The association between ambient air pollution and scarlet fever in Qingdao, China, 2014–2018: a quantitative analysis

Abstract Background We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014–2018. Methods A model (DLNM) combined with generalized additive mixed (GAMM) was applied effects of pollutions on fever, daily incidence as dependent variable independent adjusted for potential confounders. Results total 6316 cases were notified, there 376 days occurring study period. Scarlet significantly associated at 7 different relative risk (RR) degrees [1.172, 95% confidence interval (CI): 1.038–1.323 mild pollution; 1.374, CI 1.078–1.749 moderate 1.610, 1.163–2.314 severe 1.887, 1.163–3.061 most pollution]. Conclusions Our findings show that is positively Qingdao, could be increased along pollution. It contributes developing strategies prevent reduce health impact from other non-vaccine-preventable respiratory infectious diseases polluted areas.