首页> 美国卫生研究院文献>The American Journal of Tropical Medicine and Hygiene >Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia
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Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia

机译:使用哥伦比亚热带气候的当地天气和区域气候对登革热暴发的季节内和季节间自回归预测

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摘要

Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors—all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C—the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts.
机译:登革热的传播是由病毒,人类宿主和蚊媒之间复杂的相互作用导致的,所有这些相互作用都受到环境因素的影响。基于当地天气和区域气候参数的登革热发病率预测模型可以使疾病缓解工作受益。分析了2000年1月至2011年12月哥伦比亚卡利市城市环境的流行病学和气象数据的时间序列。登革热暴发通常发生在温暖干燥的时期,极端每日温度限制在18°C至32°C之间,蚊子生存和病毒传播的最佳范围。开发了两个基于环境的多元自回归预测模型,这些模型可在2周至6个月之前预测登革热暴发。这些模型有可能增强现有的登革热预警系统,最终支持病媒控制工作的时间和规模上的公共卫生决策。

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