Impact of meteorological factors on the COVID-19 transmission: A multicity study in China

Authors

Jiangtao Liu, Lanzhou University
Ji Zhou, Shanghai Meteorological Bureau
Jinxi Yao, Gansu Provincial Centre for Diseases Prevention and Control
Xiuxia Zhang, Lanzhou University of Technology
Lanyu Li, Lanzhou University
Xiaocheng Xu, Lanzhou University
Xiaotao He, Lanzhou University
Bo Wang, Lanzhou University
Shihua Fu, Lanzhou University
Tingting Niu, Lanzhou University
Jun Yan, First Hospital of Lanzhou University
Yanjun Shi, Lanzhou University
Xiaowei Ren, Lanzhou University
Jingping Niu, Lanzhou University
Weihao Zhu, Hebei Climate Centre, Hebei Meteorological Bureau
Sheng Li, CUNY School of Public HealthFollow
Bin Luo, Lanzhou University
Kai Zhang, University of Texas Health Science Center at Houston

Document Type

Article

Publication Date

4-9-2020

Abstract

The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID- 19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below0 °C, 12 cities had average AHbelow4 g/m3, and one city (Haikou) had the highest AH (14.05 g/m3). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition,we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission.

Comments

This work was originally published in Science of the Total Environment, available at https://doi.org/10.1016/j.scitotenv.2020.138513