» Articles » PMID: 35317468

Novel Evidence Showing the Possible Effect of Environmental Variables on COVID-19 Spread

Overview
Journal Geohealth
Date 2022 Mar 23
PMID 35317468
Authors
Affiliations
Soon will be listed here.
Abstract

Coronavirus disease (COVID-19) remains a serious issue, and the role played by meteorological indicators in the process of virus spread has been a topic of academic discussion. Previous studies reached different conclusions due to inconsistent methods, disparate meteorological indicators, and specific time periods or regions. This manuscript is based on seven daily meteorological indicators in the NCEP reanalysis data set and COVID-19 data repository of Johns Hopkins University from 22 January 2020 to 1 June 2021. Results showed that worldwide average temperature and precipitable water (PW) had the strongest correlation ( > 0.9,  < 0.001) with the confirmed COVID-19 cases per day from 22 January to 31 August 2020. From 22 January to 31 August 2020, positive correlations were observed between the temperature/PW and confirmed COVID-19 cases/deaths in the northern hemisphere, whereas negative correlations were recorded in the southern hemisphere. From 1 September to 31 December 2020, the opposite results were observed. Correlations were weak throughout the near full year, and weak negative correlations were detected worldwide (|| < 0.4,  ≤ 0.05); the lag time had no obvious effect. As the latitude increased, the temperature and PW of the maximum confirmed COVID-19 cases/deaths per day generally showed a decreasing trend; the 2020-year fitting functions of the response latitude pattern were verified by the 2021 data. Meteorological indicators, although not a decisive factor, may influence the virus spread by affecting the virus survival rates and enthusiasm of human activities. The temperature or PW threshold suitable for the spread of COVID-19 may increase as the latitude decreases.

Citing Articles

Evolving Drivers of Brazilian SARS-CoV-2 Transmission: A Spatiotemporally Disaggregated Time Series Analysis of Meteorology, Policy, and Human Mobility.

Kerr G, Badr H, Barbieri A, Colston J, Gardner L, Kosek M Geohealth. 2023; 7(3):e2022GH000727.

PMID: 36960326 PMC: 10030230. DOI: 10.1029/2022GH000727.


Novel Evidence Showing the Possible Effect of Environmental Variables on COVID-19 Spread.

Zhang S, Wang B, Yin L, Wang S, Hu W, Song X Geohealth. 2022; 6(3):e2021GH000502.

PMID: 35317468 PMC: 8923516. DOI: 10.1029/2021GH000502.

References
1.
Xie J, Zhu Y . Association between ambient temperature and COVID-19 infection in 122 cities from China. Sci Total Environ. 2020; 724:138201. PMC: 7142675. DOI: 10.1016/j.scitotenv.2020.138201. View

2.
Quesada J, Lopez-Pineda A, Gil-Guillen V, Arriero-Marin J, Gutierrez F, Carratala-Munuera C . Incubation period of COVID-19: A systematic review and meta-analysis. Rev Clin Esp (Barc). 2021; 221(2):109-117. PMC: 7698828. DOI: 10.1016/j.rceng.2020.08.002. View

3.
Gasparrini A, Guo Y, Hashizume M, Lavigne E, Zanobetti A, Schwartz J . Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet. 2015; 386(9991):369-75. PMC: 4521077. DOI: 10.1016/S0140-6736(14)62114-0. View

4.
Zhang S, Wang B, Wang S, Hu W, Wen X, Shao P . Influence of air pollution on human comfort in five typical Chinese cities. Environ Res. 2020; 195:110318. DOI: 10.1016/j.envres.2020.110318. View

5.
Juni P, Rothenbuhler M, Bobos P, Thorpe K, da Costa B, Fisman D . Impact of climate and public health interventions on the COVID-19 pandemic: a prospective cohort study. CMAJ. 2020; 192(21):E566-E573. PMC: 7259972. DOI: 10.1503/cmaj.200920. View