Trends of SARS-Cov-2 infection in 67 countries: Role of climate zone, temperature, humidity, and curve behavior of cumulative frequency on duplication time Trends of SARS-CoV-2 in 67 countries based on climate zone
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Aims. To analyze the role of temperature, humidity, date of first case diagnosed (DFC) and behavior of the growth-curve of cumulative frequency (CF) [number of days to rise (DCS) and reach the first 100 cases (D100), and the difference between them (ΔDD)] with the doubling time (Td) of COVID-19 cases in 67 countries grouped by climate zone.
Methods. Retrospective study based on the WHO registry of cumulative incidence of COVID-19 cases. 1,706,914 subjects diagnosed between 12-29-2019 and 4-15-2020 were analyzed based on exposure to SARS-CoV-2 virus, ambient humidity, temperature, and climate areas (temperate, tropical/subtropical). DCS, D100, ΔDD, DFC, humidity, temperature, Td for the first (Td10) and second (Td20) ten days of the CF growth-curve between countries and were compared according to climate zone, and identification of factors involved in Td, as well as predictors of CF using lineal regression models.
Results. Td10 and Td20 were ≥3 days longer in tropical/subtropical vs. temperate areas (2.8±1.2 vs. 5.7±3.4; p=1.41E-05 and 4.6±1.8 vs. 8.6±4.2; p=9.7E-05, respectively). The factors involved in Td10 (DFC and ΔDD) were different than those in Td20 (Td10 and climate areas). After D100, the fastest growth-curves during the first 10 days, were associated with Td10<2 and Td10<3 in temperate and tropical/subtropical countries, respectively. The fold change Td20/Td10 >2 was associated with earlier flattening of the growth-curve. In multivariate models, Td10, DFC and ambient temperature were negatively related with CF and explained 44.7% (r2 = 0.447) of CF variability at day 20 of the growth-curve, while Td20 and DFC were negatively related with CF and explained 63.8% (r2 = 0.638) of CF variability towards day 30 of the growth-curve.
Conclusions. Larger Td in tropical/subtropical countries is positively related to DFC and temperature. Td and environmental factors explain up to 64% of CF variability. However, pandemic containment measures may explain the remaining variability.
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