Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location.

Xiao-Dong Yang,Yue-E Cao,Hong-Li Li

doi:10.3390/ijerph18020484

Xiao-Dong Yang, Yue-E Cao + Show 1 more

Open Access

https://doi.org/10.3390/ijerph18020484

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Abstract

The purpose of this study is to investigate whether the relationship between meteorological factors (i.e., daily maximum temperature, minimum temperature, average temperature, temperature range, relative humidity, average wind speed and total precipitation) and COVID-19 transmission is affected by season and geographical location during the period of community-based pandemic prevention and control. COVID-19 infected case records and meteorological data in four cities (Wuhan, Beijing, Urumqi and Dalian) in China were collected. Then, the best-fitting model of COVID-19 infected cases was selected from four statistic models (Gaussian, logistic, lognormal distribution and allometric models), and the relationship between meteorological factors and COVID-19 infected cases was analyzed using multiple stepwise regression and Pearson correlation. The results showed that the lognormal distribution model was well adapted to describing the change of COVID-19 infected cases compared with other models (R2 > 0.78; p-values < 0.001). Under the condition of implementing community-based pandemic prevention and control, relationship between COVID-19 infected cases and meteorological factors differed among the four cities. Temperature and relative humidity were mainly the driving factors on COVID-19 transmission, but their relations obviously varied with season and geographical location. In summer, the increase in relative humidity and the decrease in maximum temperature facilitate COVID-19 transmission in arid inland cities, while at this point the decrease in relative humidity is good for the spread of COVID-19 in coastal cities. For the humid cities, the reduction of relative humidity and the lowest temperature in the winter promote COVID-19 transmission.

Highlights

The 2019 coronavirus disease (COVID-19) is ascribed to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus
Our study provides a new view for explaining the reasons for COVID-19 transmission while under the implementation of community-based pandemic prevention and control, which is conducive to predicting COVID-19 transmission dynamics, and developing effective prevention and control measures
Pearson correlation and multiple stepwise regressions were used to analyze if the relationship between meteorological factors and COVID-19 infected cases were different among the four cities, and if the relationship can be affected by the season and geographic location

Summary

Introduction

The 2019 coronavirus disease (COVID-19) is ascribed to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus. COVID-19 quickly appeared around the world after the first report in Wuhan of Hubei province, China, in late December 2019. COVID-19 as a global public health emergency and one of the major human disasters in the 21st century. 1,404,542 deaths had been reported around the world [1]. It is estimated that the global impact of COVID-19 may last several years [1]. As temperatures fall and winter arrives, the COVID-19 pandemic in many parts of the Northern Hemisphere, such as France, UK, Spain, Italy and Belgium, have seen a second outbreak [2].

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