Author: Gao, Meng; Zhou, Qiming; Yang, Xian; Li, Qingxiang; Zhang, Shiqing; Yung, Ken Kin Lam; Guo, Yike
Title: Nonlinear modulation of COVIDâ€19 transmission by climate conditions Cord-id: n0qn73dp Document date: 2021_3_23
ID: n0qn73dp
Snippet: COVIDâ€19 is spreading rapidly worldwide, posing great threats to public health and economy. This study aims to examine how the transmission of COVIDâ€19 is modulated by climate conditions, which is of great importance for better understanding of the seasonal feature of COVIDâ€19. Constrained by the accurate observations we can make, the basic reproduction numbers (R (0)) for each country were inferred and linked to temperature and relative humidity (RH) with statistical analysis. Using R (0)
Document: COVIDâ€19 is spreading rapidly worldwide, posing great threats to public health and economy. This study aims to examine how the transmission of COVIDâ€19 is modulated by climate conditions, which is of great importance for better understanding of the seasonal feature of COVIDâ€19. Constrained by the accurate observations we can make, the basic reproduction numbers (R (0)) for each country were inferred and linked to temperature and relative humidity (RH) with statistical analysis. Using R (0) as the measure of COVIDâ€19 transmission potential, we find stronger transmission of COVIDâ€19 under mildly warm (0°C < T < 20°C) and humid (RH > 60%) climate conditions, while extremely low (T < −2°C) and high (T > 20°C) temperature or a dry climate (RH < 60%) weakens transmission. The established nonlinear relationships between COVIDâ€19 transmission and climate conditions suggest that seasonal climate variability may affect the spread and severity of COVIDâ€19 infection, and temperate coastal regions with mildly warm and humid climate would be susceptible to largeâ€scale outbreaks.
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