Impact of temperature and relative humidity on the transmission of COVID-19: A modelling study in China and the United States

Abstract

Objectives We aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status. Design A retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted. Setting We use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties. Participants A total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers. Primary outcome measures Regression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value). Results Statistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the USA. Conclusions Higher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (-0.0395 to-0.0125)) in China and by 0.020 (95% CI (-0.0311 to-0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (-0.0108 to-0.0045)) in China and by 0.0080 (95% CI (-0.0150 to-0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic.