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Spatiotemporal patterns and climatic drivers of severe dengue in Thailand

机译:泰国严重登革热的时空格局和气候驱动因素

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摘要

Objectives: The burden of dengue fever in Thailand is considerable, yet there are few large-scale studies exploring the drivers of transmission. This study aimed to investigate the spatiotemporal patterns and climatic drivers of severe dengue in Thailand.Methods: Geographic Information System (GIS) techniques and spatial cluster analysis were used to visualize the spatial distribution and detect high-risk clusters of severe dengue in 76 provinces of Thailand from January 1999 to December 2014. The seasonal patterns of severe dengue cases in different provinces were identified. A two-stage modelling approach combining a generalized linear model with a distributed lag non-linear model was used to quantify the effects of monthly mean temperature and relative humidity on the occurrence of severe dengue cases in 51 provinces of Thailand.Results: Significant severe dengue clustering was detected, especially during epidemic years, and the location of these clusters showed substantial inter-annual variation. Severe dengue cases in Northern and Northeastern Thailand peaked in June to August and this pattern was stable across the study period, whereas the seasonality of severe dengue cases in other regions (especially Central Thailand) was less predictable. The risk of the occurrence of severe dengue cases increased with an increase in mean temperature in Northeastern Thailand, Central Thailand, and Southern Thailand, with peaks occurring between 24 degrees C to 30 degrees C in Northeastern Thailand and 27 degrees C to 29 degrees C in Southern Thailand West Coast, respectively. Relative humidity significantly affected the occurrence of severe dengue cases in Northeastern and Central Thailand, with optimal ranges observed for each region.Conclusions: Our findings substantiate the potential for developing climate-based dengue early warning systems for Thailand, and have implications for informing pre-emptive vector control. (C) 2018 Elsevier B.V. All rights reserved.
机译:目标:泰国的登革热负担相当可观,但很少有大规模研究探索传播途径。方法:采用地理信息系统(GIS)技术和空间聚类分析方法,对泰国76个省的重度登革热的空间分布进行可视化,并检测高危类群,以研究泰国重度登革热的时空格局和气候驱动因素。泰国从1999年1月至2014年12月。确定了不同省份的严重登革热病例的季节性模式。采用两阶段建模方法,将广义线性模型与分布式滞后非线性模型相结合,以量化每月平均温度和相对湿度对泰国51个省的严重登革热病例发生的影响。发现了聚类,尤其是在流行年份,并且这些聚类的位置显示出较大的年际变化。泰国北部和东北部的严重登革热病例在6月至8月达到顶峰,并且在整个研究期间这种模式是稳定的,而其他地区(尤其是泰国中部)的严重登革热病例的季节性则难以预测。随着泰国东北部,泰国中部和泰国南部平均温度的升高,发生严重登革热病例的风险也随之增加,泰国东北部的最高温度在24摄氏度至30摄氏度之间,泰国的最高温度在27摄氏度至29摄氏度之间。泰国南部西海岸分别。相对湿度显着影响了泰国东北部和中部地区严重登革热病例的发生,每个区域的最佳范围都得到了观察。主动矢量控制。 (C)2018 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《The Science of the Total Environment》 |2019年第15期|889-901|共13页
  • 作者单位

    Queensland Univ Technol, Sch Publ Hlth & Social Work, Victoria Pk Rd, Brisbane, Qld 4059, Australia|Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld, Australia;

    Queensland Univ Technol, Sch Publ Hlth & Social Work, Victoria Pk Rd, Brisbane, Qld 4059, Australia|Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld, Australia;

    London Sch Hyg & Trop Med, Dept Dis Control, London, England;

    QIMR Berghofer Med Res Inst, Mosquito Control Lab, Brisbane, Qld, Australia;

    Sun Yat Sen Univ, Sch Publ Hlth, Guangzhou, Guangdong, Peoples R China;

    Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld, Australia|Queensland Univ Technol, Sch Biomed Sci, Brisbane, Qld, Australia;

    Chinese Ctr Dis Control & Prevent, Div Infect Dis, Key Lab Surveillance & Early Warning Infect Dis, Beijing, Peoples R China;

    Univ Queensland, Sch Publ Hlth, Brisbane, Qld, Australia;

    Queensland Univ Technol, Sch Publ Hlth & Social Work, Victoria Pk Rd, Brisbane, Qld 4059, Australia|Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Relative humidity; Severe dengue; Temperature; Thailand;

    机译:相对湿度;严重登革热;温度;泰国;

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