Outdoor PM _2.5 Concentration and Rate of Change in COVID-19 Infection in Provincial Capital Cities in China

Motivated by earlier findings that exposure to daily outdoor PM _2.5 (P) may increase the risk of influenza infection, our study examines if immediate exposure to outdoor P will modify the rate of change in the daily number of COVID-19 infections (R), for (1) the high infection provincial capital cities in China and (2) Wuhan, China, using regression modelling. A multiple linear regression model was constructed to model the statistical relationship between P and R in China and in Wuhan, from 1 January to 20 March 2020. We carefully accounted for potential key confounders and addressed collinearity. The causal relationship between P and R, and the interaction effect between key variables were investigated. A causal relationship between P and R across the high infection provincial capital cities in China was established via matching. A higher P resulted in a higher R in China. A 10 µg/m ³ increase in P gave a 1.5% increase in R ( p < 0.001). An interaction analysis between P and absolute humidity (AH) showed a statistically significant negative relationship between P × AH and R ( p < 0.05). When AH was $ 5.8 g/m ³ , a higher P and AH gave a higher R. In contrast, when AH ≥ 5.8 g/m ³ , the effect of a higher P was counteracted by the effect of a higher AH, resulting in a lower R. Given that P can exacerbate R, we recommend the installation of air purifiers and better air ventilation to reduce the effect of P on R. Further, given the increasing discussions/observations that COVID-19 can be airborne, we highly recommend the wearing of surgical masks to keep one from contracting COVID-19 via the viral-particulate transmission pathway.