the highest incidence of infection with relative ease, and this helped to control the pandemic in the heart of Europe.

The map showing the [[:Archivo:Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.jpg|''Main airports in the European Union'']] tries to highlight the virus’ points of access to the Union from abroad, i.e. the international airports where measures were gradually introduced to slow down the arrival of passengers, first from Asia, then from South Africa, Brazil and the United Kingdom. It also shows the other airports in the network, which subsequently helped to spread the pandemic internally. Air transport flows in the European Union have two main components: business travel and leisure travel. Travel for work-related reasons is more common in the airports located in the main urban areas. Falls in the number of passengers at these airports as a result of lockdowns and reduced mobility were considerable. Frankfurt airport went from 70 million passengers in 2019 to 19 million in 2020; Madrid from 60 million in 2019 to 17 million in 2020; and Munich (München) from 48 million in 2019 to 11 million in 2020. By contrast, airports on the Mediterranean coast and the Canary Islands (islas Canarias) rely heavily on tourism. However, given that the outbreak of the virus happened in winter, during months of low tourist activity, these airports were less impacted by restrictions on mobility during the initial weeks of the pandemic. In June 2020, when the incidence of the virus had been reduced, lockdown measures were scaled-back and the summer tourist season began, some regional administrations in these areas –particularly the island regions– ventured to test tourist corridors, in which virus control systems at airports played a crucial role.

[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Evolución de casos COVID-19 en la Unión Europea. 2020. Europa.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Casos de COVID-19 en la Unión Europea. 2020. Europa. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.zip Datos].]]]
Having analysed the four geographical aspects that show the internal heterogeneity of the European Union and played a decisive role in the way the COVID-19 pandemic impacted the different territories to varying degrees, the statistics have been synthesised on the maps and graphs included on the next page to show the impact of the pandemic across the European Union.

The map showing the [[:Archivo:Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.jpg|''COVID-19 cases in the European Union'']] reveals how the pandemic spread throughout the territory from January to June 2020. The growth of the disease was explosive during the month of March and the worst figures were registered in April. This may possibly be related to the fact that the European Union had underestimated the risk of a new virus emerging in China, so by the time the pandemic was declared, European health and governance systems were overwhelmed. However, the decision to impose a policy of strict lockdowns in the vast majority of Member States gradually succeeded in reducing the number of infections afterwards. An analysis of the impact by State shows that the severity of the pandemic was uneven: the eastern States were less affected (Slovakia and Hungary recorded the lowest figures); western States that reacted quickly were able to limit the impact (e.g. Portugal, Germany and France); other western States recorded the highest figures (Spain, Ireland, Belgium and Sweden had the highest incidence rates).

The map showing the [[:Archivo:Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.jpg|''Deaths from COVID-19 in the European Union'']] reveals a general trend that correlates with the patterns for COVID-19 cases. However, the number of deaths lags behind the number of cases by a couple of weeks. The only significant variation is to be found in Italy, which was the first State to register a community transmission. They reacted quickly and, therefore, managed to limit the transmission figures somewhat. Nevertheless, Italy recorded very high death rates. This is because there were few means to combat the disease during the first weeks of the pandemic, which meant the number of seriously ill and deceased was particularly high at this early stage (at one point, the mortality rate in Italy lied over 50 per 100,000 inhabitants).

The last map shows the number of [[:Archivo:Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.jpg|''Healthcare workers in the European Union'']]. In general, Europe is globally renowned for having solid and well-equipped healthcare systems, which translate to the continent’s high level of well-being. However, the availability of doctors and nurses is uneven: higher in the northern States (Finland, Sweden, Ireland, Germany, Belgium, Estonia and Lithuania), and lower in the southern and eastern States (for this indicator, Spain and Italy have similar figures to Bulgaria, possibly as a result of the cuts on their health budgets in the wake of the double recession from 2008-2013).

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[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of deaths from COVID-19 in the European Union. 2020. Europe.]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Map: Deaths from COVID-19 in the European Union. 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.zip Datos].]]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Map: Healthcare workers in the European Union. 2018. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.zip Datos].]]]
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{{ANEAutoria|Autores= Agustín Gámir Orueta, Rubén C. Lois González, Ángel Miramontes Carballada y Ana Paula Santana Rodrigues}}
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{{ANEPaginaDescargas (monografía COVID-19)}}
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|anterior=[[Origin and global diffusion of the pandemic]]
|siguiente=[[Socio-economic and environmental impact worldwide and on the European Union]]
}}

[[Category:Spain in the World]]

Talk:Origin and global diffusion of the pandemic

2022-03-10T15:34:05Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, origen de la pandemia, casos de COVID-19 en el mundo, personal sanitario en el mundo, mortalidad por COVID-19 en el mundo|descripcion= Estudio cartográfico del origen y difusión de la pandemia en el mundo|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[Global context of the COVID-19 pandemic|Global context of the COVID-19 pandemic]]|capitulo=Origin and global diffusion of the pandemic}}

SARS-CoV-2 virus, known as COVID-19, was declared a health emergency towards the end of 2019 following an outbreak in the Chinese city of Wuhan. However, the results of water analyses gathered later from various parts of the world suggest it was already circulating before then. Initially, it presented as an acute health problem that spread from the original outbreak in Wuhan to other major metropolitan regions in China, particularly Shanghai, Chongqing and the Pearl River Delta (Guangzhou, Hong Kong, Shenzhen, etc.). Analyses of this expansion from data on public transport use, particularly the high-speed train –despite the small amount of data available from China–, explain the pandemic’s rapid spread throughout its vast territory. During the final months of 2019, it appeared the spread of the infection would be limited to China and to a few of its neighbouring Asian countries. However, international airports eased its spread to the rest of the world, and the World Health Organisation (WHO) declared it a global pandemic in early March 2020. The spread of the pandemic may be observed on the map on the [[:Archivo:Mundo_Origen-y-difusion-del-COVID--19_2020_mapa_17781_spa.jpg|''origins and spread of COVID-19'']] , which shows the number of cases per country and month from February to July 2020. The peak of infections was registered in early April 2020. The lack of effective treatments for severe cases and little knowledge of how COVID-19 was transmitted during that period meant that it proved to be a highly lethal disease that resulted
in tens of thousands of deaths. However, the severe lockdowns applied in many countries succeeded in gradually reducing the number of deaths from that first wave.

The spatial diffusion of the pandemic across continents followed a predictable pattern. Initially, the virus spread from China to the rest of Asia. However, the strict lockdown measures adopted by some countries curbed the increase in infections there. Subsequently, the virus reached Europe, where it spread rapidly and soon reached the maximum number of infections in absolute terms. Later, COVID-19 was spread to the Americas, where it quickly spread. In fact, the Americas were the hardest hit continents, only lagging behind Europe for a few weeks. Finally, the pandemic also extended to the other continents but with a much lower incidence, as happened in Africa, for example. There is, however, a possibility that the apparent lower prevalence in Africa may owe more to a lack of effective recording and to the fact that this new virus was just one more health problem in societies that are already highly vulnerable to all kinds of infectious and contagious diseases.
<div><ul style="text-align: center">

<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution of COVID-19 cases worldwide. 2020. World.]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of deaths from COVID-19 worldwide. 2020. World.]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution of COVID-19 cases by major regions of the world. 2020. World.]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution of COVID-19 cases in most affected countries. 2020. World.]]

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[[File:Logo Monografía.jpg|left|thumb|300px|Map: Origins and spread of COVID-19 in China. 2020. China. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/China_Origen-y-difusion-del-COVID--19-en-China_2020_mapa_17842_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/China_Origen-y-difusion-del-COVID--19-en-China_2020_mapa_17842_spa.zip Datos].]]
[[File:Logo Monografía.jpg|right|thumb|300px|Map: Origins and spread of COVID-19. 2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Origen-y-difusion-del-COVID--19_2020_mapa_17781_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Origen-y-difusion-del-COVID--19_2020_mapa_17781_spa.zip Datos].]]
When analysing the spatial diffusion by country, it is helpful to differentiate the results in absolute and relative terms. On the one hand, China went from being the origin of the infection to playing a very discreet role in the global ranking. In absolute terms, the United States ranked as the world leader in terms of the total number of patients from the end of March 2020, with Brazil ranking second behind it. These two countries, with over 500 million inhabitants between them, have clearly topped all statistics in absolute terms since then. By contrast, in relative terms, Chile and the European States most impacted during the first wave, such as Belgium, Spain and Sweden, stand out for their high incidence among smaller populations. In other large countries, such as Russia and India, cases evolved in an ascending pattern before reaching a certain level of control, and they were amongst the top five countries for the total number of infections throughout the whole period under study.

Having analysed the origin and expansion of the pandemic worldwide, the following paragraphs deal with its magnitude. In this context, three key aspects shall be evaluated in order to understand the scale of the problem: the number of COVID-19 cases recorded between January and June, the number of deaths and the number of healthcare workers.

[[File:Logo Monografía.jpg|right|thumb|300px|Map:Healthcare workers. 2018. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Personal-sanitario-en-el-mundo_2018_mapa_17813_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Personal-sanitario-en-el-mundo_2018_mapa_17813_spa.zip Datos].]]

The number of COVID-19 cases shall also be analysed in absolute and relative terms. In absolute values, the countries with the highest number of recorded cases during the first wave of the pandemic were the United States, Brazil, India and Russia, which is consistent with their large size. However, what is striking is that some other countries with less than 70 million inhabitants also feature at the top of the list, including the United Kingdom, France, Italy, Spain, Chile, Peru and Saudi Arabia. The high number of cases in these countries could be attributed to the high demographic densities in their urban areas, which are home to a sizeable part of their population, and the lack of an effective response to the outbreak during the initial weeks of the pandemic that allowed the virus to spread. In relative terms, the countries with worst data are the United States, Panama, Brazil, Peru, Chile, Spain, Belgium, Luxembourg, Ireland, Sweden, Belarus, Armenia, Kuwait, Qatar, Oman and Saudi Arabia, some of which are also amongst those worst affected in absolute terms. It shall be noted that the governments of some countries, such as the United States, Brazil and Belarus, showed some initial scepticism toward the threat of the pandemic and failed to take decisive measures to contain the spread of the virus. The evolution of the pandemic in Sweden, for example, was probably influenced by the implementation of deliberately lax lockdown measures that sought to seek a supposed herd immunity.

At the opposite end of the scale, the countries with fewer relative cases of COVID-19 fall into one of two categories: either they applied stringent isolation measures with exemplary levels of compliance from their populations, i.e., China, South Korea, Japan, Taiwan, New Zealand and Australia, or they have poor levels of record-keeping, and COVID-19 is present alongside other infectious and contagious diseases (ebola, malaria, yellow fever, etc.), i.e. sub-Saharan Africa and some countries in South America and Asia.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: COVID-19 cases. 2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Casos-de-COVID--19-en-el-mundo_2020_mapa_17720_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Casos-de-COVID--19-en-el-mundo_2020_mapa_17720_spa.zip Datos].]]
The number of deaths from COVID-19 during the first wave of the pandemic was influenced by several factors, including scant knowledge of the new virus, the shortage of medical and infection prevention equipment, the absence of specific medical treatments, etc. As a result, the mortality rate stood at 5% during the initial months but decreased from June 2020 due to improved treatments and Personal Protective Equipment (PPE) availability. Given that almost 80% of those who died worldwide were men over 70 and women over 80, the age distribution of the population was another factor to have a considerable bearing on the countrywide outcome. It is in this context that the world map of relative mortality shall be understood, in which there are five Western European countries (the United Kingdom, Italy, Spain, Belgium and Sweden) with a high mortality rate per 100,000 inhabitants due to their older age-sex pyramids and despite their solid health services, which were caught unaware during the first few months of the pandemic. At the opposite end of the scale, China (although many authors question the reliability of their data), Asia in general and Africa may be found, yet younger populations shall be borne in mind.

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Deaths from COVID-19. 2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Fallecidos-por-COVID--19-en-el-mundo_2020_mapa_17724_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Fallecidos-por-COVID--19-en-el-mundo_2020_mapa_17724_spa.zip Datos].]]

With regard to healthcare workers, it is important to clarify two aspects: firstly, the data compiled by the United Nations for individual countries is for different years between 2010 and 2018; secondly, only doctors and nurses have been counted as healthcare workers, excluding other job categories in the sector, such as clinical assistants, pharmacy workers, etc. The main takeaway that may be extracted from this map is the sharp contrast between north and south. The north includes Europe, North America, Oceania, some of the Latin American countries and the Arab World. Indicators in this area are high both in absolute terms and relative to population size. In addition, nurses account for a large proportion of their total number of registered healthcare workers. This situation is especially true for Norway, Sweden, Finland, Germany, Switzerland, the United States, Chile, Lithuania and Belarus (these last two countries possibly as a legacy of the Soviet model). China, India and some Latin American countries have intermediate values for the number of healthcare workers relative to population size. In the south, by contrast, sub-Saharan Africa has the lowest availability of healthcare workers, with the few exceptions to this general rule being Botswana, Zambia, Gabon and Ghana.
<div><ul style="text-align: center; display: inline-block; vertical-align:top">
<div><ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=PANDEMIC|contenido=Spread of a new disease at a certain speed, widely and simultaneously throughout several geographical areas of the world. The World Health Organisation (WHO) declared COVID-19 a pandemic after more than 100 countries officially registered cases of the disease.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=COVID OR CORONAVIRUS|contenido=Family of viruses that affect some mammals, including humans. Some coronaviruses do not pose a threat to the health of humans. However, COVID-19 causes severe acute respiratory syndromes, attacks the lungs and may cause pneumonia. It may also cause gastric disorders and the loss of smell and taste.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=SPACIAL DIFFUSION|contenido=Spread, expansion or dissemination of a phenomenon over space and time. For the diffusion process to materialise, there must be a central source from which the
phenomenon originates, a set of potential receptors, communication channels between the source and the receptors, and a variable period of time. The diffusion process passes through nodal points and may involve a spread that is either random, similar to that of an oil slick, or hierarchical. Spatial diffusion models came into widespread use following the work of Swedish geographer T. Haggerstränd in 1968.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=TRANSMISIÓN COMMUNITY TRANSMISSION|contenido=Community transmission is said to be present when a virus is detected in several people within a specific population or territory, and the origin of the infections
are unknown. In the case of COVID-19, community transmission was detected when various people were tested positive for the disease after having recently visited China and other areas where the virus was spreading. This type of transmission denotes that the virus has been widespread in the community yet gone undetected for some time. When there is community transmission, the spread of the virus is deemed to be uncontrolled.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=POSITIVITY RATE|contenido=Percentage of COVID-19 tests that come back positive out of the total number of screening tests performed. A pandemic is deemed to be under control if
this percentage lies under 5%. A positivity rate over 5%, on the other hand, suggests many people are unaware they are infected and therefore community transmission exists and screening is required. The general consensus is that this indicator offers a more accurate assessment of the risk of infection than the daily number of positives because the number of screening tests performed may vary from day to day, whilst the positivity rate is a relative value that may always be used to compare different periods as long as the testing criteria remain the same.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=INCIDENCE|contenido=Number of detected cases of a disease in a given period and specific area or community. It could also be described as the probability that a person from a specific population will be affected by said disease. In addition, the incidence rate represents the speed at which new cases of the disease appear in the exposed population. It is calculated by dividing the number of new cases of the disease by the number of inhabitants. Lastly, the cumulative incidence is the proportion of people who fall ill in a given period of time. It is calculated by dividing the number of registered cases by the number of people who were free of the disease at the beginning of the period. It is usually calculated for every 100,000 inhabitants in periods of 7 to 14 days.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=LOCKDOWN|contenido=Extraordinary and emergency measure involving the temporary isolation of an individual, group or entire population for health or safety reasons. It involves restricting movements of the population in the affected area and closing leisure, tourism and cultural facilities. It may be a full restriction in very extreme cases, yet mostly it is not so strict and travelling is allowed to varying degrees for buying food and pharmaceutical products, for work, to provide care and in case of emergency.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=IMMUNITY|contenido=A person’s general level of resistance to or protection from an infectious disease or toxin. It is linked to the presence of antibodies or cells that act specifically against the microorganism that causes the infection. There are two types of immunity: active immunity, which usually lasts for years and is acquired naturally, as a consequence of an infection, or artificially, through a vaccine; and passive immunity, which has a short duration (from a few days to several months), and is obtained naturally, by maternal transmission, or artificially, by inoculating specific protective antibodies. The term ‘herd immunity’ is widely used to describe a situation in which a high proportion of a population has immunity and, therefore, the agent is less likely to spread.}}
</ul>
<ul style="text-align: left; margin-bottom: 0; margin-top: 0>
{{ANETextoAsociado48|titulo=PCR AND ANTIGEN TESTS|contenido=The acronym PCR stands for polymerase chain reaction. It is a type of test used to detect infections. It consists of extracting genetic material from a sample and comparing it with the genes found in viruses (for example, in SARS-CoV-2). The test involves inserting a swab (cotton bud) into the nose or mouth of the person suspected of being infected to collect a sample. If the PCR technique does not detect the virus’s genetic material, it is likely the person is not infected. The antigen test entails introducing a toxic molecule to the sample that generates an antibody reaction, making it possible to infer whether the subject is currently infected by the virus.}}
</ul>
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{{ANETextoAsociado48|titulo=SOCIAL DISTANCING|contenido=Term used to describe the imposition or recommendation that people keep a physical distance between themselves and anyone with whom they do not share a home. Its purpose is to prevent transmissions. This measure has become the most effective tool for containing the spread of COVID-19, especially when community transmission exists.}}
</ul></div>
</ul></div>

{{ANEAutoria|Autores= Agustín Gámir Orueta, Rubén C. Lois González, Ángel Miramontes Carballada y Ana Paula Santana Rodrigues}}
{{ANETextoEpigrafe|epigrafe=Recursos relacionados temáticamente}}

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[[Category:Spain in the World]]

Talk:Impact of the pandemic on the European Union

2022-03-10T15:33:14Z

Usr1:

{{ANEEtiqueta|palabrasclave=sección de la Monografía covid-19, sección I, pandemia, covid19, casos de COVID-19 en la Unión Europea, personal sanitario en la Unión Europea, mortalidad por COVID-19 en la Unión Europea, estructura demográfica en Europa, aeropuertos de la Unión Europea, ciudades de Europa, dinámica demográfica en Europa|descripcion= Análisis de la afección de la pandemia en la Unión Europea a través de mapas y gráficos estadísticos del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Estructura temática (monografía COVID-19)|Estructura temática]]|seccion=[[Impact of the pandemic in the European Union|Impact of the pandemic in the European Union]]|capitulo=Impact of the pandemic in the European Union}}

The European Union is very heterogeneous from a geographical point of view. Four different geographical aspects show this complexity and warrant analysis: population density, population age, urban system and main airports. This geographical diversity becomes a key explanatory factor when studying the pandemic’s differing impact on the different States, regions and municipalities.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Population density in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.zip Datos].]]

The first map shows the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Population density in the European Union'']]. There is a sharp contrast between some very densely populated areas and other less inhabited areas. However, it shall be borne in mind that densities are conditioned by the size of the territorial units represented. At one end of the scale, some regions have a density over 500 inhabitants/km<sup>2</sup>. One of these areas is the axis that runs from the Netherlands to northern Italy, encompassing a set of highly urbanised and developed territories that also happen to be the wealthiest and most urbanised area in Europe; these are the regions that French geographer Roger Brunet named the ''Blue Banana'' at the end of the 1980s. At the other end of the scale, some regions have a density under 50 inhabitants/km<sup>2</sup>, and although they may be few in number, they occupy large territories in the north of the continent (much of Sweden, Finland and the Baltic States), in the southwest [the inland regions in Spain, Alentejo region in Portugal, and Limousin and Corsica (Corse) in France], in the southeast (various parts of Greece and Bulgaria) and in the northwest of Ireland. A priori, it seems reasonable to set a direct relationship between high population density and the ease at which any infectious disease may spread. And the most densely populated areas of the Union did, indeed, record a high number of COVID-19 cases. However, within the most populated regions, the different speed with which the decision on lockdowns was taken led to the effects of the pandemic being more severe in some regions [e.g. Lombardy (Lombardia), Île de France…] than in others [e.g. Baden-Württemberg, Bavaria (Bayern)…].

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Population over the age of 65 in the European Union. 2019. Europe.[//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.zip Datos]. ]]
The population density map shall be combined with the [[Archivo:Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.jpg|''Population over the age of 65 in the European Union'']] map, which shows a part of the population that, if infected, has a higher morbidity rate due to the age. This map is clearly different to the population density map. The regions that stand out for having a higher number of people over the age of 65 are those that form the Iberian Atlantic Arc [especially Alentejo, Galicia, Asturias and Castile and León (Castilla y León)], the hinterland of France (especially Poitou-Charentes and Limousin), the north of Italy [more specifically Piedmont (Piemonte), Liguria, Friuli-Venezia-Giulia, Tuscany (Toscana) and Umbria], several regions in eastern Germany [Saxony (Sachsen), Saxony-Anhalt (Sachsen-Anhalt) and Thuringia (Thüringen)], a couple in Greece [Epirus (Épeiros) and the Ionian Islands (Iónia nisiá)] and one in Bulgaria (Northwest). In the case of the Iberian regions, older sex-age pyramids are combined with low demographic densities and a highly dispersed population, making the provision of healthcare for older adults even more challenging.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Most populous cities in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.zip Datos].]]
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Main airports in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.zip Datos].]]]
If we look at the map showing the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Most populous cities in the European Union'']], we may observe that the high rates of urbanisation in Europe translate to a network of numerous medium-sized (by global standards) cities in close proximity to one another. This urban pattern is totally different to the megacities in Asia, Africa, and the Americas. It is particularly prominent in the aforementioned Blue Banana, where several cities with over half a million inhabitants are located just a short distance from one another and are included in different Member States. The density of flows between these cities played a significant role in easing the spread of the virus across the continent, which led to the roll-out of coordinated measures throughout the twenty-seven EU States. However, unlike
in other continents, the size and morphology of the European urban system allowed the Authorities to quarantine the cities and neighbourhoods with the highest incidence of infection with relative ease, and this helped to control the pandemic in the heart of Europe.

The map showing the [[:Archivo:Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.jpg|''Main airports in the European Union'']] tries to highlight the virus’ points of access to the Union from abroad, i.e. the international airports where measures were gradually introduced to slow down the arrival of passengers, first from Asia, then from South Africa, Brazil and the United Kingdom. It also shows the other airports in the network, which subsequently helped to spread the pandemic internally. Air transport flows in the European Union have two main components: business travel and leisure travel. Travel for work-related reasons is more common in the airports located in the main urban areas. Falls in the number of passengers at these airports as a result of lockdowns and reduced mobility were considerable. Frankfurt airport went from 70 million passengers in 2019 to 19 million in 2020; Madrid from 60 million in 2019 to 17 million in 2020; and Munich (München) from 48 million in 2019 to 11 million in 2020. By contrast, airports on the Mediterranean coast and the Canary Islands (islas Canarias) rely heavily on tourism. However, given that the outbreak of the virus happened in winter, during months of low tourist activity, these airports were less impacted by restrictions on mobility during the initial weeks of the pandemic. In June 2020, when the incidence of the virus had been reduced, lockdown measures were scaled-back and the summer tourist season began, some regional administrations in these areas –particularly the island regions– ventured to test tourist corridors, in which virus control systems at airports played a crucial role.

[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Evolución de casos COVID-19 en la Unión Europea. 2020. Europa.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Casos de COVID-19 en la Unión Europea. 2020. Europa. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.zip Datos].]]]
Having analysed the four geographical aspects that show the internal heterogeneity of the European Union and played a decisive role in the way the COVID-19 pandemic impacted the different territories to varying degrees, the statistics have been synthesised on the maps and graphs included on the next page to show the impact of the pandemic across the European Union.

The map showing the [[:Archivo:Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.jpg|''COVID-19 cases in the European Union'']] reveals how the pandemic spread throughout the territory from January to June 2020. The growth of the disease was explosive during the month of March and the worst figures were registered in April. This may possibly be related to the fact that the European Union had underestimated the risk of a new virus emerging in China, so by the time the pandemic was declared, European health and governance systems were overwhelmed. However, the decision to impose a policy of strict lockdowns in the vast majority of Member States gradually succeeded in reducing the number of infections afterwards. An analysis of the impact by State shows that the severity of the pandemic was uneven: the eastern States were less affected (Slovakia and Hungary recorded the lowest figures); western States that reacted quickly were able to limit the impact (e.g. Portugal, Germany and France); other western States recorded the highest figures (Spain, Ireland, Belgium and Sweden had the highest incidence rates).

The map showing the [[:Archivo:Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.jpg|''Deaths from COVID-19 in the European Union'']] reveals a general trend that correlates with the patterns for COVID-19 cases. However, the number of deaths lags behind the number of cases by a couple of weeks. The only significant variation is to be found in Italy, which was the first State to register a community transmission. They reacted quickly and, therefore, managed to limit the transmission figures somewhat. Nevertheless, Italy recorded very high death rates. This is because there were few means to combat the disease during the first weeks of the pandemic, which meant the number of seriously ill and deceased was particularly high at this early stage (at one point, the mortality rate in Italy lied over 50 per 100,000 inhabitants).

The last map shows the number of [[:Archivo:Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.jpg|''Healthcare workers in the European Union'']]. In general, Europe is globally renowned for having solid and well-equipped healthcare systems, which translate to the continent’s high level of well-being. However, the availability of doctors and nurses is uneven: higher in the northern States (Finland, Sweden, Ireland, Germany, Belgium, Estonia and Lithuania), and lower in the southern and eastern States (for this indicator, Spain and Italy have similar figures to Bulgaria, possibly as a result of the cuts on their health budgets in the wake of the double recession from 2008-2013).

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[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of deaths from COVID-19 in the European Union. 2020. Europe.]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Map: Deaths from COVID-19 in the European Union. 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.zip Datos].]]]
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[[File:Logo Monografía.jpg|left|thumb|300px|Map: Healthcare workers in the European Union. 2018. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.zip Datos].]]]
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{{ANEAutoria|Autores= Agustín Gámir Orueta, Rubén C. Lois González, Ángel Miramontes Carballada y Ana Paula Santana Rodrigues}}
{{ANESubirArriba}}
{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanos
|anterior=[[Origin and global diffusion of the pandemic]]
|siguiente=[[Socio-economic and environmental impact worldwide and on the European Union]]
}}

[[Category:Spain in the World]]

Talk:Global context of the COVID-19 pandemic

2022-03-10T15:32:30Z

Usr1:

{{ANEEtiqueta|palabrasclave=sección I, pandemia, covid-19, covid19|descripcion= Análisis del contexto global de la pandemia COVID-19|url=}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANEIndiceSeccion
|color=#EFA824
|indice=
*[[Origin and global diffusion of the pandemic]]
*[[Impact of the pandemic on the European Union]]
*[[Socio-economic and environmental impact worldwide and on the European Union]]
|contenido=
Es inevitable comenzar esta monografía con una referencia suficientemente explícita al contexto planetario de la pandemia COVID-19. La Organización Mundial de
la Salud la declaró como tal una vez que certificaron casos de la enfermedad en más de cien países. La expansión amplia, simultánea y con cierta velocidad en múltiples áreas geográficas de todo el mundo obliga a presentar la globalidad de este fenómeno con el fin de acercarnos a una mejor comprensión de lo ocurrido en España.

El itinerario temático que se propone en esta primera sección se sustenta en tres ideas básicas: la constatación de que es una enfermedad que, desde su punto de ignición, se propagó por todo el mundo provocando un contagio masivo y, desgraciadamente, muchas muertes; la consideración especial que merece el marco comunitario de la Unión Europea en el que se inserta nuestro país; y, por último, el establecimiento de una primera aproximación a los efectos sociales, económicos y ambientales que ha producido globalmente la pandemia en los cinco continentes y, más en concreto, en la Unión Europea.

En el primero de los temas se presenta el origen y difusión del virus SARS-CoV-2 en China, la propagación al resto del mundo, el número de casos y fallecidos en los diferentes países y los recursos humanos, concretados en el personal sanitario, disponibles para afrontar la pandemia.

En un segundo tema se aborda el caso de la Unión Europea. En él se analizan, por un lado, algunos hechos que pudieran entenderse como condicionantes para provocar una mayor facilidad en la progresión del contagio y, consiguientemente, un mayor impacto de la emergencia sanitaria (localización de áreas con mayor densidad de población, ciudades más populosas, aeropuertos con un elevado tráfico de viajeros); por otro lado, se presenta la condición de la propia estructura demográfica en cuanto al peso de la población de más de 65 años. La muestra de dos indicadores clave de la evolución de la pandemia (los casos habidos y los fallecidos en cada país) resulta bien expresiva al respecto.

Por último, se han escogido tres indicadores clave para señalar los efectos sociales, económicos y ambientales más notables que, ya en esta primera ola, se han dejado sentir en el mundo en general y también en el marco de la Unión Europea: el nivel de población ocupada, la evolución del Producto Interior Bruto y las emisiones de NO<sub>2</sub>. La pandemia COVID-19 no solo ha tenido una incidencia sanitaria trágica, sino que impactó de manera ostensible en la actividad económica y el mercado de trabajo, por un lado, y, por otro, repercutió significativamente en el comportamiento de algunos indicadores medioambientales como consecuencia de la desaceleración del trajín económico.
}}

{{ANEAutoria|Autores=Rubén C. Lois González}}

{{ANEBibliografia|Texto=
*AGGARWAL, R.; BHATTACHARYA, S. y SINGH, S. (2020): «Mapping the Global Research and Clinical Trials in COVID-19», ''MedRXiv''. Disponible en: https://doi.org/10.1101/2020.06.27.20141788
*GUALLART MORENO, C. (2020): «La cartografía digital generada por la COVID-19: análisis y tipologías», ''Espacio, Tiempo y Forma'', serie VI-Geografía nº 13, pp. 103–134. Disponible en: https://doi.org/10.5944/etfvi.13.2020.27806
*JUERGENS, C. (2020): «Trustworthy COVID-19 Mapping: Geo-spatial Data Literacy Aspects of Choropleth Maps», ''KN Journal of Cartography and Geographic Information'', 23, pp. 1-7. Disponible en: https://doi.org/10.1007/s42489-020-00057-w
*LIU, N., et al. (2020): «Coronavirus disease 2019 (COVID-19): an evidence map of medical literatura», ''BMC Medical Research Methodology'' 20, 177. Disponible en: https://doi.org/10.1186/s12874-020-01059-y
*OSTASZEWSKI, M., et al. (2020): «COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms», ''Scientific Data'' 7, 136. Disponible en: https://doi.org/10.1038/s41597-020-0477-8
*POURGHASEMI H. R., et al. (2020): «Assessment of the outbreak risk, mapping and infection behavior of COVID-19: Application of the autoregressive integrated-moving average (ARIMA) and polynomial models», ''Plos One'' 15(7): e0236238. Disponible en: https://doi.org/10.1371/journal.pone.0236238
*SMITH C. D. y MENNIS J. (2020): «Incorporating Geographic Information Science and Technology in Response to the COVID-19 Pandemic». ''Preventing Chronic Disease'' 17: 200246. Disponible en: http://dx.doi.org/10.5888/pcd17.200246
*TÉTART, F. (2021): ''Grand atlas: Quel monde après le Covid-19?''. Paris, Editions Autrement. 143 pp.
}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosPrimero
|siguiente=[[The COVID-19 pandemic in Spain]]
}}

Socio-economic and environmental impact worldwide and on the European Union

2022-03-10T15:32:03Z

Usr1: Usr1 moved page Talk:Socio-economic and environmental impact worldwide and in the European Union to Socio-economic and environmental impact worldwide and on the European Union without leaving a redirect: Cambio de nombre.

{{ANEEtiqueta|palabrasclave=sección de la Monografía covid-19, sección I, pandemia, covid19, trabajo en el mundo, pobreza laboral en el mundo, horas de trabajo perdidas por COVID-19 en el mundo, PIB en el mundo, PIB en la Unión Europea, población parada en la Unión Europea, población ocupada en la Unión Europea, gases de efecto invernadero, emisiones de dióxido de carbono en el mundo, contaminación mundial en la pandemia|descripcion= Presentación cartográfica de los efectos sociales, económicos y ambientales en el mundo y en la Unión Europea|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Estructura temática (monografía COVID-19)|Estructura temática]]|seccion=[[Global context of the COVID-19 pandemic|Global context of the COVID-19 pandemic]]|capitulo=Socio-economic and environmental impact worldwide and in the European Union}}

The COVID-19 pandemic entailed a standstill to mobility and economic activities during the first half of 2020 that led to both an acute global economic recession and a short-term reduction in the environmental impact of human activities.

{{ANETextoEpigrafe|epigrafe=Socio-economic impact}}
<div><ul style="text-align: left; float:right; margin-left:0px; margin-right:0px">
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[[File:Logo Monografía.jpg|right|thumb|300px|Map: Gross Domestic Product per capita. 2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Producto-Interior-Bruto-per-capita-en-el-mundo_2020_mapa_18057_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Producto-Interior-Bruto-per-capita-en-el-mundo_2020_mapa_18057_spa.zip Datos].]]
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[[File:Logo Monografía.jpg|right|thumb|300px|Map:Variation in Gross Domestic Product in the European Union. 2019-2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-del-Producto-Interior-Bruto-en-la-Union-Europea_2019-2020_mapa_18086_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-del-Producto-Interior-Bruto-en-la-Union-Europea_2019-2020_mapa_18086_spa.zip Datos].]]
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The [[:Archivo:Mundo_Producto-Interior-Bruto-per-capita-en-el-mundo_2020_mapa_18057_spa.jpg| ''Gross Domestic Product per capita'']] map reveals the contrast between the most developed countries, located in Europe, North America and Oceania, and the least developed ones, concentrated mainly in Africa. The impact of the 2020 economic crisis was uneven, with different implications for various parts of the world. Europe and the United States experienced a sharp drop in GDP as mobility restrictions and temporary company shutdowns curbed their economic activity. In contrast, despite successfully managing to control the pandemic, China, Australia and New Zealand experienced economic downturns mainly caused by the decline in exports due to the significant decrease in international trade.

With regard to Europe, the map showing the [[:Archivo:Europa_Variacion-del-Producto-Interior-Bruto-en-la-Union-Europea_2019-2020_mapa_18086_spa.jpg|''Variation in Gross Domestic Product in the European Union'']] shows two complementary variables, i.e. the 2020 GDP per capita by State and the variation in GDP between mid-2019 and mid-2020. In terms of GDP per capita, the States with the highest incomes were those located in Scandinavia, the Benelux, Germany, France, Austria and Ireland, whilst those with the lowest incomes were in Eastern Europe, especially Romania and Bulgaria. In terms of variation, however, the States that suffered the most severe economic contractions during the first half of 2020 were those on the shores of the Mediterranean, along with Belgium, Hungary and Romania. At the other end of the scale, Ireland, Luxembourg and the Scandinavian and Baltic States were the least impacted.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Lost working hours due to COVID-19. 2019-2020. World. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Horas-de-trabajo-perdidas-por-COVID--19-en-el-mundo_2019-2020_mapa_18065_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Mundo_Horas-de-trabajo-perdidas-por-COVID--19-en-el-mundo_2019-2020_mapa_18065_spa.zip Datos]]]

The labour market is depicted by two graphs. Firstly, the graph on the [[:Archivo:Mundo_Evolucion-del-mercado-de-trabajo-en-el-mundo_2000-2020_graficoestadistico_18082_spa.jpg|''Evolution of the labour market worldwide'']] shows the evolution of global employment in the medium term, from 2000 to 2020. Only few significant variations are visible in this type of graph. However, it does show a decrease in the total number of workers and a moderate rise in unemployment during the transition from 2019 to 2020. For its part, the graph illustrating the [[:Archivo:Mundo_Distribucion-de-los-trabajadores-con-pobreza-laboral-en-el-mundo_2010-2020_graficoestadistico_18083_spa.jpg|''Global distribution of workers in poverty'']] confirms that a large part of the labour force in the least developed countries is living in poverty –particularly in Sub-Saharan Africa–, whilst moderate poverty spans throughout East Asia, South Asia and North Africa.

<div><ul style="text-align: left; float:right; margin-left:0px; margin-right:0px">
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[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Evolution of the labour market worldwide. 2000-2020. World.]]
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[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Global distribution of workers in poverty. 2010-2020. World.]]
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</ul></div>

One statistic that is clearly indicative of the pandemic’s impact on business activity is the number of lost working hours. The map depicting the number of [[:Archivo:Mundo_Horas-de-trabajo-perdidas-por-COVID--19-en-el-mundo_2019-2020_mapa_18065_spa.jpg|''Lost working hours Due to COVID-19'']] shows the heavier burden of the crisis in Andean America (from Colombia to Argentina), part of Central America, the United Kingdom, several southerly EU Member States (Spain, Italy, Greece), South Africa, Morocco, Oman, Turkey, the Caucasus, the Indian subcontinent and the Philippines. Generally speaking, these territories were also the ones most affected by the pandemic, many of which already had fragile labour markets. At the other end of the scale are some of the countries that successfully managed to contain the virus, such as China, Australia and New Zealand, some countries in Indochina, Sub-Saharan Africa, Europe (Switzerland, Norway and Belarus) and several EU Member States (the Netherlands, Denmark, Estonia, Latvia, Poland and the Czech Republic).

<div><ul style="text-align: right; float:left; margin-left:0px; margin-right:0px">
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[[File:Logo Monografía.jpg|left|thumb|300px|Map: Unemployment rates in the European Union in 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-paro-en-la-Union-Europea_2020_mapa_18102_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-paro-en-la-Union-Europea_2020_mapa_18102_spa.zip Datos].]]
</li>
<li style="display: inline-block; vertical-align: top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Employment rates in the European Union in 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-ocupacion-en-la-Union-Europea_2020_mapa_18103_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Tasa-de-ocupacion-en-la-Union-Europea_2020_mapa_18103_spa.zip Datos].]]
</li>
</ul></div>

Another analysis relevant to the study of how the crisis impacted the labour market is shown on the map depicting the [[:Archivo:Europa_Tasa-de-paro-en-la-Union-Europea_2020_mapa_18102_spa.jpg|'' Unemployment rates in the European Union in 2020'']]. Figures were clearly high for Spain, Greece and some Scandinavian and Baltic States. The Eastern States, Belgium, the Netherlands, Ireland and Portugal, however, had lower unemployment rates. Generally speaking, unemployment increased to a greater extent in States that previously had fragile labour markets and were therefore more exposed to the crisis. It is also worth mentioning that the relatively high data for Scandinavia could be linked to the fact that the these States tend to have better social protection schemes for the unemployed than the rest of the Union. Lastly, it should be noted that the temporary job protection measures succeeded in tempering the final figures for all EU Member States.

The last map related to the labour market shows the [[:Archivo:Europa_Tasa-de-ocupacion-en-la-Union-Europea_2020_mapa_18103_spa.jpg|''Employment rates in the European Union in 2020'']]. The highest employment rates were in the north and the lowest in the south. This map shows certain structural behaviours, such as the greater or lesser insertion of women in the labour market. Statistics for 2020 were heavily influenced by the furlough policies that most States introduced to counteract the pandemic’s impact on the labour market. The States with the highest employment rates were Sweden and the Netherlands, where full employment of both men and women in the context of a moderately ageing population may be pointed out. By contrast, Spain, Italy and Greece had the lowest employment figures, with high ageing and fewer women and young people in the labour market.

To summarise, the pandemic plunged humanity into a severe economic recession that was temporarily tempered by increased cash injections from the Central Banks (with the European Union and the United States leading the way), a notable rise in public spending as well as some other instruments, such as furlough policies. Nonetheless, as the world starts to overcome the worst of the crisis, each country shall address its level of indebtedness and face up to the effects the pandemic has had on employment.

{{ANETextoEpigrafe|epigrafe=Environmental impact}}
The COVID-19 pandemic had some effects on environment as well. The initial lockdowns and consequent reductions in business activity had a direct impact on air and water pollution as well as on greenhouse gas emissions in many developed countries.
Water quality in rivers and seas clearly improved due to a drastic reduction in industrial discharges. The difference was particularly remarkable in North America and Europe, where, for example, clear water in Venice’s canals could be seen. Wild animals were also quick to take advantage of the absence of humans on the streets and could be spotted roaming the avenues in some major European cities.
Energy demand fell globally by 4% and CO<sub>2</sub> emissions decreased by 5.8% in 2020, a fall the likes of which had not been seen since the Second World War. This prompted several international organisations, such as the International Energy Agency (IEA) and the World Meteorological Organisation (WMO), to revise their projections for greenhouse gas emissions during the third decade of the 21st century downwards from their pre-pandemic figures.

Unfortunately, however, if data are analysed by country or world region, there is not much cause for optimism. In China, air pollution and greenhouse gas emissions fell drastically during the first half of 2020 but began to recover before summer. In fact, figures for 2020 show in large cities, such as Beijing and Shanghai, a 5% increase in CO<sub>2</sub> emissions and polluting particles into the atmosphere compared to 2019. In the European Union and the United States, the fall in polluting emissions was very notable from March to May 2020 (between -20% and -25%), and also the remainder of the year also stayed below 2019 values.
The analysis by economic activities shows that the pollution caused by industry and energy decreased in the first half of 2020 and increased again during the second half of the year. By contrast, CO<sub>2</sub> emissions due to land and air transport also fell during the first half of 2020 but did not recover towards the end of the year.
<div><ul style="text-align: center;float:center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Variation in global CO<sub>2</sub> emissions due to the COVID-19 lockdown. 2019-2020. World.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Illustration: Forecast of global GHG emissions due to COVID-19. 2015-2030. World.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Variation in NO<sub>2</sub> concentration in Europe due to the COVID-19 Lockdown. 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-de-la-concentracion-de-NO2-debido-al-confinamiento-en-Europa_2020_mapa_18121_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Variacion-de-la-concentracion-de-NO2-debido-al-confinamiento-en-Europa_2020_mapa_18121_spa.zip Datos].]]
</li>
</ul></div>
{{ANEAutoria|Autores= Carlos Baños Castiñeira, Agustín Gámir Orueta, Rubén C. Lois González y Jorge Olcina Cantos}}
{{ANESubirArriba}}
{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanos
|anterior=[[Impact of the pandemic in the European Union]]
|siguiente=[[Población, poblamiento y comorbilidad]]
}}

[[Categoría:España en el mundo]]

Talk:Global context of the COVID-19 pandemic

2022-03-10T15:30:24Z

Usr1:

{{ANEEtiqueta|palabrasclave=sección I, pandemia, covid-19, covid19|descripcion= Análisis del contexto global de la pandemia COVID-19|url=}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANEIndiceSeccion
|color=#EFA824
|indice=
*[[Origin and global diffusion of the pandemic]]
*[[Impact of the pandemic on the European Union]]
*[[Socio-economic and environmental impact worldwide and in the European Union]]
|contenido=
Es inevitable comenzar esta monografía con una referencia suficientemente explícita al contexto planetario de la pandemia COVID-19. La Organización Mundial de
la Salud la declaró como tal una vez que certificaron casos de la enfermedad en más de cien países. La expansión amplia, simultánea y con cierta velocidad en múltiples áreas geográficas de todo el mundo obliga a presentar la globalidad de este fenómeno con el fin de acercarnos a una mejor comprensión de lo ocurrido en España.

El itinerario temático que se propone en esta primera sección se sustenta en tres ideas básicas: la constatación de que es una enfermedad que, desde su punto de ignición, se propagó por todo el mundo provocando un contagio masivo y, desgraciadamente, muchas muertes; la consideración especial que merece el marco comunitario de la Unión Europea en el que se inserta nuestro país; y, por último, el establecimiento de una primera aproximación a los efectos sociales, económicos y ambientales que ha producido globalmente la pandemia en los cinco continentes y, más en concreto, en la Unión Europea.

En el primero de los temas se presenta el origen y difusión del virus SARS-CoV-2 en China, la propagación al resto del mundo, el número de casos y fallecidos en los diferentes países y los recursos humanos, concretados en el personal sanitario, disponibles para afrontar la pandemia.

En un segundo tema se aborda el caso de la Unión Europea. En él se analizan, por un lado, algunos hechos que pudieran entenderse como condicionantes para provocar una mayor facilidad en la progresión del contagio y, consiguientemente, un mayor impacto de la emergencia sanitaria (localización de áreas con mayor densidad de población, ciudades más populosas, aeropuertos con un elevado tráfico de viajeros); por otro lado, se presenta la condición de la propia estructura demográfica en cuanto al peso de la población de más de 65 años. La muestra de dos indicadores clave de la evolución de la pandemia (los casos habidos y los fallecidos en cada país) resulta bien expresiva al respecto.

Por último, se han escogido tres indicadores clave para señalar los efectos sociales, económicos y ambientales más notables que, ya en esta primera ola, se han dejado sentir en el mundo en general y también en el marco de la Unión Europea: el nivel de población ocupada, la evolución del Producto Interior Bruto y las emisiones de NO<sub>2</sub>. La pandemia COVID-19 no solo ha tenido una incidencia sanitaria trágica, sino que impactó de manera ostensible en la actividad económica y el mercado de trabajo, por un lado, y, por otro, repercutió significativamente en el comportamiento de algunos indicadores medioambientales como consecuencia de la desaceleración del trajín económico.
}}

{{ANEAutoria|Autores=Rubén C. Lois González}}

{{ANEBibliografia|Texto=
*AGGARWAL, R.; BHATTACHARYA, S. y SINGH, S. (2020): «Mapping the Global Research and Clinical Trials in COVID-19», ''MedRXiv''. Disponible en: https://doi.org/10.1101/2020.06.27.20141788
*GUALLART MORENO, C. (2020): «La cartografía digital generada por la COVID-19: análisis y tipologías», ''Espacio, Tiempo y Forma'', serie VI-Geografía nº 13, pp. 103–134. Disponible en: https://doi.org/10.5944/etfvi.13.2020.27806
*JUERGENS, C. (2020): «Trustworthy COVID-19 Mapping: Geo-spatial Data Literacy Aspects of Choropleth Maps», ''KN Journal of Cartography and Geographic Information'', 23, pp. 1-7. Disponible en: https://doi.org/10.1007/s42489-020-00057-w
*LIU, N., et al. (2020): «Coronavirus disease 2019 (COVID-19): an evidence map of medical literatura», ''BMC Medical Research Methodology'' 20, 177. Disponible en: https://doi.org/10.1186/s12874-020-01059-y
*OSTASZEWSKI, M., et al. (2020): «COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms», ''Scientific Data'' 7, 136. Disponible en: https://doi.org/10.1038/s41597-020-0477-8
*POURGHASEMI H. R., et al. (2020): «Assessment of the outbreak risk, mapping and infection behavior of COVID-19: Application of the autoregressive integrated-moving average (ARIMA) and polynomial models», ''Plos One'' 15(7): e0236238. Disponible en: https://doi.org/10.1371/journal.pone.0236238
*SMITH C. D. y MENNIS J. (2020): «Incorporating Geographic Information Science and Technology in Response to the COVID-19 Pandemic». ''Preventing Chronic Disease'' 17: 200246. Disponible en: http://dx.doi.org/10.5888/pcd17.200246
*TÉTART, F. (2021): ''Grand atlas: Quel monde après le Covid-19?''. Paris, Editions Autrement. 143 pp.
}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosPrimero
|siguiente=[[The COVID-19 pandemic in Spain]]
}}

Impact of the pandemic on the European Union

2022-03-10T15:29:47Z

Usr1: Usr1 moved page Impact of the pandemic in the European Union to Impact of the pandemic on the European Union: Cambio de nombre.

Work in progress...

Impact of the pandemic in the European Union

2022-03-10T15:29:47Z

Usr1: Usr1 moved page Impact of the pandemic in the European Union to Impact of the pandemic on the European Union: Cambio de nombre.

#REDIRECT [[Impact of the pandemic on the European Union]]

Talk:Impact of the pandemic on the European Union

2022-03-10T15:29:47Z

Usr1: Usr1 moved page Talk:Impact of the pandemic in the European Union to Talk:Impact of the pandemic on the European Union: Cambio de nombre.

{{ANEEtiqueta|palabrasclave=sección de la Monografía covid-19, sección I, pandemia, covid19, casos de COVID-19 en la Unión Europea, personal sanitario en la Unión Europea, mortalidad por COVID-19 en la Unión Europea, estructura demográfica en Europa, aeropuertos de la Unión Europea, ciudades de Europa, dinámica demográfica en Europa|descripcion= Análisis de la afección de la pandemia en la Unión Europea a través de mapas y gráficos estadísticos del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Estructura temática (monografía COVID-19)|Estructura temática]]|seccion=[[Impact of the pandemic in the European Union|Impact of the pandemic in the European Union]]|capitulo=Impact of the pandemic in the European Union}}

The European Union is very heterogeneous from a geographical point of view. Four different geographical aspects show this complexity and warrant analysis: population density, population age, urban system and main airports. This geographical diversity becomes a key explanatory factor when studying the pandemic’s differing impact on the different States, regions and municipalities.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Population density in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.zip Datos].]]

The first map shows the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Population density in the European Union'']]. There is a sharp contrast between some very densely populated areas and other less inhabited areas. However, it shall be borne in mind that densities are conditioned by the size of the territorial units represented. At one end of the scale, some regions have a density over 500 inhabitants/km<sup>2</sup>. One of these areas is the axis that runs from the Netherlands to northern Italy, encompassing a set of highly urbanised and developed territories that also happen to be the wealthiest and most urbanised area in Europe; these are the regions that French geographer Roger Brunet named the ''Blue Banana'' at the end of the 1980s. At the other end of the scale, some regions have a density under 50 inhabitants/km<sup>2</sup>, and although they may be few in number, they occupy large territories in the north of the continent (much of Sweden, Finland and the Baltic States), in the southwest [the inland regions in Spain, Alentejo region in Portugal, and Limousin and Corsica (Corse) in France], in the southeast (various parts of Greece and Bulgaria) and in the northwest of Ireland. A priori, it seems reasonable to set a direct relationship between high population density and the ease at which any infectious disease may spread. And the most densely populated areas of the Union did, indeed, record a high number of COVID-19 cases. However, within the most populated regions, the different speed with which the decision on lockdowns was taken led to the effects of the pandemic being more severe in some regions [e.g. Lombardy (Lombardia), Île de France…] than in others [e.g. Baden-Württemberg, Bavaria (Bayern)…].

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Population over the age of 65 in the European Union. 2019. Europe.[//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.zip Datos]. ]]
The population density map shall be combined with the [[Archivo:Europa_Poblacion-mayor-de-65-anos-en-la-Union-Europea_2019_mapa_17830_spa.jpg|''Population over the age of 65 in the European Union'']] map, which shows a part of the population that, if infected, has a higher morbidity rate due to the age. This map is clearly different to the population density map. The regions that stand out for having a higher number of people over the age of 65 are those that form the Iberian Atlantic Arc [especially Alentejo, Galicia, Asturias and Castile and León (Castilla y León)], the hinterland of France (especially Poitou-Charentes and Limousin), the north of Italy [more specifically Piedmont (Piemonte), Liguria, Friuli-Venezia-Giulia, Tuscany (Toscana) and Umbria], several regions in eastern Germany [Saxony (Sachsen), Saxony-Anhalt (Sachsen-Anhalt) and Thuringia (Thüringen)], a couple in Greece [Epirus (Épeiros) and the Ionian Islands (Iónia nisiá)] and one in Bulgaria (Northwest). In the case of the Iberian regions, older sex-age pyramids are combined with low demographic densities and a highly dispersed population, making the provision of healthcare for older adults even more challenging.

[[File:Logo Monografía.jpg|left|thumb|300px|Map: Most populous cities in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Ciudades-mas-pobladas-de-la-Union-Europea_2019_mapa_18141_spa.zip Datos].]]
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Main airports in the European Union. 2019. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.zip Datos].]]]
If we look at the map showing the [[:Archivo:Europa_Densidad-de-poblacion-en-la-Union-Europea_2019_mapa_18193_spa.jpg|''Most populous cities in the European Union'']], we may observe that the high rates of urbanisation in Europe translate to a network of numerous medium-sized (by global standards) cities in close proximity to one another. This urban pattern is totally different to the megacities in Asia, Africa, and the Americas. It is particularly prominent in the aforementioned Blue Banana, where several cities with over half a million inhabitants are located just a short distance from one another and are included in different Member States. The density of flows between these cities played a significant role in easing the spread of the virus across the continent, which led to the roll-out of coordinated measures throughout the twenty-seven EU States. However, unlike
in other continents, the size and morphology of the European urban system allowed the Authorities to quarantine the cities and neighbourhoods with the highest incidence of infection with relative ease, and this helped to control the pandemic in the heart of Europe.

The map showing the [[:Archivo:Europa_Principales-aeropuertos-de-la-Union-Europea_2019_mapa_17850_spa.jpg|''Main airports in the European Union'']] tries to highlight the virus’ points of access to the Union from abroad, i.e. the international airports where measures were gradually introduced to slow down the arrival of passengers, first from Asia, then from South Africa, Brazil and the United Kingdom. It also shows the other airports in the network, which subsequently helped to spread the pandemic internally. Air transport flows in the European Union have two main components: business travel and leisure travel. Travel for work-related reasons is more common in the airports located in the main urban areas. Falls in the number of passengers at these airports as a result of lockdowns and reduced mobility were considerable. Frankfurt airport went from 70 million passengers in 2019 to 19 million in 2020; Madrid from 60 million in 2019 to 17 million in 2020; and Munich (München) from 48 million in 2019 to 11 million in 2020. By contrast, airports on the Mediterranean coast and the Canary Islands (islas Canarias) rely heavily on tourism. However, given that the outbreak of the virus happened in winter, during months of low tourist activity, these airports were less impacted by restrictions on mobility during the initial weeks of the pandemic. In June 2020, when the incidence of the virus had been reduced, lockdown measures were scaled-back and the summer tourist season began, some regional administrations in these areas –particularly the island regions– ventured to test tourist corridors, in which virus control systems at airports played a crucial role.

[[File:Logo Monografía.jpg|right|thumb|300px|Statistical graph: Evolución de casos COVID-19 en la Unión Europea. 2020. Europa.]]

[[File:Logo Monografía.jpg|right|thumb|300px|Map: Casos de COVID-19 en la Unión Europea. 2020. Europa. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.zip Datos].]]]
Having analysed the four geographical aspects that show the internal heterogeneity of the European Union and played a decisive role in the way the COVID-19 pandemic impacted the different territories to varying degrees, the statistics have been synthesised on the maps and graphs included on the next page to show the impact of the pandemic across the European Union.

The map showing the [[:Archivo:Europa_Casos-de-COVID--19-en-la-Union-Europea_2020_mapa_17792_spa.jpg|''COVID-19 cases in the European Union'']] reveals how the pandemic spread throughout the territory from January to June 2020. The growth of the disease was explosive during the month of March and the worst figures were registered in April. This may possibly be related to the fact that the European Union had underestimated the risk of a new virus emerging in China, so by the time the pandemic was declared, European health and governance systems were overwhelmed. However, the decision to impose a policy of strict lockdowns in the vast majority of Member States gradually succeeded in reducing the number of infections afterwards. An analysis of the impact by State shows that the severity of the pandemic was uneven: the eastern States were less affected (Slovakia and Hungary recorded the lowest figures); western States that reacted quickly were able to limit the impact (e.g. Portugal, Germany and France); other western States recorded the highest figures (Spain, Ireland, Belgium and Sweden had the highest incidence rates).

The map showing the [[:Archivo:Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.jpg|''Deaths from COVID-19 in the European Union'']] reveals a general trend that correlates with the patterns for COVID-19 cases. However, the number of deaths lags behind the number of cases by a couple of weeks. The only significant variation is to be found in Italy, which was the first State to register a community transmission. They reacted quickly and, therefore, managed to limit the transmission figures somewhat. Nevertheless, Italy recorded very high death rates. This is because there were few means to combat the disease during the first weeks of the pandemic, which meant the number of seriously ill and deceased was particularly high at this early stage (at one point, the mortality rate in Italy lied over 50 per 100,000 inhabitants).

The last map shows the number of [[:Archivo:Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.jpg|''Healthcare workers in the European Union'']]. In general, Europe is globally renowned for having solid and well-equipped healthcare systems, which translate to the continent’s high level of well-being. However, the availability of doctors and nurses is uneven: higher in the northern States (Finland, Sweden, Ireland, Germany, Belgium, Estonia and Lithuania), and lower in the southern and eastern States (for this indicator, Spain and Italy have similar figures to Bulgaria, possibly as a result of the cuts on their health budgets in the wake of the double recession from 2008-2013).

<div><ul style="text-align: center">
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Statistical graph: Evolution in the number of deaths from COVID-19 in the European Union. 2020. Europe.]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Deaths from COVID-19 in the European Union. 2020. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Fallecidos-por-COVID--19-en-la-Union-Europea_2020_mapa_17793_spa.zip Datos].]]]
</li>
<li style="display: inline-block; vertical-align:top">
[[File:Logo Monografía.jpg|left|thumb|300px|Map: Healthcare workers in the European Union. 2018. Europe. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Europa_Personal-sanitario-en-la-Union-Europea_2018_mapa_17875_spa.zip Datos].]]]
</li>
</ul></div>

{{ANEAutoria|Autores= Agustín Gámir Orueta, Rubén C. Lois González, Ángel Miramontes Carballada y Ana Paula Santana Rodrigues}}
{{ANESubirArriba}}
{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanos
|anterior=[[Origin and global diffusion of the pandemic]]
|siguiente=[[Socio-economic and environmental impact worldwide and in the European Union]]
}}

[[Category:Spain in the World]]

Talk:Impact of the pandemic in the European Union

2022-03-10T15:29:47Z

Usr1: Usr1 moved page Talk:Impact of the pandemic in the European Union to Talk:Impact of the pandemic on the European Union: Cambio de nombre.

#REDIRECT [[Talk:Impact of the pandemic on the European Union]]

Talk:Social, economic and environmental effects

2022-03-10T12:02:35Z

Usr1:

{{ANEEtiqueta

|palabrasclave=sección III, pandemia, covid-19, covid19

|descripcion=Efectos sociales, económicos y ambientales

|url=

}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[File:Logo_Monografía.jpg|left|50x50px|link=]]|Título=La pandemia COVID-19 en España|Subtítulo=Primera ola: de los primeros casos a finales de junio de 2020|Año=2021|Contenido=Nuevo contenido}}
{{ANEIndiceSeccion
|color=#A25652
|indice=
*[[Internal territorial governance|Internal territorial governance]]
*[[Movilidad]]
**[[Transporte por carretera (monografía COVID-19)|Transporte por carretera]]
**[[Transporte por ferrocarril (monografía COVID-19)|Transporte por ferrocarril]]
**[[Transporte urbano (monografía COVID-19)|Transporte urbano]]
**[[Transporte aéreo (monografía COVID-19)|Transporte aéreo]]
**[[Transporte marítimo (monografía COVID-19)|Transporte marítimo]]
**[[Movilidad detectada a través de la telefonía|Movilidad detectada a través de la telefonía]]
*[[Magnitudes macroeconómicas y sectores productivos]]
**[[Magnitudes macroeconómicas (monografía COVID-19)|Magnitudes macroeconómicas]]
**[[Agricultura y pesca|Agricultura y pesca]]
**[[Minería, energía, industria y construcción (monografía COVID-19)|Minería, energía, industria y construcción]]
**[[Servicios no turísticos|Servicios no turísticos]]
**[[Turismo (monografía COVID-19)|Turismo]]
*[[Trabajo (monografía COVID-19)|Trabajo]]
*[[Public Finance]]
*[[Educación (monografía COVID-19)|Educación]]
*[[Solidarity initiatives]]
*[[Repercusiones ambientales|Repercusiones ambientales]]
|contenido=
Los efectos de una pandemia como la sufrida por razón de la COVID-19 son difíciles de precisar, tanto a nivel planetario o global, como en cada uno de los países. Entre las repercusiones las hay tangibles e intangibles, a corto o largo plazo, personales o comunitarias, locales o nacionales e internacionales.

Sería un propósito inalcanzable medir con precisión, a todos los niveles y en los diferentes campos, el impacto producido por un fenómeno tan inesperado como severo. Tómese, por tanto, el contenido de esta sección como una propuesta que constata la incidencia de la pandemia COVID-19 en España en algunos aspectos que, al margen de los sanitarios, se han considerado más significativos.

Se han buscado aquellas facetas que cuentan con información cuantitativa y actualizada que nos permitan acercarnos a una representación lo más objetiva posible de lo acontecido. Los recursos gráficos y cartográficos, bien sostenidos por un soporte largamente pensado, no agotan las posibilidades de conformar una imagen acabada que hiciera posible percibir la totalidad de los efectos producidos. Son, tan solo, una manifestación de cariz epidérmico que esconde un fondo que quizás nunca se podrá desvelar.

El hilo argumental que sostiene la exposición de contenidos recorre un hipotético camino desde la respuesta a la pandemia que ha dado la gobernanza territorial hasta la incidencia producida en el entorno medioambiental. En medio se considera el brusco cambio operado en la movilidad de personas y mercancías, el impacto producido en las magnitudes macroeconómicas y sectores productivos, las transformaciones en el funcionamiento y estructura del mercado de trabajo, la influencia en la recaudación por parte de la hacienda pública, el embate sufrido por el sistema educativo por razón del confinamiento domiciliario y, por último, la movilización institucional y social que desencadenó un auténtico alud de acciones solidarias.

Puede que, de fijarnos tan solo en los temas citados, se nos escape la verdadera entidad del hecho vivido. Un virus, ente extremadamente insignificante por su tamaño, ha sido capaz de paralizar el mundo. Seguramente acertó Italo Calvino cuando, antes de morir en 1985, vaticinó que la levedad –lo que pesa poco y es diminuto– iba a ser uno de los valores imperantes en el tercer milenio; en el tema tratado en esta monografía, parece corroborarse aquella afirmación, hecha por el autor citado en relación a creatividad literaria, pues se ha constatado que algo tan diminuto ha provocado impactos de impensable calado.

El enorme problema vivido arrancó de algo extremadamente pequeño, desatando efectos inesperados por su envergadura: enfermedad, muerte, crisis social y económica. Puede que también vaya a incidir en un deseable cambio de paradigma de nuestra relación con el entorno, haciéndola más justa y sostenible. En todo caso, la comunidad humana ha demostrado, una vez más, su capacidad de reacción al procurar los auxilios sanitarios pertinentes para vencer a la pandemia en un tiempo muy corto y retomar con renovada energía el camino de la recuperación social y económica.
}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosUltimo
|anterior=[[La pandemia COVID-19 en España]]
}}

Solidarity initiatives

2022-03-10T10:25:00Z

Usr1: Created page with "Page under construction"

Page under construction

Talk:Social, economic and environmental effects

2022-03-10T10:24:29Z

Usr1:

{{ANEEtiqueta

|palabrasclave=sección III, pandemia, covid-19, covid19

|descripcion=Efectos sociales, económicos y ambientales

|url=

}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[File:Logo_Monografía.jpg|left|50x50px|link=]]|Título=La pandemia COVID-19 en España|Subtítulo=Primera ola: de los primeros casos a finales de junio de 2020|Año=2021|Contenido=Nuevo contenido}}
{{ANEIndiceSeccion
|color=#A25652
|indice=
*[[Internal territorial governance|Internal territorial governance]]
*[[Movilidad]]
**[[Transporte por carretera (monografía COVID-19)|Transporte por carretera]]
**[[Transporte por ferrocarril (monografía COVID-19)|Transporte por ferrocarril]]
**[[Transporte urbano (monografía COVID-19)|Transporte urbano]]
**[[Transporte aéreo (monografía COVID-19)|Transporte aéreo]]
**[[Transporte marítimo (monografía COVID-19)|Transporte marítimo]]
**[[Movilidad detectada a través de la telefonía|Movilidad detectada a través de la telefonía]]
*[[Magnitudes macroeconómicas y sectores productivos]]
**[[Magnitudes macroeconómicas (monografía COVID-19)|Magnitudes macroeconómicas]]
**[[Agricultura y pesca|Agricultura y pesca]]
**[[Minería, energía, industria y construcción (monografía COVID-19)|Minería, energía, industria y construcción]]
**[[Servicios no turísticos|Servicios no turísticos]]
**[[Turismo (monografía COVID-19)|Turismo]]
*[[Trabajo (monografía COVID-19)|Trabajo]]
*[[Hacienda pública (monografía COVID-19)|Hacienda pública]]
*[[Educación (monografía COVID-19)|Educación]]
*[[Solidarity initiatives]]
*[[Repercusiones ambientales|Repercusiones ambientales]]
|contenido=
Los efectos de una pandemia como la sufrida por razón de la COVID-19 son difíciles de precisar, tanto a nivel planetario o global, como en cada uno de los países. Entre las repercusiones las hay tangibles e intangibles, a corto o largo plazo, personales o comunitarias, locales o nacionales e internacionales.

Sería un propósito inalcanzable medir con precisión, a todos los niveles y en los diferentes campos, el impacto producido por un fenómeno tan inesperado como severo. Tómese, por tanto, el contenido de esta sección como una propuesta que constata la incidencia de la pandemia COVID-19 en España en algunos aspectos que, al margen de los sanitarios, se han considerado más significativos.

Se han buscado aquellas facetas que cuentan con información cuantitativa y actualizada que nos permitan acercarnos a una representación lo más objetiva posible de lo acontecido. Los recursos gráficos y cartográficos, bien sostenidos por un soporte largamente pensado, no agotan las posibilidades de conformar una imagen acabada que hiciera posible percibir la totalidad de los efectos producidos. Son, tan solo, una manifestación de cariz epidérmico que esconde un fondo que quizás nunca se podrá desvelar.

El hilo argumental que sostiene la exposición de contenidos recorre un hipotético camino desde la respuesta a la pandemia que ha dado la gobernanza territorial hasta la incidencia producida en el entorno medioambiental. En medio se considera el brusco cambio operado en la movilidad de personas y mercancías, el impacto producido en las magnitudes macroeconómicas y sectores productivos, las transformaciones en el funcionamiento y estructura del mercado de trabajo, la influencia en la recaudación por parte de la hacienda pública, el embate sufrido por el sistema educativo por razón del confinamiento domiciliario y, por último, la movilización institucional y social que desencadenó un auténtico alud de acciones solidarias.

Puede que, de fijarnos tan solo en los temas citados, se nos escape la verdadera entidad del hecho vivido. Un virus, ente extremadamente insignificante por su tamaño, ha sido capaz de paralizar el mundo. Seguramente acertó Italo Calvino cuando, antes de morir en 1985, vaticinó que la levedad –lo que pesa poco y es diminuto– iba a ser uno de los valores imperantes en el tercer milenio; en el tema tratado en esta monografía, parece corroborarse aquella afirmación, hecha por el autor citado en relación a creatividad literaria, pues se ha constatado que algo tan diminuto ha provocado impactos de impensable calado.

El enorme problema vivido arrancó de algo extremadamente pequeño, desatando efectos inesperados por su envergadura: enfermedad, muerte, crisis social y económica. Puede que también vaya a incidir en un deseable cambio de paradigma de nuestra relación con el entorno, haciéndola más justa y sostenible. En todo caso, la comunidad humana ha demostrado, una vez más, su capacidad de reacción al procurar los auxilios sanitarios pertinentes para vencer a la pandemia en un tiempo muy corto y retomar con renovada energía el camino de la recuperación social y económica.
}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosUltimo
|anterior=[[La pandemia COVID-19 en España]]
}}

Talk:Different spatial behaviours

2022-03-09T11:18:38Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, COVID-19, población absoluta, casos de COVID-19, focos de contagio por COVID-19, tasa de frecuentación de COVID-19, riesgo de contagio por COVID-19, vulnerabilidad al contagio por COVID-19, vulnerabilidad social|descripcion=Análisis de los comportamientos espaciales diferenciados a través de mapas y tablas del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Thematic structure]]|seccion=[[The COVID-19 pandemic in Spain]]|capitulo=Different spatial behaviours}}{{ANEIndiceCapitulo|colorcaja=#628D93
|indice=
*[[Galicia]]
*[[Saragossa (Zaragoza)]]
*[[Barcelona and its metropolitan area]]
*[[City and Region of Madrid]]
*[[Málaga]]
*[[Synthetic vulnerability index in Barcelona and Madrid]]
}}<br>
<li style="display: inline-block">
<div style="text-align:right"><div style="color:MediumBlue"><div style="padding-top: 0em; padding-right: 3em; padding-bottom: 0em; padding-left: 0em>'''HABITANTES A 1 DE ENERO DE 2020'''</div>
{| cellspacing="0" cellpadding="0" style="margin-top: 0; float:right; margin-right: 0px; margin-bottom: 0em; margin-left: 10px"
| style="vertical-align: top; border-style: solid; border-width: 1px; border-color: #A7A7A7; background-color:#ffffff" |
<div style="padding-top: 0.1em; padding-right: 0.5em; padding-bottom: 0.3em; padding-left: 0.5em; font-size: 100%; text-align: center; float:right">
{| style="float:right; margin-right: 10px; margin-bottom: 0em; margin-left:10px"

|-
! colspan="2" style="color:MediumBlue; background:LightGoldenrodYellow; text-align:center; border: solid; border-width: 1px" | MUNICIPIOS
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | A Coruña||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px; width:100px"|247.640
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Vigo|| style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |296.629
|-
| style="background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Ourense|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|105.643
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" |Santiago de Compostela||style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |97.848
|-
| style="background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Zaragoza|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|681.877
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Barcelona || style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |1.664.182
|-
| style="background:White; text-align:left;color:#000000; border: solid; border-width: 1px; width:200px" | Madrid||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|3.334.730
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:150px" |Málaga || style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |578.460
|-
! colspan="2" style="color:MediumBlue;background:LightGoldenrodYellow; text-align:center; border: solid; border-width: 1px" | ÁMBITO SUPRAMUNICIPAL
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Galicia||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|2.701.819
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Área Metropolitana de Barcelona||style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |3.339.279
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Comunidad de Madrid|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"| 6.779.888
|-
| colspan=2; style="background:white; text-align:left" | <div style="padding-top: 0em; padding-right: 0.5em; padding-bottom: 0em; padding-left: 0.5em; style="background:White; font-size: 95%"><small style="color:#959595">Fuente: Estadística del Padrón continuo 2020. INE. Se relacionan las ciudades y ámbitos supramunicipales que se analizan en los ejemplos contenidos en este tema. Figuran en el orden en el que aparecen en la publicación</small></div>
|}
|}
</div>
</div>

<div style="text-align:left">
Durante la llamada primera ola de la pandemia COVID-19 en España el impacto sanitario ha sido muy dispar espacialmente. En los temas precedentes, la unidad de análisis y representación de esta diversidad ha sido mayoritariamente la provincia, un territorio extenso que encierra en su seno una condición física y humana a veces muy contrastada.

En este tema de la monografía se desciende a una escala de mayor detalle, la metropolitana o municipal, e incluso dentro de esta se llega, en algunos casos, a unidades inferiores como los distritos municipales, barrios o secciones censales. Esta aproximación permite afinar algunas hipótesis de trabajo con suficiente fundamento a la hora de buscar relaciones entre determinadas variables temáticas y el comportamiento espacial de la pandemia, aunque, en esta nueva aproximación, no cabe esperar conclusiones definitivas al respecto.

Una primera idea que parece desprenderse de la lectura de los mapas y gráficos que se incluyen en este tema es la decisiva importancia del factor humano en la incidencia mayor o menor de los efectos sanitarios de la pandemia en el seno de las ciudades y áreas metropolitanas. La movilidad de la población, la renta familiar disponible, el nivel de paro laboral, el peso del grupo de personas por debajo del umbral de la pobreza, el tipo de hábitat o la ubicación espacial de las residencias de población mayor son, entre otras, condiciones a tener en cuenta para calibrar mejor el impacto sanitario producido.

Un paso más se da en los ejemplos propuestos cuando se abordan índices de cariz integrador y señalan la peligrosidad, el riesgo o la vulnerabilidad en el seno del espacio urbano o metropolitano, sirviéndose para ello de unidades de análisis y representación espacial de mayor detalle como en algún caso son las secciones censales.

[[File:Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.jpg|left|thumb|300px|Mapa: Localización de comportamientos espaciales diferenciados. 2020. España. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.zip Datos].]]
Los ejemplos presentados son cinco como se puede ver en el mapa de ''[[:File:Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.jpg|Localización de las áreas estudiadas]]'': Galicia, la ciudad de Zaragoza, Barcelona y su área metropolitana, la Comunidad de Madrid y la propia ciudad y, por último, Málaga. En los casos de las ciudades de Zaragoza y Málaga, la cartografía se ciñe al entorno municipal; en Galicia, se parte de una visión de conjunto de la comunidad autónoma para descender después a las ciudades de A Coruña, Ourense, Santiago de Compostela y Vigo, en las que se refleja la dispersión de los focos de contagio, presumiblemente ligada esa dispersión a la propia estructura del hábitat gallego y ubicación de residencias de mayores en las afueras de las ciudades.

En el caso de Barcelona y su entorno, se toma una doble perspectiva que va desde el contexto metropolitano, al propiamente municipal de la ciudad con sus distritos y barrios. En el ejemplo de Madrid, también se presta atención a una doble aproximación: la estrictamente municipal con sus distritos y la del territorio autónomo como marco más general.

En los casos de las ciudades de Barcelona y Madrid, se ha elaborado un índice sintético de vulnerabilidad social, teniendo como unidad espacial de análisis a la sección censal. Se estima que ello puede contribuir a una mejor comprensión de la afección diferenciada de la pandemia en el territorio y en la comunidad humana que lo habita.
</div>

{{ANETextoDestacado|titulo=IDEAS CLAVE CONTENIDAS EN LOS EJEMPLOS PRESENTADOS EN ESTE TEMA|contenido=
1. La estructura del poblamiento ha podido influir en el grado de afección de la pandemia al ser un elemento de contención del virus, cuando aquella muestra mayor dispersión social y, en definitiva, una menor intensidad del contacto físico.

2. No resulta arriesgado manifestar, aunque sea como hipótesis dotada con suficiente fundamento, que la pobreza y precariedad social han podido provocar en la primera ola de la pandemia, así como en las posteriores, más contagios y víctimas entre los más vulnerables.

3. La distinta capacidad de reducir la movilidad que hace uso básicamente de los medios públicos de transporte dentro del espacio urbano, ligada al tipo de trabajo desempeñado por determinados grupos sociales y a su condición económica más precaria, puede ser uno de los factores o condicionantes que parece han incidido en una afección de la pandemia más acusada.

4. El factor densidad demográfica en un entorno urbano tuvo, en la primera ola de la pandemia, una clara relación con la distribución del número de afectados, aunque no fue el único. Más bien, hay que acudir a un modelo multifactorial más complejo para tratar de encontrar una explicación satisfactoria.

5. A tenor de la respuesta ciudadana a una encuesta sobre la situación anímica de la población durante el confinamiento domiciliario en la gran ciudad, se ha detectado que, en determinados sectores urbanos con un grado de vulnerabilidad social alto, el número de respuestas de cariz positivo frente a la situación anímica vivida ha sido significativamente elevado lo que indica una alta capacidad de resiliencia en los mismos.

6. Otra hipótesis que parece vislumbrarse y reclama la atención de los especialistas es el diferente comportamiento de la pandemia según sexos. Los datos apuntan a un mayor impacto en los varones en cuanto a los hospitalizados, ingresados en UCI y fallecidos, a pesar de diagnosticarse como positivas un mayor número de mujeres. Este hecho parece evidenciar una mayor gravedad de los síntomas y repercusiones de la enfermedad en los hombres.}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}
<div style="text-align:left">
{{ANEPaginaDescargas (monografía COVID-19)}}
</div>

{{ANENavegacionHermanos

|anterior=[[Overview]]

|siguiente=[[Internal territorial governance]]
}}

[[Categoría:Servicios y equipamientos sociales]]
[[Categoría:Población, poblamiento y sociedad]]

Talk:Different spatial behaviours

2022-03-09T11:18:12Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, COVID-19, población absoluta, casos de COVID-19, focos de contagio por COVID-19, tasa de frecuentación de COVID-19, riesgo de contagio por COVID-19, vulnerabilidad al contagio por COVID-19, vulnerabilidad social|descripcion=Análisis de los comportamientos espaciales diferenciados a través de mapas y tablas del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Thematic structure]]|seccion=[[The COVID-19 pandemic in Spain]]|capitulo=Different spatial behaviours}}{{ANEIndiceCapitulo|colorcaja=#628D93
|indice=
*[[Galicia]]
*[[Saragossa (Zaragoza)]]
*[[Barcelona and its metropolitan area]]
*[[City and Region of Madrid]]
*[[Málaga]]
*[[Synthetic vulnerability index in Barcelona and Madrid]]
}}<br>
<li style="display: inline-block">
<div style="text-align:right"><div style="color:MediumBlue"><div style="padding-top: 0em; padding-right: 3em; padding-bottom: 0em; padding-left: 0em>'''HABITANTES A 1 DE ENERO DE 2020'''</div>
{| cellspacing="0" cellpadding="0" style="margin-top: 0; float:right; margin-right: 0px; margin-bottom: 0em; margin-left: 10px"
| style="vertical-align: top; border-style: solid; border-width: 1px; border-color: #A7A7A7; background-color:#ffffff" |
<div style="padding-top: 0.1em; padding-right: 0.5em; padding-bottom: 0.3em; padding-left: 0.5em; font-size: 100%; text-align: center; float:right">
{| style="float:right; margin-right: 10px; margin-bottom: 0em; margin-left:10px"

|-
! colspan="2" style="color:MediumBlue; background:LightGoldenrodYellow; text-align:center; border: solid; border-width: 1px" | MUNICIPIOS
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | A Coruña||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px; width:100px"|247.640
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Vigo|| style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |296.629
|-
| style="background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Ourense|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|105.643
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" |Santiago de Compostela||style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |97.848
|-
| style="background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Zaragoza|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|681.877
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Barcelona || style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |1.664.182
|-
| style="background:White; text-align:left;color:#000000; border: solid; border-width: 1px; width:200px" | Madrid||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|3.334.730
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:150px" |Málaga || style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |578.460
|-
! colspan="2" style="color:MediumBlue;background:LightGoldenrodYellow; text-align:center; border: solid; border-width: 1px" | ÁMBITO SUPRAMUNICIPAL
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Galicia||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|2.701.819
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Área Metropolitana de Barcelona||style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |3.339.279
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Comunidad de Madrid|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"| 6.779.888
|-
| colspan=2; style="background:white; text-align:left" | <div style="padding-top: 0em; padding-right: 0.5em; padding-bottom: 0em; padding-left: 0.5em; style="background:White; font-size: 95%"><small style="color:#959595">Fuente: Estadística del Padrón continuo 2020. INE. Se relacionan las ciudades y ámbitos supramunicipales que se analizan en los ejemplos contenidos en este tema. Figuran en el orden en el que aparecen en la publicación</small></div>
|}
|}
</div>
</div>

<div style="text-align:left">
Durante la llamada primera ola de la pandemia COVID-19 en España el impacto sanitario ha sido muy dispar espacialmente. En los temas precedentes, la unidad de análisis y representación de esta diversidad ha sido mayoritariamente la provincia, un territorio extenso que encierra en su seno una condición física y humana a veces muy contrastada.

En este tema de la monografía se desciende a una escala de mayor detalle, la metropolitana o municipal, e incluso dentro de esta se llega, en algunos casos, a unidades inferiores como los distritos municipales, barrios o secciones censales. Esta aproximación permite afinar algunas hipótesis de trabajo con suficiente fundamento a la hora de buscar relaciones entre determinadas variables temáticas y el comportamiento espacial de la pandemia, aunque, en esta nueva aproximación, no cabe esperar conclusiones definitivas al respecto.

Una primera idea que parece desprenderse de la lectura de los mapas y gráficos que se incluyen en este tema es la decisiva importancia del factor humano en la incidencia mayor o menor de los efectos sanitarios de la pandemia en el seno de las ciudades y áreas metropolitanas. La movilidad de la población, la renta familiar disponible, el nivel de paro laboral, el peso del grupo de personas por debajo del umbral de la pobreza, el tipo de hábitat o la ubicación espacial de las residencias de población mayor son, entre otras, condiciones a tener en cuenta para calibrar mejor el impacto sanitario producido.

Un paso más se da en los ejemplos propuestos cuando se abordan índices de cariz integrador y señalan la peligrosidad, el riesgo o la vulnerabilidad en el seno del espacio urbano o metropolitano, sirviéndose para ello de unidades de análisis y representación espacial de mayor detalle como en algún caso son las secciones censales.

[[Archivo:Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.jpg|left|thumb|300px|Mapa: Localización de comportamientos espaciales diferenciados. 2020. España. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.zip Datos].]]
Los ejemplos presentados son cinco como se puede ver en el mapa de ''[[:Archivo:Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.jpg|Localización de las áreas estudiadas]]'': Galicia, la ciudad de Zaragoza, Barcelona y su área metropolitana, la Comunidad de Madrid y la propia ciudad y, por último, Málaga. En los casos de las ciudades de Zaragoza y Málaga, la cartografía se ciñe al entorno municipal; en Galicia, se parte de una visión de conjunto de la comunidad autónoma para descender después a las ciudades de A Coruña, Ourense, Santiago de Compostela y Vigo, en las que se refleja la dispersión de los focos de contagio, presumiblemente ligada esa dispersión a la propia estructura del hábitat gallego y ubicación de residencias de mayores en las afueras de las ciudades.

En el caso de Barcelona y su entorno, se toma una doble perspectiva que va desde el contexto metropolitano, al propiamente municipal de la ciudad con sus distritos y barrios. En el ejemplo de Madrid, también se presta atención a una doble aproximación: la estrictamente municipal con sus distritos y la del territorio autónomo como marco más general.

En los casos de las ciudades de Barcelona y Madrid, se ha elaborado un índice sintético de vulnerabilidad social, teniendo como unidad espacial de análisis a la sección censal. Se estima que ello puede contribuir a una mejor comprensión de la afección diferenciada de la pandemia en el territorio y en la comunidad humana que lo habita.
</div>

{{ANETextoDestacado|titulo=IDEAS CLAVE CONTENIDAS EN LOS EJEMPLOS PRESENTADOS EN ESTE TEMA|contenido=
1. La estructura del poblamiento ha podido influir en el grado de afección de la pandemia al ser un elemento de contención del virus, cuando aquella muestra mayor dispersión social y, en definitiva, una menor intensidad del contacto físico.

2. No resulta arriesgado manifestar, aunque sea como hipótesis dotada con suficiente fundamento, que la pobreza y precariedad social han podido provocar en la primera ola de la pandemia, así como en las posteriores, más contagios y víctimas entre los más vulnerables.

3. La distinta capacidad de reducir la movilidad que hace uso básicamente de los medios públicos de transporte dentro del espacio urbano, ligada al tipo de trabajo desempeñado por determinados grupos sociales y a su condición económica más precaria, puede ser uno de los factores o condicionantes que parece han incidido en una afección de la pandemia más acusada.

4. El factor densidad demográfica en un entorno urbano tuvo, en la primera ola de la pandemia, una clara relación con la distribución del número de afectados, aunque no fue el único. Más bien, hay que acudir a un modelo multifactorial más complejo para tratar de encontrar una explicación satisfactoria.

5. A tenor de la respuesta ciudadana a una encuesta sobre la situación anímica de la población durante el confinamiento domiciliario en la gran ciudad, se ha detectado que, en determinados sectores urbanos con un grado de vulnerabilidad social alto, el número de respuestas de cariz positivo frente a la situación anímica vivida ha sido significativamente elevado lo que indica una alta capacidad de resiliencia en los mismos.

6. Otra hipótesis que parece vislumbrarse y reclama la atención de los especialistas es el diferente comportamiento de la pandemia según sexos. Los datos apuntan a un mayor impacto en los varones en cuanto a los hospitalizados, ingresados en UCI y fallecidos, a pesar de diagnosticarse como positivas un mayor número de mujeres. Este hecho parece evidenciar una mayor gravedad de los síntomas y repercusiones de la enfermedad en los hombres.}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}
<div style="text-align:left">
{{ANEPaginaDescargas (monografía COVID-19)}}
</div>

{{ANENavegacionHermanos

|anterior=[[Overview]]

|siguiente=[[Internal territorial governance]]
}}

[[Categoría:Servicios y equipamientos sociales]]
[[Categoría:Población, poblamiento y sociedad]]

Talk:Different spatial behaviours

2022-03-09T11:17:46Z

Usr1: Created page with "{{ANEEtiqueta|palabrasclave=pandemia, covid19, COVID-19, población absoluta, casos de COVID-19, focos de contagio por COVID-19, tasa de frecuentación de COVID-19, riesgo de..."

{{ANEEtiqueta|palabrasclave=pandemia, covid19, COVID-19, población absoluta, casos de COVID-19, focos de contagio por COVID-19, tasa de frecuentación de COVID-19, riesgo de contagio por COVID-19, vulnerabilidad al contagio por COVID-19, vulnerabilidad social|descripcion=Análisis de los comportamientos espaciales diferenciados a través de mapas y tablas del Atlas Nacional de España|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura=[[Thematic structure]]|seccion=[[The COVID-19 pandemic in Spain]]|capitulo=Different spatial behaviours}}{{ANEIndiceCapitulo|colorcaja=#628D93
|indice=
*[[Galicia]]
*[[Saragossa (Zaragoza)]]
*[[Barcelona and its metropolitan area]]
*[[City and Region of Madrid]]
*[[Málaga]]
*[[Synthetic vulnerability index in Barcelona and Madrid]]
}}<br>
<li style="display: inline-block">
<div style="text-align:right"><div style="color:MediumBlue"><div style="padding-top: 0em; padding-right: 3em; padding-bottom: 0em; padding-left: 0em>'''HABITANTES A 1 DE ENERO DE 2020'''</div>
{| cellspacing="0" cellpadding="0" style="margin-top: 0; float:right; margin-right: 0px; margin-bottom: 0em; margin-left: 10px"
| style="vertical-align: top; border-style: solid; border-width: 1px; border-color: #A7A7A7; background-color:#ffffff" |
<div style="padding-top: 0.1em; padding-right: 0.5em; padding-bottom: 0.3em; padding-left: 0.5em; font-size: 100%; text-align: center; float:right">
{| style="float:right; margin-right: 10px; margin-bottom: 0em; margin-left:10px"

|-
! colspan="2" style="color:MediumBlue; background:LightGoldenrodYellow; text-align:center; border: solid; border-width: 1px" | MUNICIPIOS
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | A Coruña||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px; width:100px"|247.640
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Vigo|| style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |296.629
|-
| style="background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Ourense|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|105.643
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" |Santiago de Compostela||style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |97.848
|-
| style="background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Zaragoza|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|681.877
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Barcelona || style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |1.664.182
|-
| style="background:White; text-align:left;color:#000000; border: solid; border-width: 1px; width:200px" | Madrid||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|3.334.730
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:150px" |Málaga || style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |578.460
|-
! colspan="2" style="color:MediumBlue;background:LightGoldenrodYellow; text-align:center; border: solid; border-width: 1px" | ÁMBITO SUPRAMUNICIPAL
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Galicia||style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"|2.701.819
|-
| style="background:Ivory; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Área Metropolitana de Barcelona||style="background:Ivory; text-align:right; color:#000000; border: solid; border-width: 1px" |3.339.279
|-
| style= "background:White; text-align:left; color:#000000; border: solid; border-width: 1px; width:200px" | Comunidad de Madrid|| style="background:White; text-align:right; color:#000000; border: solid; border-width: 1px"| 6.779.888
|-
| colspan=2; style="background:white; text-align:left" | <div style="padding-top: 0em; padding-right: 0.5em; padding-bottom: 0em; padding-left: 0.5em; style="background:White; font-size: 95%"><small style="color:#959595">Fuente: Estadística del Padrón continuo 2020. INE. Se relacionan las ciudades y ámbitos supramunicipales que se analizan en los ejemplos contenidos en este tema. Figuran en el orden en el que aparecen en la publicación</small></div>
|}
|}
</div>
</div>

<div style="text-align:left">
Durante la llamada primera ola de la pandemia COVID-19 en España el impacto sanitario ha sido muy dispar espacialmente. En los temas precedentes, la unidad de análisis y representación de esta diversidad ha sido mayoritariamente la provincia, un territorio extenso que encierra en su seno una condición física y humana a veces muy contrastada.

En este tema de la monografía se desciende a una escala de mayor detalle, la metropolitana o municipal, e incluso dentro de esta se llega, en algunos casos, a unidades inferiores como los distritos municipales, barrios o secciones censales. Esta aproximación permite afinar algunas hipótesis de trabajo con suficiente fundamento a la hora de buscar relaciones entre determinadas variables temáticas y el comportamiento espacial de la pandemia, aunque, en esta nueva aproximación, no cabe esperar conclusiones definitivas al respecto.

Una primera idea que parece desprenderse de la lectura de los mapas y gráficos que se incluyen en este tema es la decisiva importancia del factor humano en la incidencia mayor o menor de los efectos sanitarios de la pandemia en el seno de las ciudades y áreas metropolitanas. La movilidad de la población, la renta familiar disponible, el nivel de paro laboral, el peso del grupo de personas por debajo del umbral de la pobreza, el tipo de hábitat o la ubicación espacial de las residencias de población mayor son, entre otras, condiciones a tener en cuenta para calibrar mejor el impacto sanitario producido.

Un paso más se da en los ejemplos propuestos cuando se abordan índices de cariz integrador y señalan la peligrosidad, el riesgo o la vulnerabilidad en el seno del espacio urbano o metropolitano, sirviéndose para ello de unidades de análisis y representación espacial de mayor detalle como en algún caso son las secciones censales.

[[Archivo:Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.jpg|left|thumb|300px|Mapa: Localización de comportamientos espaciales diferenciados. 2020. España. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.pdf PDF]. [//centrodedescargas.cnig.es/CentroDescargas/busquedaRedirigida.do?ruta=PUBLICACION_CNIG_DATOS_VARIOS/aneTematico/Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.zip Datos].]]
Los ejemplos presentados son cinco como se puede ver en el mapa de ''[[:Archivo:Espana_Localizacion-de-comportamientos-espaciales-diferenciados_2020_mapa_18050_spa.jpg|Localización de las áreas estudiadas]]'': Galicia, la ciudad de Zaragoza, Barcelona y su área metropolitana, la Comunidad de Madrid y la propia ciudad y, por último, Málaga. En los casos de las ciudades de Zaragoza y Málaga, la cartografía se ciñe al entorno municipal; en Galicia, se parte de una visión de conjunto de la comunidad autónoma para descender después a las ciudades de A Coruña, Ourense, Santiago de Compostela y Vigo, en las que se refleja la dispersión de los focos de contagio, presumiblemente ligada esa dispersión a la propia estructura del hábitat gallego y ubicación de residencias de mayores en las afueras de las ciudades.

En el caso de Barcelona y su entorno, se toma una doble perspectiva que va desde el contexto metropolitano, al propiamente municipal de la ciudad con sus distritos y barrios. En el ejemplo de Madrid, también se presta atención a una doble aproximación: la estrictamente municipal con sus distritos y la del territorio autónomo como marco más general.

En los casos de las ciudades de Barcelona y Madrid, se ha elaborado un índice sintético de vulnerabilidad social, teniendo como unidad espacial de análisis a la sección censal. Se estima que ello puede contribuir a una mejor comprensión de la afección diferenciada de la pandemia en el territorio y en la comunidad humana que lo habita.
</div>

{{ANETextoDestacado|titulo=IDEAS CLAVE CONTENIDAS EN LOS EJEMPLOS PRESENTADOS EN ESTE TEMA|contenido=
1. La estructura del poblamiento ha podido influir en el grado de afección de la pandemia al ser un elemento de contención del virus, cuando aquella muestra mayor dispersión social y, en definitiva, una menor intensidad del contacto físico.

2. No resulta arriesgado manifestar, aunque sea como hipótesis dotada con suficiente fundamento, que la pobreza y precariedad social han podido provocar en la primera ola de la pandemia, así como en las posteriores, más contagios y víctimas entre los más vulnerables.

3. La distinta capacidad de reducir la movilidad que hace uso básicamente de los medios públicos de transporte dentro del espacio urbano, ligada al tipo de trabajo desempeñado por determinados grupos sociales y a su condición económica más precaria, puede ser uno de los factores o condicionantes que parece han incidido en una afección de la pandemia más acusada.

4. El factor densidad demográfica en un entorno urbano tuvo, en la primera ola de la pandemia, una clara relación con la distribución del número de afectados, aunque no fue el único. Más bien, hay que acudir a un modelo multifactorial más complejo para tratar de encontrar una explicación satisfactoria.

5. A tenor de la respuesta ciudadana a una encuesta sobre la situación anímica de la población durante el confinamiento domiciliario en la gran ciudad, se ha detectado que, en determinados sectores urbanos con un grado de vulnerabilidad social alto, el número de respuestas de cariz positivo frente a la situación anímica vivida ha sido significativamente elevado lo que indica una alta capacidad de resiliencia en los mismos.

6. Otra hipótesis que parece vislumbrarse y reclama la atención de los especialistas es el diferente comportamiento de la pandemia según sexos. Los datos apuntan a un mayor impacto en los varones en cuanto a los hospitalizados, ingresados en UCI y fallecidos, a pesar de diagnosticarse como positivas un mayor número de mujeres. Este hecho parece evidenciar una mayor gravedad de los síntomas y repercusiones de la enfermedad en los hombres.}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}
<div style="text-align:left">
{{ANEPaginaDescargas (monografía COVID-19)}}
</div>

{{ANENavegacionHermanos

|anterior=[[Visión de conjunto]]

|siguiente=[[Gobernanza territorial]]
}}

[[Categoría:Servicios y equipamientos sociales]]
[[Categoría:Población, poblamiento y sociedad]]

Talk:Overview

2022-03-09T11:14:06Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Overview}}{{ANEIndiceCapitulo|colorcaja=#628D93
|indice=
*[[Epidemiological indicators]]
*[[Overall mortality]]
*[[Estimated excess mortality]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Downward phase of the pandemic]]

|siguiente=[[Different spatial behaviours]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Talk:Overview

2022-03-09T11:12:20Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Overview}}{{ANEIndiceCapitulo|colorcaja=#EFA824
|indice=
*[[Epidemiological indicators]]
*[[Overall mortality]]
*[[Estimated excess mortality]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Downward phase of the pandemic]]

|siguiente=[[Different spatial behaviours]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Talk:Overview

2022-03-09T11:11:19Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[The COVID-19 pandemic in Spain|The COVID-19 pandemic in Spain]]|capitulo=Overview}}{{ANEIndiceCapitulo|colorcaja=#EFA824
|indice=
*[[Indicadores epidemiológicos]]
*[[Mortalidad general]]
*[[Sobremortalidad estimada]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Fase descendente de la pandemia]]

|siguiente=[[Comportamientos espaciales diferenciados]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Talk:Overview

2022-03-09T11:10:36Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[La pandemia COVID-19 en España|La pandemia COVID-19 en España]]|capitulo=Visión de conjunto}}{{ANEIndiceCapitulo|colorcaja=#EFA824
|indice=
*[[Indicadores epidemiológicos]]
*[[Mortalidad general]]
*[[Sobremortalidad estimada]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Fase descendente de la pandemia]]

|siguiente=[[Comportamientos espaciales diferenciados]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Talk:Overview

2022-03-09T11:08:54Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monographs from the National Atlas of Spain|Logo=[[File:Logo Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANEIndiceSeccion
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[La pandemia COVID-19 en España|La pandemia COVID-19 en España]]|capitulo=Visión de conjunto}}{{ANEIndiceCapitulo|colorcaja=#EFA824
|indice=
*[[Indicadores epidemiológicos]]
*[[Mortalidad general]]
*[[Sobremortalidad estimada]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Fase descendente de la pandemia]]

|siguiente=[[Comportamientos espaciales diferenciados]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Talk:Overview

2022-03-09T11:08:06Z

Usr1:

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[File:Logo_Monografía.jpg|left|50x50px|link=]]|Título=The COVID-19 pandemic in Spain|Subtítulo=First wave: from the first cases to the end of June 2020|Año=2021|Contenido=New content}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[La pandemia COVID-19 en España|La pandemia COVID-19 en España]]|capitulo=Visión de conjunto}}{{ANEIndiceCapitulo|colorcaja=#EFA824
|indice=
*[[Indicadores epidemiológicos]]
*[[Mortalidad general]]
*[[Sobremortalidad estimada]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Fase descendente de la pandemia]]

|siguiente=[[Comportamientos espaciales diferenciados]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Talk:Overview

2022-03-09T11:07:24Z

Usr1: Created page with "{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la v..."

{{ANEEtiqueta|palabrasclave=pandemia, covid19, indicadores epidemiológicos, indicadores sanitarios, mortalidad general, sobremortalidad estimada|descripcion=Análisis de la visión de conjunto|url=valor}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[File:Logo_Monografía.jpg|left|50x50px|link=]]|Título=La pandemia COVID-19 en España|Subtítulo=Primera ola: de los primeros casos a finales de junio de 2020|Año=2021|Contenido=Nuevo contenido}}
{{ANENavegacionCapitulo (monografía COVID-19)|estructura temática=Estructura temática|seccion=[[La pandemia COVID-19 en España|La pandemia COVID-19 en España]]|capitulo=Visión de conjunto}}{{ANEIndiceCapitulo|colorcaja=#EFA824
|indice=
*[[Indicadores epidemiológicos]]
*[[Mortalidad general]]
*[[Sobremortalidad estimada]]
}}<br>
En este tema se ofrece en primer lugar una visión de conjunto del comportamiento de algunos indicadores sanitarios o epidemiológicos; a continuación, a partir de los datos ofrecidos por el Instituto Nacional de Estadística (INE), se trata la mortalidad general acaecida en el periodo de estudio y su comparación con la que podría denominarse habitual o esperada; por último, se atiende a la información publicada también por el INE acerca de la sobremortalidad computada semanalmente.

No busque el lector establecer conclusiones apresuradas al comparar entre sí los tres aspectos señalados que integran el contenido de este tema. La información estadística procede de fuentes distintas y cada una de estas posee una metodología propia.

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}

{{ANENavegacionHermanos

|anterior=[[Fase descendente de la pandemia]]

|siguiente=[[Comportamientos espaciales diferenciados]]

}}

[[Categoría:Población, poblamiento y sociedad]]
[[Categoría:Servicios y equipamientos sociales]]

Internal territorial governance

2022-03-09T11:04:26Z

Usr1: Created page with "Page under construction"

Page under construction

Talk:Social, economic and environmental effects

2022-03-09T11:04:04Z

Usr1:

{{ANEEtiqueta

|palabrasclave=sección III, pandemia, covid-19, covid19

|descripcion=Efectos sociales, económicos y ambientales

|url=

}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[File:Logo_Monografía.jpg|left|50x50px|link=]]|Título=La pandemia COVID-19 en España|Subtítulo=Primera ola: de los primeros casos a finales de junio de 2020|Año=2021|Contenido=Nuevo contenido}}
{{ANEIndiceSeccion
|color=#A25652
|indice=
*[[Internal territorial governance|Internal territorial governance]]
*[[Movilidad]]
**[[Transporte por carretera (monografía COVID-19)|Transporte por carretera]]
**[[Transporte por ferrocarril (monografía COVID-19)|Transporte por ferrocarril]]
**[[Transporte urbano (monografía COVID-19)|Transporte urbano]]
**[[Transporte aéreo (monografía COVID-19)|Transporte aéreo]]
**[[Transporte marítimo (monografía COVID-19)|Transporte marítimo]]
**[[Movilidad detectada a través de la telefonía|Movilidad detectada a través de la telefonía]]
*[[Magnitudes macroeconómicas y sectores productivos]]
**[[Magnitudes macroeconómicas (monografía COVID-19)|Magnitudes macroeconómicas]]
**[[Agricultura y pesca|Agricultura y pesca]]
**[[Minería, energía, industria y construcción (monografía COVID-19)|Minería, energía, industria y construcción]]
**[[Servicios no turísticos|Servicios no turísticos]]
**[[Turismo (monografía COVID-19)|Turismo]]
*[[Trabajo (monografía COVID-19)|Trabajo]]
*[[Hacienda pública (monografía COVID-19)|Hacienda pública]]
*[[Educación (monografía COVID-19)|Educación]]
*[[Acciones solidarias|Acciones solidarias]]
*[[Repercusiones ambientales|Repercusiones ambientales]]
|contenido=
Los efectos de una pandemia como la sufrida por razón de la COVID-19 son difíciles de precisar, tanto a nivel planetario o global, como en cada uno de los países. Entre las repercusiones las hay tangibles e intangibles, a corto o largo plazo, personales o comunitarias, locales o nacionales e internacionales.

Sería un propósito inalcanzable medir con precisión, a todos los niveles y en los diferentes campos, el impacto producido por un fenómeno tan inesperado como severo. Tómese, por tanto, el contenido de esta sección como una propuesta que constata la incidencia de la pandemia COVID-19 en España en algunos aspectos que, al margen de los sanitarios, se han considerado más significativos.

Se han buscado aquellas facetas que cuentan con información cuantitativa y actualizada que nos permitan acercarnos a una representación lo más objetiva posible de lo acontecido. Los recursos gráficos y cartográficos, bien sostenidos por un soporte largamente pensado, no agotan las posibilidades de conformar una imagen acabada que hiciera posible percibir la totalidad de los efectos producidos. Son, tan solo, una manifestación de cariz epidérmico que esconde un fondo que quizás nunca se podrá desvelar.

El hilo argumental que sostiene la exposición de contenidos recorre un hipotético camino desde la respuesta a la pandemia que ha dado la gobernanza territorial hasta la incidencia producida en el entorno medioambiental. En medio se considera el brusco cambio operado en la movilidad de personas y mercancías, el impacto producido en las magnitudes macroeconómicas y sectores productivos, las transformaciones en el funcionamiento y estructura del mercado de trabajo, la influencia en la recaudación por parte de la hacienda pública, el embate sufrido por el sistema educativo por razón del confinamiento domiciliario y, por último, la movilización institucional y social que desencadenó un auténtico alud de acciones solidarias.

Puede que, de fijarnos tan solo en los temas citados, se nos escape la verdadera entidad del hecho vivido. Un virus, ente extremadamente insignificante por su tamaño, ha sido capaz de paralizar el mundo. Seguramente acertó Italo Calvino cuando, antes de morir en 1985, vaticinó que la levedad –lo que pesa poco y es diminuto– iba a ser uno de los valores imperantes en el tercer milenio; en el tema tratado en esta monografía, parece corroborarse aquella afirmación, hecha por el autor citado en relación a creatividad literaria, pues se ha constatado que algo tan diminuto ha provocado impactos de impensable calado.

El enorme problema vivido arrancó de algo extremadamente pequeño, desatando efectos inesperados por su envergadura: enfermedad, muerte, crisis social y económica. Puede que también vaya a incidir en un deseable cambio de paradigma de nuestra relación con el entorno, haciéndola más justa y sostenible. En todo caso, la comunidad humana ha demostrado, una vez más, su capacidad de reacción al procurar los auxilios sanitarios pertinentes para vencer a la pandemia en un tiempo muy corto y retomar con renovada energía el camino de la recuperación social y económica.
}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosUltimo
|anterior=[[La pandemia COVID-19 en España]]
}}

Talk:Social, economic and environmental effects

2022-03-09T11:03:02Z

Usr1:

{{ANEEtiqueta

|palabrasclave=sección III, pandemia, covid-19, covid19

|descripcion=Efectos sociales, económicos y ambientales

|url=

}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[File:Logo_Monografía.jpg|left|50x50px|link=]]|Título=La pandemia COVID-19 en España|Subtítulo=Primera ola: de los primeros casos a finales de junio de 2020|Año=2021|Contenido=Nuevo contenido}}
{{ANEIndiceSeccion
|color=#A25652
|indice=
*[[Gobernanza territorial]]
*[[Movilidad]]
**[[Transporte por carretera (monografía COVID-19)|Transporte por carretera]]
**[[Transporte por ferrocarril (monografía COVID-19)|Transporte por ferrocarril]]
**[[Transporte urbano (monografía COVID-19)|Transporte urbano]]
**[[Transporte aéreo (monografía COVID-19)|Transporte aéreo]]
**[[Transporte marítimo (monografía COVID-19)|Transporte marítimo]]
**[[Movilidad detectada a través de la telefonía|Movilidad detectada a través de la telefonía]]
*[[Magnitudes macroeconómicas y sectores productivos]]
**[[Magnitudes macroeconómicas (monografía COVID-19)|Magnitudes macroeconómicas]]
**[[Agricultura y pesca|Agricultura y pesca]]
**[[Minería, energía, industria y construcción (monografía COVID-19)|Minería, energía, industria y construcción]]
**[[Servicios no turísticos|Servicios no turísticos]]
**[[Turismo (monografía COVID-19)|Turismo]]
*[[Trabajo (monografía COVID-19)|Trabajo]]
*[[Hacienda pública (monografía COVID-19)|Hacienda pública]]
*[[Educación (monografía COVID-19)|Educación]]
*[[Acciones solidarias|Acciones solidarias]]
*[[Repercusiones ambientales|Repercusiones ambientales]]
|contenido=
Los efectos de una pandemia como la sufrida por razón de la COVID-19 son difíciles de precisar, tanto a nivel planetario o global, como en cada uno de los países. Entre las repercusiones las hay tangibles e intangibles, a corto o largo plazo, personales o comunitarias, locales o nacionales e internacionales.

Sería un propósito inalcanzable medir con precisión, a todos los niveles y en los diferentes campos, el impacto producido por un fenómeno tan inesperado como severo. Tómese, por tanto, el contenido de esta sección como una propuesta que constata la incidencia de la pandemia COVID-19 en España en algunos aspectos que, al margen de los sanitarios, se han considerado más significativos.

Se han buscado aquellas facetas que cuentan con información cuantitativa y actualizada que nos permitan acercarnos a una representación lo más objetiva posible de lo acontecido. Los recursos gráficos y cartográficos, bien sostenidos por un soporte largamente pensado, no agotan las posibilidades de conformar una imagen acabada que hiciera posible percibir la totalidad de los efectos producidos. Son, tan solo, una manifestación de cariz epidérmico que esconde un fondo que quizás nunca se podrá desvelar.

El hilo argumental que sostiene la exposición de contenidos recorre un hipotético camino desde la respuesta a la pandemia que ha dado la gobernanza territorial hasta la incidencia producida en el entorno medioambiental. En medio se considera el brusco cambio operado en la movilidad de personas y mercancías, el impacto producido en las magnitudes macroeconómicas y sectores productivos, las transformaciones en el funcionamiento y estructura del mercado de trabajo, la influencia en la recaudación por parte de la hacienda pública, el embate sufrido por el sistema educativo por razón del confinamiento domiciliario y, por último, la movilización institucional y social que desencadenó un auténtico alud de acciones solidarias.

Puede que, de fijarnos tan solo en los temas citados, se nos escape la verdadera entidad del hecho vivido. Un virus, ente extremadamente insignificante por su tamaño, ha sido capaz de paralizar el mundo. Seguramente acertó Italo Calvino cuando, antes de morir en 1985, vaticinó que la levedad –lo que pesa poco y es diminuto– iba a ser uno de los valores imperantes en el tercer milenio; en el tema tratado en esta monografía, parece corroborarse aquella afirmación, hecha por el autor citado en relación a creatividad literaria, pues se ha constatado que algo tan diminuto ha provocado impactos de impensable calado.

El enorme problema vivido arrancó de algo extremadamente pequeño, desatando efectos inesperados por su envergadura: enfermedad, muerte, crisis social y económica. Puede que también vaya a incidir en un deseable cambio de paradigma de nuestra relación con el entorno, haciéndola más justa y sostenible. En todo caso, la comunidad humana ha demostrado, una vez más, su capacidad de reacción al procurar los auxilios sanitarios pertinentes para vencer a la pandemia en un tiempo muy corto y retomar con renovada energía el camino de la recuperación social y económica.
}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosUltimo
|anterior=[[La pandemia COVID-19 en España]]
}}

Talk:Social, economic and environmental effects

2022-03-09T11:02:43Z

Usr1: Created page with "{{ANEEtiqueta |palabrasclave=sección III, pandemia, covid-19, covid19 |descripcion=Efectos sociales, económicos y ambientales |url= }}{{ANEObra|Serie=Monografías del At..."

{{ANEEtiqueta

|palabrasclave=sección III, pandemia, covid-19, covid19

|descripcion=Efectos sociales, económicos y ambientales

|url=

}}{{ANEObra|Serie=Monografías del Atlas Nacional de España|Logo=[[Archivo:Logo_Monografía.jpg|left|50x50px|link=]]|Título=La pandemia COVID-19 en España|Subtítulo=Primera ola: de los primeros casos a finales de junio de 2020|Año=2021|Contenido=Nuevo contenido}}
{{ANEIndiceSeccion
|color=#A25652
|indice=
*[[Gobernanza territorial]]
*[[Movilidad]]
**[[Transporte por carretera (monografía COVID-19)|Transporte por carretera]]
**[[Transporte por ferrocarril (monografía COVID-19)|Transporte por ferrocarril]]
**[[Transporte urbano (monografía COVID-19)|Transporte urbano]]
**[[Transporte aéreo (monografía COVID-19)|Transporte aéreo]]
**[[Transporte marítimo (monografía COVID-19)|Transporte marítimo]]
**[[Movilidad detectada a través de la telefonía|Movilidad detectada a través de la telefonía]]
*[[Magnitudes macroeconómicas y sectores productivos]]
**[[Magnitudes macroeconómicas (monografía COVID-19)|Magnitudes macroeconómicas]]
**[[Agricultura y pesca|Agricultura y pesca]]
**[[Minería, energía, industria y construcción (monografía COVID-19)|Minería, energía, industria y construcción]]
**[[Servicios no turísticos|Servicios no turísticos]]
**[[Turismo (monografía COVID-19)|Turismo]]
*[[Trabajo (monografía COVID-19)|Trabajo]]
*[[Hacienda pública (monografía COVID-19)|Hacienda pública]]
*[[Educación (monografía COVID-19)|Educación]]
*[[Acciones solidarias|Acciones solidarias]]
*[[Repercusiones ambientales|Repercusiones ambientales]]
|contenido=
Los efectos de una pandemia como la sufrida por razón de la COVID-19 son difíciles de precisar, tanto a nivel planetario o global, como en cada uno de los países. Entre las repercusiones las hay tangibles e intangibles, a corto o largo plazo, personales o comunitarias, locales o nacionales e internacionales.

Sería un propósito inalcanzable medir con precisión, a todos los niveles y en los diferentes campos, el impacto producido por un fenómeno tan inesperado como severo. Tómese, por tanto, el contenido de esta sección como una propuesta que constata la incidencia de la pandemia COVID-19 en España en algunos aspectos que, al margen de los sanitarios, se han considerado más significativos.

Se han buscado aquellas facetas que cuentan con información cuantitativa y actualizada que nos permitan acercarnos a una representación lo más objetiva posible de lo acontecido. Los recursos gráficos y cartográficos, bien sostenidos por un soporte largamente pensado, no agotan las posibilidades de conformar una imagen acabada que hiciera posible percibir la totalidad de los efectos producidos. Son, tan solo, una manifestación de cariz epidérmico que esconde un fondo que quizás nunca se podrá desvelar.

El hilo argumental que sostiene la exposición de contenidos recorre un hipotético camino desde la respuesta a la pandemia que ha dado la gobernanza territorial hasta la incidencia producida en el entorno medioambiental. En medio se considera el brusco cambio operado en la movilidad de personas y mercancías, el impacto producido en las magnitudes macroeconómicas y sectores productivos, las transformaciones en el funcionamiento y estructura del mercado de trabajo, la influencia en la recaudación por parte de la hacienda pública, el embate sufrido por el sistema educativo por razón del confinamiento domiciliario y, por último, la movilización institucional y social que desencadenó un auténtico alud de acciones solidarias.

Puede que, de fijarnos tan solo en los temas citados, se nos escape la verdadera entidad del hecho vivido. Un virus, ente extremadamente insignificante por su tamaño, ha sido capaz de paralizar el mundo. Seguramente acertó Italo Calvino cuando, antes de morir en 1985, vaticinó que la levedad –lo que pesa poco y es diminuto– iba a ser uno de los valores imperantes en el tercer milenio; en el tema tratado en esta monografía, parece corroborarse aquella afirmación, hecha por el autor citado en relación a creatividad literaria, pues se ha constatado que algo tan diminuto ha provocado impactos de impensable calado.

El enorme problema vivido arrancó de algo extremadamente pequeño, desatando efectos inesperados por su envergadura: enfermedad, muerte, crisis social y económica. Puede que también vaya a incidir en un deseable cambio de paradigma de nuestra relación con el entorno, haciéndola más justa y sostenible. En todo caso, la comunidad humana ha demostrado, una vez más, su capacidad de reacción al procurar los auxilios sanitarios pertinentes para vencer a la pandemia en un tiempo muy corto y retomar con renovada energía el camino de la recuperación social y económica.
}}

{{ANEAutoria|Autores=José Sancho Comíns}}

{{ANESubirArriba}}

{{ANEPaginaDescargas (monografía COVID-19)}}
{{ANENavegacionHermanosUltimo
|anterior=[[La pandemia COVID-19 en España]]
}}

Synthetic vulnerability index in Barcelona and Madrid

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Málaga

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City and Region of Madrid

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Barcelona and its metropolitan area

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Saragossa (Zaragoza)

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Galicia

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Different spatial behaviours

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Estimated excess mortality

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Overall mortality

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Epidemiological indicators

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Overview

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The COVID-19 pandemic in Spain

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Downward phase of the pandemic

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Putting resources into action

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First COVID-19 cases

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Resources for health services before the pandemic

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Population, human settlements and comorbidities

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