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基于分布滞后非线性模型探讨上海市诺如病毒感染性腹泻的发病与气象因素的关联
引用本文:周士夏,张海洋,王丽萍,刘玮,方立群,国家科技重大专项腹泻症候群监测团队.基于分布滞后非线性模型探讨上海市诺如病毒感染性腹泻的发病与气象因素的关联[J].中华疾病控制杂志,2021,25(10):1180.
作者姓名:周士夏  张海洋  王丽萍  刘玮  方立群  国家科技重大专项腹泻症候群监测团队
作者单位:1.230032 合肥,安徽医科大学公共卫生学院
基金项目:国家科技重大专项2018ZX10713001国家科技重大专项2018ZX10713002国家科技重大专项2018ZX10201001
摘    要:  目的  探讨上海市腹泻患者中诺如病毒感染与气象因素的关联,为诺如病毒感染性腹泻的防控提供科学依据。  方法  收集上海市2012―2019年腹泻病例与上海市各气象监测点逐日气象资料,利用分布滞后非线性模型(distributed lag non-linear model, DLNM)分析诺如病毒感染性腹泻的发病与气象因素的关联。  结果  在21 148名腹泻入院的就诊患者中,诺如病毒检出率为18.75%。其中45~<60岁人群的检出率最高(22.72%)。DLNM结果显示,相对于日平均气温18 ℃(P50),当日平均气温为-6 ℃时对诺如病毒感染的影响最大(RR=3.06, 95% CI: 1.49~6.30);日平均气温在滞后2 d时对诺如病毒感染产生最大影响(RR=1.15, 95% CI: 1.02~1.29)。相对于日降水量0 mm(P50),当日降水量195 mm时出现最大负效应(RR=0.31, 95% CI: 0.06~1.66)。  结论  上海市腹泻入院就诊患者的诺如病毒感染率较高,低温增加诺如病毒感染性腹泻发病风险,应根据诺如病毒流行特征针对性地开展防控工作。

关 键 词:诺如病毒    哨点监测    分布滞后非线性模型    腹泻
收稿时间:2021-03-02

Exploration of the association between meteorological factors and positive rate of norovirus infectious diarrhea based on the distributed lag non-linear model in Shanghai
Institution:1.School of Public Health, Anhui Medical University, Hefei 230032, China2.State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China3.Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China4.Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing 100191, China
Abstract:  Objective  To explore the association between norovirus among diarrheal patients and meteorological factors in Shanghai, and to provide a scientific basis for the prevention and control of norovirus infectious diarrhea.  Methods  We collected the data of diarrhea in Shanghai from 2012 to 2019 and the daily meteorological data of all meteorological monitoring points in Shanghai. A distributed lag non-linear model (DLNM) was constructed to analyze the relationship between norovirus infections diarrhea and meteorological factors.  Results  18.75% of the 21 148 diarrheal patients were found norovirus. Age group of 45~ < 60 years old patients were found with the highest positive percentage (22.72%). Compared with the daily average temperature of 18 ℃ (P50), the daily average temperature of -6 ℃ had the greatest impact on norovirus infection (RR=3.06, 95% CI: 1.49-6.30); the average daily temperature lagging by 2 days has a maximum impact on norovirus infection (RR=1.15, 95% CI: 1.02-1.29). Compared with the daily precipitation of 0mm (P50), the highest negative effect was associated with daily precipitation of 195 mm (RR=0.31, 95% CI: 0.06-1.66).  Conclusions  The rate of norovirus infection in patients in Shanghai is high, and low temperature increases the risk of norovirus infectious diarrhea. Targeted prevention and control work should be carried out according to the characteristics of norovirus epidemic.
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