标题:Climate-driven variation in mosquito density predicts the spatiotemporal dynamics of dengue
作者:Li, Ruiyun; Xu, Lei; Bjornstad, Ottar N.; Liu, Keke; Song, Tie; Chen, Aifang; Xu, Bing; Liu, Qiyong; Stenseth, Nils C.
作者机构:[Li, Ruiyun; Xu, Lei; Stenseth, Nils C.] Univ Oslo, Dept Biosci, Ctr Ecol & Evolutionary Synth, N-0316 Oslo, Norway.; [Xu, Lei; Liu, Keke; Liu, Qiyo 更多
通讯作者:Stenseth, NC;Liu, QY;Liu, QY;Xu, B;Stenseth, NC
通讯作者地址:[Stenseth, NC]Univ Oslo, Dept Biosci, Ctr Ecol & Evolutionary Synth, N-0316 Oslo, Norway;[Liu, QY]Chinese Ctr Dis Control & Prevent, Natl Inst Communi 更多
来源:PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
出版年:2019
卷:116
期:9
页码:3624-3629
DOI:10.1073/pnas.1806094116
关键词:dengue fever; climate variation; mosquito density; integrated modeling; approach
摘要:Dengue is a climate-sensitive mosquito-borne disease with increasing geographic extent and human incidence. Although the climate-epidemic association and outbreak risks have been assessed using both statistical and mathematical models, local mosquito population dynamics have not been incorporated in a unified predictive framework. Here, we use mosquito surveillance data from 2005 to 2015 in China to integrate a generalized additive model of mosquito dynamics with a susceptible-infectedrecovered (SIR) compartmental model of viral transmission to establish a predictive model linking climate and seasonal dengue risk. The findings illustrate that spatiotemporal dynamics of dengue are predictable from the local vector dynamics, which in turn, can be predicted by climate conditions. On the basis of the similar epidemiology and transmission cycles, we believe that this integrated approach and the finer mosquito surveillance data provide a framework that can be extended to predict outbreak risk of other mosquito-borne diseases as well as project dengue risk maps for future climate scenarios.
收录类别:SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062041979&doi=10.1073%2fpnas.1806094116&partnerID=40&md5=f45dc5a3eb12516931b7899e9a4c9a5c
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