RESUMO
OBJECTIVE: This study investigates the spatial differences in the occurrence of COVID-19 in Brazilian Tropical Zone and its relationship with climatic, demographic, and economic factors based on data from February 2020 to May 2021. METHODS: A Linear Regression Model with the GDP per capita, demographic density and climatic factors from 5.534 Brazilian cities with (sub)tropical climate was designed and used to explain the spread of COVID-19 in Brazil. MAIN RESULTS: The model shows evidence that economic, demographic and climate factors maintain a relationship with the variation in the number of cases of COVID-19. The Köppen climate classification defines climatic regions by rainfall and temperature. Some studies have shown an association between temperature and humidity and the survival of SARS-CoV-2. In this cohort study, Brazilian cities located in tropical regions without a dry season (monthly rainfall > 60 mm) showed a greater prevalence than in cities located in tropical regions with a dry season (some monthly rainfall < 60 mm). CONCLUSION: Empirical evidence shows that the Brazil's tropical-climate cities differ in the number (contamination rate) of COVID-19 cases, mainly because of humidity. This study aims to alert the research community and public policy-makers to the trade-off between temperature and humidity for the stability of SARS-COV-2, and the implications for the spread of the virus in tropical climate zones.
RESUMO
This work explores (non)linear associations between relative humidity and temperature and the incidence of COVID-19 among 27 Brazilian state capital cities in (sub)tropical climates, measured daily from summer through winter. Previous works analyses have shown that SARS-CoV-2, the virus that causes COVID-19, finds stability by striking a certain balance between relative humidity and temperature, which indicates the possibility of surface contact transmission. The question remains whether seasonal changes associated with climatic fluctuations might actively influence virus survival. Correlations between climatic variables and infectivity rates of SARS-CoV-2 were applied by the use of a Generalized Additive Model (GAM) and the Locally Estimated Scatterplot Smoothing LOESS nonparametric model. Tropical climates allow for more frequent outdoor human interaction, making such areas ideal for studies on the natural transmission of the virus. Outcomes revealed an inverse relationship between subtropical and tropical climates for the spread of the novel coronavirus and temperature, suggesting a sensitivity behavior to climates zones. Each 1 °C rise of the daily temperature mean correlated with a -11.76% (t = -5.71, p < 0.0001) decrease and a 5.66% (t = 5.68, p < 0.0001) increase in the incidence of COVID-19 for subtropical and tropical climates, respectively.