Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China.
Lam, Jacqueline CK
Li, Victor OK
Springer Science and Business Media LLC
MetadataShow full item record
Han, Y., Lam, J. C., Li, V. O., Crowcroft, J., Fu, J., Downey, J., Gozes, I., et al. (2021). Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China.. Sci Rep, 11 (1) https://doi.org/10.1038/s41598-021-02523-5
This study investigates thoroughly whether acute exposure to outdoor PM2.5 concentration, P, modifies the rate of change in the daily number of COVID-19 infections (R) across 18 high infection provincial capitals in China, including Wuhan. A best-fit multiple linear regression model was constructed to model the relationship between P and R, from 1 January to 20 March 2020, after accounting for meteorology, net move-in mobility (NM), time trend (T), co-morbidity (CM), and the time-lag effects. Regression analysis shows that P (β = 0.4309, p < 0.001) is the most significant determinant of R. In addition, T (β = -0.3870, p < 0.001), absolute humidity (AH) (β = 0.2476, p = 0.002), P × AH (β = -0.2237, p < 0.001), and NM (β = 0.1383, p = 0.003) are more significant determinants of R, as compared to GDP per capita (β = 0.1115, p = 0.015) and CM (Asthma) (β = 0.1273, p = 0.005). A matching technique was adopted to demonstrate a possible causal relationship between P and R across 18 provincial capital cities. A 10 µg/m3 increase in P gives a 1.5% increase in R (p < 0.001). Interaction analysis also reveals that P × AH and R are negatively correlated (β = -0.2237, p < 0.001). Given that P exacerbates R, we recommend the installation of air purifiers and improved air ventilation to reduce the effect of P on R. Given the increasing observation that COVID-19 is airborne, measures that reduce P, plus mandatory masking that reduces the risks of COVID-19 associated with viral-particulate transmission, are strongly recommended. Our study is distinguished by the focus on the rate of change instead of the individual cases of COVID-19 when modelling the statistical relationship between R and P in China; causal instead of correlation analysis via the matching analysis, while taking into account the key confounders, and the individual plus the interaction effects of P and AH on R.
Air Pollutants, COVID-19, China, Cities, Humans, Incidence, Particulate Matter, Risk Assessment, SARS-CoV-2
Research Grants Council, University Grants Committee (T41-709/17-N)
External DOI: https://doi.org/10.1038/s41598-021-02523-5
This record's URL: https://www.repository.cam.ac.uk/handle/1810/331497
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: firstname.lastname@example.org