Influence of coarse particulate matter on chickenpox in Jiading District, Shanghai, 2009–2018: A distributed lag non-linear time series analysis

Abstract

Although the link between ambient air pollution and some infectious diseases has been studied, few studies have explored so far, the relationship between chickenpox and particulate matter. Daily chickenpox counts in Jiading District, Shanghai, were collected from 2009 to 2018. Time series analysis was conducted to describe the trends of the daily number of chickenpox cases and the concentration of particulate matter 10 μm or less (PM10). The distributed lag non-linear model (DLNM) was developed to assess the lag and non-linear relationship between the number of chickenpox cases and PM10 concentration adjusting for meteorological factors and other pollutants. Spatiotemporal scanning was used to detect the clustering of chickenpox cases. There was a concomitant relationship between the number of chickenpox cases and PM10 concentration, especially in the period of high PM10 concentration. DLNM results showed a nonlinear relationship between the number of chickenpox cases and PM10 concentration with the maximum effect of PM10 being lagged for 13–14 days, which was consistent with the average incubation period of chickenpox. PM10 was significantly associated with the daily number of chickenpox cases when above 300 μg/m3. The risk of chickenpox increased with increasing PM10 concentration and the association was strongest at the lag of 14 day (RR = 1.13, 95% CI: 1.04–1.23) for PM10 concentration of 500 μg/m3 versus 50 μg/m3. The study provides evidence that high PM10 concentration increases the risk of chickenpox spreading.