Abstract
BackgroundWe 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.MethodsA distributed lag non-linear model (DLNM) combined with a generalized additive mixed model (GAMM) 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.ResultsA total of 6316 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 relative risk (RR) of air pollution degrees [1.172, 95% confidence interval (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].ConclusionsOur 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.
Highlights
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
According to the Chinese Infectious Diseases Law, clinicians must report to the Notifiable Disease Surveillance System (NDSS) when they identify any probable, clinical, or laboratory-confirmed case of scarlet fever within 24 h of diagnosis, and it ensures that the morbidity of scarlet fever is a relative real figure of the city
Description of disease and air pollution A total of 6316 cases of scarlet fever were notified in the study area over no air pollution and air pollution periods from 2014 to 2018
Summary
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. What happening with worsening air pollution at the same time is the increasing incidence of scarlet fever, which is a significant threat to the growing child population in Qingdao [19]. Qingdao, presented as the site, is appropriate to explore the association between air pollution and scarlet fever. We conducted a distributed lag non-linear time series analysis to quantify the association between them in a large population study in Qingdao, China during 2014– 2018, aiming at providing facility to developing strategies for preventing and reducing health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas
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