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

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 thi...

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Bibliographic Details
Published in:PLOS Neglected Tropical Diseases
Main Authors: Ka Chun Chong, Jinjun Ran, Steven Yuk Fai Lau, William Bernard Goggins, Shi Zhao, Pin Wang, Linwei Tian, Maggie Haitian Wang, Kirran N Mohammad, Lai Wei, Xi Xiong, Hengyan Liu, Paul Kay Sheung Chan, Huwen Wang, Yawen Wang, Jingxuan Wang
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2021
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Online Access:https://doi.org/10.1371/journal.pntd.0009056
https://doaj.org/article/47fdd27d2af04b148a7977cd3066e337
Description
Summary: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.