Housing-Type and Urban Spatial Patterns of Infectious Diseases: Spatial Analysis of COVID-19 Cases at Household Level in Málaga (Spain)

Abstract

Although many studies examine housing conditions during COVID-19 lockdowns, fewer explore how housing attributes and their spatial distribution relate to disease risk. This study applies an Exploratory Spatial Data Analysis (ESDA) framework to connect housing and COVID-19 data in Malaga, Spain. A relative risk surface was generated using spatial point pattern methods to identify high-risk areas. COVID-19 cases were then linked to residential buildings through geoprocessing, allowing characterization of housing features at the building level. Local Moran’s I analysis identified clusters with higher Excess Risk (ER), revealing five clearly defined high-risk areas across the city. However, some building clusters with high concentrations of cases differed from these zones. These clusters were analyzed according to building typology, and Spearman’s correlation suggested associations between case rates and several construction variables. Yet Quasi-Poisson regression results indicated that no individual construction variable had a significant effect on case rates. Housing type, however, showed a notable association: multi-family buildings presented an incidence rate ratio of 84% (95% CI: 80–88%) compared with single-family dwellings, indicating a 16% lower incidence in the former. In summary, results show that there are specific areas in the city which were prone to higher rates of cases, which also show particular housing type distributions, with single-family homes displaying a higher risk, despite being the less frequent type of dwelling.