Climate Influences on COVID-19 Prevalence Rates: An Application of a Panel Data Spatial Model

ABSTRACT

The present study aims to measure the impact of climate characteristics on the prevalence rate of COVID-19 in Brazilian states given the exogenous nature of these variables. We used a daily panel for the period from March 10 to April 10, 2020, the first phase of the pandemic, as there were few intervention policies to contain the spread of COVID-19 during that period, and it was estimated, through GLS, spatial models to control the presence of spatial spillover, first-order autoregressive errors and correlation between cross-sections. Considering the COVID-19 incubation period and the time it takes for COVID-19 symptoms to manifest, the econometric models were estimated using the 14-, 11- and 7- day moving averages of the climate variables. The results showed that increases of 1% in the solar incidence, average temperature and relative humidity of the air reduced COVID-19 prevalence rates by 0.16%, 0.049% and 0.22%, respectively, considering the 11-day moving average.