摘要
目的研究2008-2019年北京市法定传染病种类数、感染人数、死亡人数在不同报道次序下与PM2.5浓度的交互效应及其响应特征,为城市传染病的控制和预防提供科学依据。方法通过北京市疾控中心获取近十余年共计583周的法定传染病报告数,耦合对应的即刻-短期-中期-长期PM2.5平均浓度,分别采用Pearson相关性分析、描述性统计及贝叶斯回归模型对二者间的交互效应和响应特征进行分析。结果法定传染病种类数与PM2.5在各个时间尺度上相关性差异有统计学意义(r_(0 d)=-0.26,r_(7 d)=-0.23,r_(15 d)=-0.26,r_(30 d)=-0.34,r_(60 d)=-0.43,P<0.05),且时间尺度越大,相关性越强;各类法定传染病病发时对应的PM2.5具有较大的浓度范围,存在月份间差异,且冬季特征明显,并且相应PM2.5浓度变化相对较小;在相对较长的一段期间内传染病累积感染数、累积致死数与其报道次序不存在严格对应关系;法定传染病患病数量随PM2.5浓度升高会随不同报道次序而存在不同的变化趋势(P<0.01)。结论北京市PM2.5浓度升高可能会增加法定传染病的发病率,研究期内传染病累积感染数与累积致死数与其报道次序不存在严格对应关系,不同报道次序的各传染病均需要引起足够重视。
Objective The current analysis was set to enquire the types of legal infectious diseases in Beijing,the number of infected persons and the death in different order of reporting as well as the interaction effect of PM2.5 concentration and its response characteristics from 2018 to 2019 and provide the basis for the control and prevention of urban infectious diseases.Methods The number of notifiable infectious disease reports for a total of 583 weeks in the past decade was obtained by the Beijing CDC.The mean concentrations of PM2.5 corresponding to the coupling of immediate-short-medium–long term were respectively analyzed by Pearson correlation analysis,descriptive statistics,and Bayesian regression model for the interaction effect and response characteristics between them.Results The correlation between the number of notifiable infectious diseases and PM2.5 was statistically significant on each time scale,with a larger time scale along with a stronger correlation(r_(0 d)=-0.26,r_(7 d)=-0.23,r_(15 d)=-0.26,r_(30 d)=-0.34,r_(60 d)=-0.43,P<0.05).The PM2.5 corresponding to each type of notifiable infectious disease showed a large concentration range,with monthly differences,and it was significant in winter,and the change in the corresponding PM2.5 concentration was relatively small.There was no strict correspondence between the cumulative number of infections and the cumulative number of deaths and the reporting order in a relatively long time.The prevalence of notifiable infectious diseases tended to change with the increase of PM2.5 concentration in different reporting orders(P<0.01).Conclusion Increasing PM2.5 concentration in Beijing may increase the incidence of notifiable infectious diseases.During the research period,the strict correspondence among the cumulative number of infections and the cumulative number of death and the reporting order was not detected,and all infectious diseases in different reporting orders required adequate attention.
作者
王飞
王新雨
付海霞
王雪珂
姜雅琴
赵颖
WANG Fei;WANG Xin-yu;FU Hai-xia;WANG Xue-ke;JIANG Ya-qin;ZHAO Ying(Sports Science Institute,Shanxi University,Taiyuan030006,China;不详)
出处
《医学动物防制》
2021年第3期210-215,共6页
Journal of Medical Pest Control
基金
山西省重点研发项目(201903D321069)
山西省基础研究项目(201801D121261)
山西省2020年度研究生教育创新计划项目(2020SY087)。
关键词
PM2.5
法定传染病
相关性分析
贝叶斯回归模型
边际效应
PM2.5
Notifiable infectious diseases
Correlation analysis
Bayesian regression model
Marginal effect
