The relationship between (sub)tropical climates and the incidence of COVID-19
David Prata,
Waldecy Rodrigues,
Paulo Henrique De Souza Bermejo,
Marina Moreira,
Wainesten Camargo,
Marcelo Lisboa,
Geovane Rossone Reis,
Humberto Xavier de Araujo
Affiliations
David Prata
Institute of Regional Development, Graduate Program of Computational Modelling, Federal University of Tocantins, Palmas, Brazil
Waldecy Rodrigues
Institute of Regional Development, Graduate Program of Computational Modelling, Federal University of Tocantins, Palmas, Brazil
Paulo Henrique De Souza Bermejo
Research and Development Center for Public Sector Excellence and Transformation (NExT) of the Department of Administration, Federal University of Brasilia, Brazil
Marina Moreira
Research and Development Center for Public Sector Excellence and Transformation (NExT) of the Department of Administration, Federal University of Brasilia, Brazil
Wainesten Camargo
Institute of Regional Development, Graduate Program of Computational Modelling, Federal University of Tocantins, Palmas, Brazil
Marcelo Lisboa
Institute of Regional Development, Graduate Program of Computational Modelling, Federal University of Tocantins, Palmas, Brazil
Geovane Rossone Reis
Institute of Regional Development, Graduate Program of Computational Modelling, Federal University of Tocantins, Palmas, Brazil
Humberto Xavier de Araujo
Institute of Regional Development, Graduate Program of Computational Modelling, Federal University of Tocantins, Palmas, Brazil
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.
