Investigating the Relationship Between Air Quality and COVID-19 Transmission

Albrecht, Laura; Czarnecki, Paulina; Sakelaris, Bennet

doi:10.6339/21-JDS1010

Journal of Data Science

Investigating the Relationship Between Air Quality and COVID-19 Transmission^✩

Volume 19, Issue 3 (2021), pp. 485–497

Laura Albrecht ^†

Paulina Czarnecki ^†

Bennet Sakelaris ^†

https://doi.org/10.6339/21-JDS1010

Pub. online: 23 March 2021 Type: Data Science In Action

^✩ Version information: This is an updated version from the one released in April 2021. The update corrected the unit of PM 2.5 to AQI in Figures 3–4 and a few places involving it in the text.

^† All authors contributed equally to this work.

Received
29 December 2020

Accepted
26 February 2021

Published
23 March 2021

Abstract

It is hypothesized that short-term exposure to air pollution may influence the transmission of aerosolized pathogens such as COVID-19. We used data from 23 provinces in Italy to build a generalized additive model to investigate the association between the effective reproductive number of the disease and air quality while controlling for ambient environmental variables and changes in human mobility. The model finds that there is a positive, nonlinear relationship between the density of particulate matter in the air and COVID-19 transmission, which is in alignment with similar studies on other respiratory illnesses.

Supplementary material

Supplementary Material

The data and R code used to generate these results, as well as figures for individual cities in the validation process, are included in the supplementary files. A README is provided to describe the data available, how to generate each figure presented in the paper, and where important variables should be found in the code.

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Keywords

air pollution effective reproduction number generalized additive model mobility particulate matter

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