The Impact of Meteorological Factors and Air Pollution on the Spread of COVID-19

Danhua Huang,Jiashu Zhao,Xueqin Wang,Yukang Jiang,Yewei Li,Ting Tian

doi:10.6339/jds.202012_18(5).0005

Abstract

The new coronavirus disease (COVID-19), as a new infectious disease, has relatively strong ability to spread from person to person. This paper studies several meteorological factors and air quality indicators between Shenzhen and Wenzhou, China, and conducts modelling analysis on whether the transmission of COVID-19 is affected by atmosphere. A comparative assessment is made on the characteristics of meteorological factors and air quality in these two typical cities in China and their impacts on the spread of COVID-19. The article uses meteorological data and air quality data, including 7 variables: daily average temperature, daily average relative humidity, daily average wind speed, nitrogen dioxide (NO2), atmospheric fine particulate matter (PM2.5), carbon monoxide (CO) and ozone (O3), a distributed lag non-linear model (DLNM) is constructed to explore the correlation between atmospheric conditions and non-imported confirmed cases of COVID-19, and the relative risk is introduced to measure the lagging effects of meteorological factors and air pollution on the number of non-imported confirmed cases. Our finding indicates that there is significant differences in the relationship between 7 predictors and the transmission of COVID-19 in Shenzhen and Wenzhou. However, all predictors between the two cities have a non-linear relationship with the number of non-imported confirmed cases. The lower daily average temperature has increased the risk of epidemic transmission in the two cities. As the temperature rises, the risk of epidemic transmission in both cities will significantly decrease. The average daily relative humidity has no significant effects on the epidemic situation in Shenzhen, but the lower relative humidity reduces the risk of epidemic spread in Wenzhou. In contrast, meteorological data have significant impacts on the spread of COVID-19 in Wenzhou. The four predictors (NO2, PM2.5, CO, and O3) have significant effects on the number of nonimported confirmed cases. Among them, PM2.5 has a significant positive correlation with the number of non-imported confirmed cases. Daily average wind speed, NO2 and O3 have different effects on the number of non-imported confirmed cases in different cities.

Highlights

新型冠状病毒疾病(COVID-19)作为一种新发传染病,具有较强的人际传播能力。本文研究了中国深圳市和温州市 2 个城市的若干气象因素与空气质量指标,对 COVID-19 是否受空气影响进行建模分析。对中国两个典型城市中的气象因素和空气质量的特征及其对 COVID-19 的影响, 进行对比评估。本文利用气象数据与空气质量数据,包括日平均温度、日平均相对湿度、日平均⻛速、二氧化氮(NO2)、大气细颗粒物(PM2.5)、一氧化碳(CO)和臭氧(O3),针对 COVID-19 确诊人数构建分布滞后非线性模型(Distributed Lag Non-Linear Model, distributed lag non-linear model (DLNM)),引入了相对危险度来衡量气象因素和大气污染因素对确诊人数的滞后影响,并考虑气象因素和大气污染因素对 COVID-19 发病可能存在滞后效应,探究空气因素与确诊病例的相关关系和趋势变化。文章发现,深圳市和温州市在 7 个指标与 COVID-19 的效应关系上呈现明显的差异。但所有指标在两个城市间,都与 COVID-19 的患病人数呈现非线性关系。较低的日平均温度使两座城市的疫情传播的⻛险有所上升,随着温度的升高,两座城市的疫情传播⻛险均会显著下降。日平均相对湿度对深圳疫情情况则几乎没有影响,而较低的相对湿度使得温州市疫情传播⻛险降低。相比而言,气象数据对温州市的 COVID-19 的传播具有显著影响。NO2、PM2.5、carbon monoxide (CO)、O3 四个指标与 COVID-19 的患病人数存在显著效应。其中 PM2.5 与 COVID-19 患病人数呈显著正相关关系;日平均⻛速、NO2 与 O3 在不同城市对患病人数的影响有所差异。
This paper studies several meteorological factors and air quality indicators between Shenzhen and Wenzhou, China, and conducts modelling analysis on whether the transmission of COVID-19 is affected by atmosphere
A comparative assessment is made on the characteristics of meteorological factors and air quality in these two typical cities in China and their impacts on the spread of COVID-19

Summary

Introduction

新型冠状病毒疾病(COVID-19)作为一种新发传染病,具有较强的人际传播能力。本文研究了中国深圳市和温州市 2 个城市的若干气象因素与空气质量指标,对 COVID-19 是否受空气影响进行建模分析。对中国两个典型城市中的气象因素和空气质量的特征及其对 COVID-19 的影响, 进行对比评估。本文利用气象数据与空气质量数据,包括日平均温度、日平均相对湿度、日平均⻛速、二氧化氮(NO2)、大气细颗粒物(PM2.5)、一氧化碳(CO)和臭氧(O3),针对 COVID-19 确诊人数构建分布滞后非线性模型(Distributed Lag Non-Linear Model, DLNM),引入了相对危险度来衡量气象因素和大气污染因素对确诊人数的滞后影响,并考虑气象因素和大气污染因素对 COVID-19 发病可能存在滞后效应,探究空气因素与确诊病例的相关关系和趋势变化。文章发现,深圳市和温州市在 7 个指标与 COVID-19 的效应关系上呈现明显的差异。但所有指标在两个城市间,都与 COVID-19 的患病人数呈现非线性关系。较低的日平均温度使两座城市的疫情传播的⻛险有所上升,随着温度的升高,两座城市的疫情传播⻛险均会显著下降。日平均相对湿度对深圳疫情情况则几乎没有影响,而较低的相对湿度使得温州市疫情传播⻛险降低。相比而言,气象数据对温州市的 COVID-19 的传播具有显著影响。NO2、PM2.5、CO、O3 四个指标与 COVID-19 的患病人数存在显著效应。其中 PM2.5 与 COVID-19 患病人数呈显著正相关关系;日平均⻛速、NO2 与 O3 在不同城市对患病人数的影响有所差异。. The Impact of Meteorological Factors and Air Pollution on the Spread of COVID-19 This paper studies several meteorological factors and air quality indicators between Shenzhen and Wenzhou, China, and conducts modelling analysis on whether the transmission of COVID-19 is affected by atmosphere. A comparative assessment is made on the characteristics of meteorological factors and air quality in these two typical cities in China and their impacts on the spread of COVID-19.

Results

Conclusion