Nonlinear modulation of COVID-19 transmission by climate conditions

Meng Gao*, Qiming Zhou, Xian Yang, Qingxiang Li, Shiqing Zhang, Kin Lam Yung, Yi-Ke Guo*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

9 Citations (Scopus)

Abstract

COVID-19 is spreading rapidly worldwide, posing great threats to public health and economy. This study aims to examine how the transmission of COVID-19 is modulated by climate conditions, which is of great importance for better understanding of the seasonal feature of COVID-19. Constrained by the accurate observations we can make, the basic reproduction numbers (R0) for each country were inferred and linked to temperature and relative humidity (RH) with statistical analysis. Using R0 as the measure of COVID-19 transmission potential, we find stronger transmission of COVID-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 COVID-19 transmission and climate conditions suggest that seasonal climate variability may affect the spread and severity of COVID-19 infection, and temperate coastal regions with mildly warm and humid climate would be susceptible to large-scale outbreaks.

Original languageEnglish
Article numbere1985
Number of pages6
JournalMeteorological Applications
Volume28
Issue number2
DOIs
Publication statusPublished - 23 Mar 2021

Scopus Subject Areas

  • Atmospheric Science

User-Defined Keywords

  • COVID-19
  • relative humidity
  • temperature
  • transmission

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