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

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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.

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It's luck that has saved us from the pandemic -financial review
  • Afr
AFR, 2020. It's luck that has saved us from the pandemic -financial review. URL: https://www.afr.com/policy/health-and-education/ it-s-luck-that-has-saved-us-from-the-pandemic-20200420-p54lbg. [Online].
Air quality open data platform
AQICN, 2020. Air quality open data platform. URL: https://aqicn.org/data-platform/covid19/verify/ 0a29217a-fb3a-4572-97dc-353d1b9b42fb. [Online].
Why britain ended up as the one of the worst in the world at fighting coronavirus -the experts' views
  • P Bharat
Bharat, P., 2020. Why britain ended up as the one of the worst in the world at fighting coronavirus -the experts' views. URL: https://www.telegraph.co.uk/news/2020/05/01/ britain-ended-one-worst-world-fighting-coronavirus-experts/. the Telegraph -[Online].
Research on the relationship between air quality and cardiovascular diseases in ningbo based on dlmn model
  • Y Hu
  • G Li
  • J Liu
  • Y Wu
  • X Yao
  • L Feng
HU, Y., LI, G., LIU, J., WU, Y., YAO, X., FENG, L., 2018. Research on the relationship between air quality and cardiovascular diseases in ningbo based on dlmn model. Journal of Zhejiang Wanli University, 20.
Short-term impact of air pollutants on influenza-like illness in yichang city
  • Q Liao
  • X J Hu
  • Q Xue
LIAO, Q., HU, X.j., XUE, Q., et al., 2018. Short-term impact of air pollutants on influenza-like illness in yichang city. Journal of Environmental and Occupational Medicine 35, 879-884.
Coronavirus disease 2019 (covid-19) situation report 62
  • Who
WHO, 2020a. Coronavirus disease 2019 (covid-19) situation report 62. URL: https://www.who.int/emergencies/diseases/. [Online].
Coronavirus disease (covid-19) pandemic
  • Who
WHO, 2020b. Coronavirus disease (covid-19) pandemic. URL: https: //www.who.int/emergencies/diseases/novel-coronavirus-2019. [Online].