國家衛生研究院 NHRI:Item 3990099045/11630
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    題名: Prediction of annual dengue incidence by hydro-climatic extremes for southern Taiwan
    作者: Yuan, HY;Wen, TH;Kung, YH;Tsou, HH;Chen, CH;Chen, LW;Lin, PS
    貢獻者: National Mosquito-Borne Diseases Control Research Center;Institute of Population Health Sciences;National Institute of Infectious Diseases and Vaccinology
    摘要: Dengue is one of the most rapidly spreading mosquito-borne viral diseases in the world. An increase in the incidence of dengue is commonly thought to be a consequence of variability of weather conditions. Taiwan, which straddles the Tropic of Cancer, is an excellent place to study the relationship between weather conditions and dengue fever cases since the island forms an isolated geographic environment. Therefore, clarifying the association between extreme weather conditions and annual dengue incidence is one of important issues for epidemic early warning. In this paper, we develop a Poisson regression model with extreme weather parameters for prediction of annual dengue incidence. A leave-one-out method is used to evaluate the performance of predicting dengue incidence. Our results indicate that dengue transmission has a positive relationship with the minimum temperature predictors during the early summer while a negative relationship with all the maximum 24-h rainfall predictors during the early epidemic phase of dengue outbreaks. Our findings provide a better understanding of the relationships between extreme weather and annual trends in dengue cases in Taiwan and it could have important implications for dengue forecasts in surrounding areas with similar meteorological conditions.
    日期: 2019-02
    關聯: International Journal of Biometeorology. 2019 Feb;63(2):259-268.
    Link to: http://dx.doi.org/10.1007/s00484-018-01659-w
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0020-7128&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000459790300016
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85060766809
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