GIS-based spatial modelling of COVID-19 death incidence in Sao Paulo, Brazil

Seeking to understand the socio-spatial behaviour of the COVID-19 virus in the most impacted area in Brazil, five spatial regression models were analysed to assess the disease distribution in the affected territory. Results obtained using the Spearman correlation test provided evidence for the correlation between COVID-19 death incidence and social aspects such as population density, average people per household, and informal urban settlements. More importantly, all analysed models using four selected explanatory variables have proven to represent at least 85 per cent of reported deaths at the district level. Overall, our results have demonstrated that the geographically weighted regression (GWR) model best explains the spatial distribution of COVID-19 in the city of Sao Paulo, highlighting the spatial aspects of the data. Spatial analysis has shown the spread of COVID-19 in areas with highly vulnerable populations. Our findings corroborate reports from the recent literature, pointing out the need for special attention in peripheral areas and informal settlements.

Automated summary

The research findings indicate that there is a correlation between COVID-19 death incidence and social aspects such as population density, average people per household, and informal urban settlements. The geographically weighted regression (GWR) model provides the best explanation for the spatial distribution of COVID-19 in São Paulo city, highlighting the spatial aspects of the data.