Meteorological parameters and cases of COVID-19 in Brazilian cities: an observational study

ABSTRACT

Meteorological parameters modulate transmission of the SARS-Cov-2 virus, the causative agent related to coronavirus disease-2019 (COVID-19) development. However, findings across the globe have been inconsistent attributed to several confounding factors. The aim of the present study was to investigate the relationship between reported meteorological parameters from July 1 to October 31, 2020, and the number of confirmed COVID-19 cases in 4 Brazilian cities: São Paulo, the largest city with the highest number of cases in Brazil, and the cities with greater number of cases in the state of Parana during the study period (Curitiba, Londrina and Maringa). The assessment of meteorological factors with confirmed COVID-19 cases included atmospheric pressure, temperature, relative humidity, wind speed, solar irradiation, sunlight, dew point temperature, and total precipitation. The 7- and 15-day moving averages of confirmed COVID-19 cases were obtained for each city. Pearson’s correlation coefficients showed significant correlations between COVID-19 cases and all meteorological parameters, except for total precipitation, with the strongest correlation with maximum wind speed (0.717, <0.001) in São Paulo. Regression tree analysis demonstrated that the largest number of confirmed COVID-19 cases was associated with wind speed (between ≥0.3381 and <1.173 m/s), atmospheric pressure (<930.5mb), and solar radiation (<17.98e⁺³). Lower number of cases was observed for wind speed <0.3381 m/s and temperature <23.86°C. Our results encourage the use of meteorological information as a critical component in future risk assessment models.

KEYWORDS:

• COVID-19
• cases
• meteorological factors
• regression tree
• transmissibility

Acknowledgments

MA was supported in part by grant from NIEHS (National Institute of Environmental Health Sciences - R01ES10563 and R01ES07331); JPPP was supported in part by CNPq (National Council for Scientific and Technological Development - 310.608/2017).

Declaration of competing interest

The authors declare no perceived or known conflict of interest.

Additional information

Funding

This work was supported by the National Council for Scientific and Technological Development (CNPq) [310.608/2017]; National Institute of Environmental Health Sciences [R01ES10563 and R01ES07331].