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洪水与虫媒病毒病:预测澳大利亚东南部内陆地区的罗斯河病毒病疫情

Flooding and Arboviral Disease: Predicting Ross River Virus Disease Outbreaks Across Inland Regions of South-Eastern Australia.

机构信息

School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, O Block, Kelvin Grove, Queensland, Australia.

出版信息

J Med Entomol. 2020 Jan 9;57(1):241-251. doi: 10.1093/jme/tjz120.

Abstract

Flood frequency is expected to increase across the globe with climate change. Understanding the relationship between flooding and arboviral disease can reduce disease risk and associated costs. South-eastern Australia is dominated by the flood-prone Murray-Darling River system where the incidence of Australia's most common arboviral disease, Ross River virus (RRV), is high. This study aimed to determine the relationship between riverine flooding and RRV disease outbreaks in inland south-eastern Australia, specifically New South Wales (NSW). Each study month from 1991 to 2013, for each of 37 local government areas (LGAs) was assigned 'outbreak/non-outbreak' status based on long-term trimmed-average age-standardized RRV notification rates and 'flood/non-flood' status based on riverine overflow. LGAs were grouped into eight climate zones with the relationship between flood and RRV outbreak modeled using generalized estimating equations. Modeling adjusted for rainfall in the previous 1-3 mo. Spring-summer flooding increased the odds of summer RRV outbreaks in three climate zones before and after adjusting for rainfall 1, 2, and 3 mo prior to the outbreak. Flooding at any time of the year was not predictive of RRV outbreaks in the remaining five climate zones. Predicting RRV disease outbreaks with flood events can assist with more targeted mosquito spraying programs, thereby reducing disease transmission and mosquito resistance.

摘要

随着气候变化,预计全球洪水频率将会增加。了解洪水与虫媒病毒病之间的关系,可以降低疾病风险和相关成本。澳大利亚东南部受洪水多发的墨累-达令河系统控制,该地区是澳大利亚最常见的虫媒病毒病——罗斯河病毒(RRV)高发地区。本研究旨在确定澳大利亚东南部内陆(新南威尔士州)洪水与 RRV 疾病爆发之间的关系。1991 年至 2013 年,每个研究月都根据长期修剪平均年龄标准化的 RRV 通知率,将 37 个地方政府区域(LGA)中的每一个分配为“爆发/非爆发”状态,并根据河流水位溢出将其分为“洪水/非洪水”状态。LGA 分为八个气候区,使用广义估计方程对洪水与 RRV 爆发之间的关系进行建模。模型调整了前 1-3 个月的降雨量。在调整了前 1、2 和 3 个月的降雨后,春夏季洪水增加了三个气候区夏季 RRV 爆发的可能性。在其余五个气候区,任何时候的洪水都不能预测 RRV 爆发。用洪水事件预测 RRV 疾病爆发可以帮助更有针对性地进行蚊子喷洒计划,从而减少疾病传播和蚊子的抗药性。

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