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• W4229901750 abstract "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 generalized additive Mixed Model (GAMM) combined with a distributed lag non-linear model (DLNM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results: A total of 6,316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different RRs of air pollution degrees (1.172, 95%CI: 1.038-1.323 in mild air pollution; 1.374, 95%CI: 1.078-1.749 in moderate air pollution; 1.610, 95%CI: 1.163-2.314 in severe air pollution; 1.887, 95%CI: 1.163-3.061 in most severe air pollution). Conclusions: Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas." @default.
• W4229901750 created "2022-05-11" @default.
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• W4229901750 date "2020-04-30" @default.
• W4229901750 modified "2023-09-24" @default.
• W4229901750 title "The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis" @default.
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• W4229901750 doi "https://doi.org/10.21203/rs.2.18047/v3" @default.
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