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

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.