Málaga

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The COVID-19 pandemic in Spain. First wave: from the first cases to the end of June 2020

Monographs from the National Atlas of Spain.


Thematic structure > The COVID-19 pandemic in Spain > Different spatial behaviours > Málaga

Map: Covid-19 hotspots. City of Málaga. 2020. Málaga. PDF. More information.
Map: Infection hazard. Number of COVID-19 cases. City of Málaga. 2020. Málaga. PDF. More information.
Map: Infection hazard. Percentage of COVID-19 cases. City of Málaga. 2020. Málaga. PDF. More information.
Map: Population density and COVID-19 hotspots. City of Málaga. 2020. Málaga. PDF. More information.
Map: Vulnerability to COVID-19. City of Málaga. 2020. Málaga. PDF. More information.
Map: Risk of COVID-19 infection. City of Málaga. 2020. Málaga. PDF. More information.

The maps showing the COVID-19 outbreak in the city of Málaga during the rising phase of the first wave of the COVID-19 pandemic (March 2020) have been drawn up from a very detailed, real-time updated source of information, i.e. COVID-19 cases by home address. These thorough data have enabled assessing the patterns of distribution of COVID-19 cases in place and time in an urban environment over months of observation. COVID-19 cases do not show a spatial pattern of random distribution. Instead, they are gathered in clusters or aggregation of cases related by geographical propinquity called hotspots.

A hotspot is the area occupied by an aggregation of at least five COVID-19 cases lying under 200 metres away from each other. Hotspots are the basic units used in urban areas for studying infections. Were there an aggregation of cases in a specific area at a certain time, a sudden rise in the amount of infections would occur in the surroundings. A source of infection may exist at professional or social events. However, once the infected returns home, he or she breeds a secondary or transmitted infection around his or her residence.

The risk of infection in each hotspot has been assessed on the basis of the general equation of risk, i.e. cross-checking infection hazard, vulnerability and exposure. The total amount of cases as well as the percentage that cases mean amongst the total population have been used to grade hazard. Vulnerability has been estimated from the number of people exposed to COVID-19, inhabitants arranged in age groups and levels of home overcrowding, i.e. ratio of home size to number of household members.

Mapping hotspots and the risk of infection may be very useful when it comes to deciding on a relevant issue. The probability of being infected within a certain period is higher when living close to a hotspot than when living anywhere else in the city. This entails a direct predictive way that enables focusing on specific areas in the city where surveillance, alerts, screens and reports shall be intensified. This all helps stopping infections at the very root.

The spatial distribution of COVID-19 cases was uneven during the first period as may be observed on the different maps. Broadly speaking, hotspot patterns of distribution in the city of Málaga may be explained by dividing the territory in three stripes running parallel to the coast, i.e. a southern strip, a central band and a northern fringe. The southern strip, which spreads along the coastline, is ruled by a scattered distribution of cases that do not form hotspots, except for Malagueta, Alameda de Colón and Echevarría (El Palo). In the same vein, the western part of this coastal band shows a predominantly dispersed pattern of distribution in the neighbourhoods located south of the railway. This dispersed pattern of distribution is also largely found in the areas located on the right bank of the River Guadalhorce. To the north of this southern strip, there is a central band of the city where the spatial pattern of infection is no longer disperse, but concentrated, as the aggregation of cases around hotspots increases significantly. The pattern of distribution becomes disperse again in the northern fringe of the city, both in its central and western sectors.

The historical city centre shows a dispersed pattern of distribution in which no hotspots may be discerned. In the western part of the city, the hotspots around La Unión / Los Tilos and Camino de San Rafael streets are the most significant aggregation of cases. However, the whole area around Cádiz road, with areas of high population density, shows a fairly dispersed pattern of distribution where no clear hotspots may be observed. The area that concentrates a greater amount of hotspots is the one located to the north-west of the city, mainly to the north of Carlos Haya avenue and Martínez Maldonado street. Hotspots located to the northwest of the Regional Hospital are noteworthy for the high case density that does not match with the population density in the area.

When looking for causes that may explain the hotspot patterns of distribution, the most immediate assumption is the one that links a higher concentration of cases to a higher population density. A preliminary analysis of the population density map of Málaga, on which also the location of the main hotspots is shown, reveals that the areas with the highest case density are also the areas with the highest population density. However, this thesis does not hold in the opposite direction, as there are large areas of the city with very low population density that nevertheless have a high percentage of COVID-19 cases. In the same vein, areas of high population density with no significant aggregation of cases are very common (e.g. the northern and western parts of the city).

When assessing the possible explaining factors for case distribution in an urban area during the first wave of the pandemic, a conclusion may be drawn: although population density is partly related to the case distribution, a more complex multi-factorial model underlies. Economic activity and age (young students, type of work, etc.) contribute in the first instance to the location and transmission of infection, which will then be distributed according to the mobility of the population, the shifts amongst hotspots as well as some other reasons. Variables such as building typology and living conditions (e.g. overcrowding, ventilation, etc.) or proximity to areas of possible infection (e.g. hospitals, healthcare centres, etc.) are also explaining factors. On the other hand, nearness to the sea and the positive environmental conditions it provides (less pollution, greater exposure to the wind, etc.) may lead to fewer hotspots.


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Co-authorship of the text in Spanish: Matías Mérida Rodríguez, Jesús Miranda Páez, María Jesús Perles Roselló y Juan Francisco Sortino Barrionuevo. See the list of members engaged


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You can download the complete publication The COVID-19 pandemic in Spain. First wave: from the first cases to the end of June 2020 in Libros Digitales del ANE site.