Meteorological conditions and nonpharmaceutical interventions jointly determined local transmissibility of COVID-19 in 41 Chinese cities: A retrospective observational study

Li-Qun Fang; Hai-Yang Zhang; Han Zhao; Tian-Le Che; An-Ran Zhang; Ming-Jin Liu; Wen-Qiang Shi; Jian-Ping Guo; Yong Zhang; Wei Liu; Yang Yang

doi:10.1016/j.lanwpc.2020.100020

Meteorological conditions and nonpharmaceutical interventions jointly determined local transmissibility of COVID-19 in 41 Chinese cities: A retrospective observational study

Lancet Reg Health West Pac. 2020 Sep:2:100020. doi: 10.1016/j.lanwpc.2020.100020. Epub 2020 Sep 6.

Authors

Li-Qun Fang¹, Hai-Yang Zhang¹, Han Zhao², Tian-Le Che¹, An-Ran Zhang^{1

3

4}, Ming-Jin Liu³, Wen-Qiang Shi¹, Jian-Ping Guo⁵, Yong Zhang², Wei Liu¹, Yang Yang³

Affiliations

¹ State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China.
² School of Mathematical Sciences, Beijing Normal University, Beijing 100875, PR China.
³ Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
⁴ Department of Epidemiology, School of Public Health, Shandong University, Jinan, PR China.
⁵ The State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, PR China.

Abstract

Background: Before effective vaccines become widely available, sufficient understanding of the impacts of climate, human movement and non-pharmaceutical interventions on the transmissibility of COVID-19 is needed but still lacking.

Methods: We collected by crowdsourcing a database of 11 003 COVID-19 cases from 305 cities outside Hubei Province from December 31, 2019 to April 27, 2020. We estimated the daily effective reproduction numbers (R_t ) of COVID-19 in 41 cities where the crowdsourced case data are comparable to the official surveillance data. The impacts of meteorological variables, human movement indices and nonpharmaceutical emergency responses on R_t were evaluated with generalized estimation equation models.

Findings: The median R_t was 0•46 (IQR: 0•37-0•87) in the northern cities, higher than 0•20 (IQR: 0•09-0•52) in the southern cities (p=0•004). A higher local transmissibility of COVID-19 was associated with a low temperature, a relative humidity near 70-75%, and higher intracity and intercity human movement. An increase in temperature from 0℃ to 20℃ would reduce R_t by 30% (95 CI 10-46%). A further increase to 30℃ would result in another 17% (95% CI 5-27%) reduction. An increase in relative humidity from 40% to 75% would raise the transmissibility by 47% (95% CI 9-97%), but a further increase to 90% would reduce the transmissibility by 12% (95% CI 4-19%). The decrease in intracity human movement as a part of the highest-level emergency response in China reduced the transmissibility by 36% (95% CI 27-44%), compared to 5% (95% CI 1-9%) for restricting intercity transport. Other nonpharmaceutical interventions further reduced R_t by 39% (95% CI 31-47%).

Interpretation: Climate can affect the transmission of COVID-19 where effective interventions are implemented. Restrictions on intracity human movement may be needed in places where other nonpharmaceutical interventions are unable to mitigate local transmission.

Funding: China Mega-Project on Infectious Disease Prevention; U.S. National Institutes of Health and National Science Foundation.

Abstract

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