Limited role for meteorological factors on the variability in COVID-19 incidence: A retrospective study of 102 Chinese cities

Chong, Ka Chun; Ran, Jinjun; Lau, Steven Yuk Fai; Goggins, William Bernard; Zhao, Shi; Wang, Pin; Tian, Linwei; Wang, Maggie Haitian; Mohammad, Kirran N.; Wei, Lai; Xiong, Xi; Liu, Hengyan; Chan, Paul Kay Sheung; Wang, Huwen; Wang, Yawen; Wang, Jingxuan

While many studies have focused on identifying the association between meteorological factors and the activity of COVID-19, we argue that the contribution of meteorological factors to a reduction of the risk of COVID-19 was minimal when the effects of control measures were taken into account. In this study, we assessed how much variability in COVID-19 activity is attributable to city-level socio-demographic characteristics, meteorological factors, and the control measures imposed. We obtained the daily incidence of COVID-19, city-level characteristics, and meteorological data from a total of 102 cities situated in 27 provinces/municipalities outside Hubei province in China from 1 January 2020 to 8 March 2020, which largely covers almost the first wave of the epidemic. Generalized linear mixed effect models were employed to examine the variance in the incidence of COVID-19 explained by different combinations of variables. According to the results, including the control measure effects in a model substantially raised the explained variance to 45%, which increased by >40% compared to the null model that did not include any covariates. On top of that, including temperature and relative humidity in the model could only result in < 1% increase in the explained variance even though the meteorological factors showed a statistically significant association with the incidence rate of COVID-19. In conclusion, we showed that very limited variability of the COVID-19 incidence was attributable to meteorological factors. Instead, the control measures could explain a larger proportion of variance.