Environmental and socioeconomic factors : weather and COVID-19 cases in Cape Town

Abstract

Cape Town, a microcosm of one of the most unequal societies in the world, remains both socially and spatially segregated. In this research, we address whether or not that separation is related to recorded COVID-19 cases in the city. We estimate both the temperature and relative humidity relationship to cases, via distributed-lag nonlinear model (DLNM) components, since the relationship between environmental factors and health can be delayed. The DLNM framework describes the additional time (lag) of the exposure-response association, capturing both the nonlinear exposure-response and the delays. We also expand the discussion to include lockdown measures, their association with infections and socio-economic status in Cape Town. We find that (i) relative humidity, more than temperature, is associated with changes in reported COVID-19 risk; (ii) at relatively high temperatures (21 °C), relative case risk is lower in the low socio-economic status areas; (iii) case risk is generally higher in the same areas.