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Epidemiological characteristics and transmission dynamics of epidemic Japanese encephalitis in China: A modeling study

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机构: [1]Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China [2]National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), Shanghai, China [3]National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China [4]Department of Pharmacy, Cancer Hospital of Shantou University Medical College, Shantou 515041, China [5]Department of Clinical Medicine, Shantou University Medical College, Shantou 515041, China [6]Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States of America [7]School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China [8]Xinjiang Key Laboratory of Vector-borne Infectious Diseases, Urumqi, Xinjiang 830002, China [9]Peking University Center for Public Health and Epidemic Preparedness and Response, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 38 Xueyuan Road, Beijing 100191, China
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关键词: Bayesian inference Japanese encephalitis Mosquito-borne disease Population movement Transmission dynamics

摘要:
In recent decades, China has experienced successive epidemics of seasonal Japanese encephalitis (JE), with the Japanese encephalitis virus (JEV) particularly spreading continuously in rural and suburban areas.Nationwide data on 9061 JE cases, mosquito abundance from 89 surveillance sites, and population movement between 337 cities during 2013-19 were obtained. Seasonal multivariate linear regression models including time trends and reconciliation terms representing annual and semiannual cycles were fitted to the weekly time series of JE cases, and the amplitude and peak time of the cycles were estimated. A metapopulation network model of inter-city population mobility coupled with an iterative Bayesian inference algorithm was established to simulate the epidemic dynamics of JEV and estimate the time-varying transmission parameters.The timing of the annual peak of JEV epidemics varied with latitude (p-value < 0.05), mainly characterized by earlier in southern cities and later in northern cities. There was no significant difference in the annual amplitude fluctuations of JEV epidemics in different latitudes (p-value > 0.05). Regions with higher values of effective reproduction number Reff were mainly concentrated in central China, including Sichuan, Chongqing and Shaanxi provinces, with the annual activity peak typically occurring around August. Infections caused by population mobility mainly occurred in hub cities with high connectivity and radiated to surrounding cities.Findings from this nationwide study can help enhance situational awareness of the spread of JE and inform appropriate intervention strategies to advance the goal of JE elimination.Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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出版当年[2025]版:
大类 | 2 区 医学
小类 | 1 区 传染病学
最新[2025]版:
大类 | 2 区 医学
小类 | 1 区 传染病学
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第一作者机构: [1]Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
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通讯作者:
通讯机构: [3]National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China [7]School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China [8]Xinjiang Key Laboratory of Vector-borne Infectious Diseases, Urumqi, Xinjiang 830002, China [*1]National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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