Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China.
College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan Province, China.
PLoS One. 2021 Mar 3;16(3):e0247980. doi: 10.1371/journal.pone.0247980. eCollection 2021.
Japanese encephalitis (JE) is an acute infectious disease caused by the Japanese encephalitis virus (JEV) and is transmitted by mosquitoes. Meteorological conditions are known to play a pivotal role in the spread of JEV. In this study, a zero-inflated generalised additive model and a long short-term memory model were used to assess the relationship between the meteorological factors and population density of Culex tritaeniorhynchus as well as the incidence of JE and to predict the prevalence dynamics of JE, respectively. The incidence of JE in the previous month, the mean air temperature and the average of relative humidity had positive effects on the outbreak risk and intensity. Meanwhile, the density of all mosquito species in livestock sheds (DMSL) only affected the outbreak risk. Moreover, the region-specific prediction model of JE was developed in Chongqing by used the Long Short-Term Memory Neural Network. Our study contributes to a better understanding of the JE dynamics and helps the local government establish precise prevention and control measures.
日本脑炎（JE）是由日本脑炎病毒（JEV）引起的急性传染病，通过蚊子传播。气象条件被认为在 JEV 的传播中起着关键作用。在这项研究中，使用零膨胀广义加性模型和长短期记忆模型来评估气象因素与三带喙库蚊种群密度以及 JE 发病率之间的关系，并分别预测 JE 的流行动态。上月 JE 的发病率、平均气温和平均相对湿度对暴发风险和强度有积极影响。同时，牲畜棚内所有蚊子种类的密度（DMSL）仅影响暴发风险。此外，还通过长短期记忆神经网络在重庆开发了 JE 的区域特定预测模型。我们的研究有助于更好地了解 JE 的动态，并帮助地方政府制定精确的预防和控制措施。
