The short-term seasonal analyses between atmospheric environment and COVID-19 in epidemic areas of Cities in Australia, South Korea, and Italy

TL;DR

This study analyzes how atmospheric environmental factors like temperature, humidity, and pollutants influence COVID-19 transmission dynamics in Australia, South Korea, and Italy, revealing seasonal and pollutant effects on the basic reproduction number (R0).

Contribution

It introduces a cross-country analysis of short-term environmental impacts on COVID-19 transmission using DLNM and identifies key pollutants affecting disease spread.

Findings

Air temperature and humidity affect R0 with lag effects.

PM10 significantly influences excess morbidity.

O3, PM2.5, and SO2 have cumulative impacts.

Abstract

The impact of the outbreak of COVID-19 on health has been widely concerned. Disease risk assessment, prediction, and early warning have become a significant research field. Previous research suggests that there is a relationship between air quality and the disease. This paper investigated the impact of the atmospheric environment on the basic reproduction number (R$_0$) in Australia, South Korea, and Italy by using atmospheric environment data, confirmed case data, and the distributed lag non-linear model (DLNM) model based on Quasi-Poisson regression. The results show that the air temperature and humidity have lag and persistence on short-term R$_0$, and seasonal factors have an apparent decorating effect on R$_0$. PM$_{10}$ is the primary pollutant that affects the excess morbidity rate. Moreover, O$_3$, PM$_{2.5}$, and SO$_2$ as perturbation factors have an apparent cumulative effect. These results present beneficial knowledge for correlation between environment and COVID-19, which guiding prospective analyses of disease data.