Literature DB >> 33657174

Association between meteorological factors and the prevalence dynamics of Japanese encephalitis.

Taotian Tu1, Keqiang Xu2, Lei Xu3,4, Yuan Gao3, Ying Zhou1, Yaming He1, Yang Liu1, Qiyong Liu3, Hengqing Ji1, Wenge Tang1.   

Abstract

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.

Entities:  

Year:  2021        PMID: 33657174     DOI: 10.1371/journal.pone.0247980

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  4 in total

1.  The epidemiology and disease burden of children hospitalized for viral infections within the family Flaviviridae in China: A national cross-sectional study.

Authors:  Ran Wang; Xinyu Wang; Linlin Zhang; Guoshuang Feng; Mengjia Liu; Yueping Zeng; Zhengde Xie
Journal:  PLoS Negl Trop Dis       Date:  2022-07-05

2.  Mechanistic insights into the Japanese encephalitis virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica.

Authors:  Vivek Dhar Dwivedi; Ankita Singh; Sherif Aly El-Kafraway; Thamir A Alandijany; Arwa A Faizo; Leena Hussein Bajrai; Mohammad Amjad Kamal; Esam Ibraheem Azhar
Journal:  Sci Rep       Date:  2021-09-13       Impact factor: 4.379

3.  Improving Dengue Forecasts by Using Geospatial Big Data Analysis in Google Earth Engine and the Historical Dengue Information-Aided Long Short Term Memory Modeling.

Authors:  Zhichao Li; Helen Gurgel; Lei Xu; Linsheng Yang; Jinwei Dong
Journal:  Biology (Basel)       Date:  2022-01-21

4.  A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950.

Authors:  Shin-Yueh Liu; Tsair-Wei Chien; Ting-Ya Yang; Yu-Tsen Yeh; Willy Chou; Julie Chi Chow
Journal:  Int J Environ Res Public Health       Date:  2021-03-19       Impact factor: 3.390

  4 in total

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