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季节性人类流动性和埃及伊蚊栖息地适宜性对哥伦比亚寨卡病毒疫情严重程度的影响。

The effects of seasonal human mobility and Aedes aegypti habitat suitability on Zika virus epidemic severity in Colombia.

机构信息

College of Natural Sciences, Forestry, and Agriculture, University of Maine, Orono, Maine, United States of America.

School of Integrative Biology, University of Illinois, Urbana-Champaign, Illinois, United States of America.

出版信息

PLoS Negl Trop Dis. 2024 Nov 6;18(11):e0012571. doi: 10.1371/journal.pntd.0012571. eCollection 2024 Nov.

Abstract

The Zika virus epidemic of 2015-16, which caused over 1 million confirmed or suspected human cases in the Caribbean and Latin America, was driven by a combination of movement of infected humans and availability of suitable habitat for mosquito species that are key disease vectors. Both human mobility and mosquito vector abundances vary seasonally, and the goal of our research was to analyze the interacting effects of disease vector densities and human movement across metapopulations on disease transmission intensity and the probability of super-spreader events. Our research uses the novel approach of combining geographical modeling of mosquito presence with network modeling of human mobility to offer a comprehensive simulation environment for Zika virus epidemics that considers a substantial number of spatial and temporal factors compared to the literature. Specifically, we tested the hypotheses that 1) regions with the highest probability of mosquito presence will have more super-spreader events during dry months, when mosquitoes are predicted to be more abundant, 2) regions reliant on tourism industries will have more super-spreader events during wet months, when they are more likely to contribute to network-level pathogen spread due to increased travel. We used the case study of Colombia, a country with a population of about 50 million people, with an annual calendar that can be partitioned into overlapping cycles of wet and dry seasons and peak tourism and off tourism seasons that drive distinct cyclical patterns of mosquito abundance and human movement. Our results show that whether the first infected human was introduced to the network during the wet versus dry season and during the tourism versus off tourism season profoundly affects the severity and trajectory of the epidemic. For example, Zika virus was first detected in Colombia in October of 2015. Had it originated in January, a dry season month with high rates of tourism, it likely could have infected up to 60% more individuals and up to 40% more super-spreader events may have occurred. In addition, popular tourism destinations such as Barranquilla and Cartagena have the highest risk of super-spreader events during the winter, whereas densely populated areas such as Medellín and Bogotá are at higher risk of sustained transmission during dry months in the summer. Our research demonstrates that public health planning and response to vector-borne disease outbreaks requires a thorough understanding of how vector and host patterns vary due to seasonality in environmental conditions and human mobility dynamics. This research also has strong implications for tourism policy and the potential response strategies in case of an emergent epidemic.

摘要

2015-16 年的寨卡病毒疫情在加勒比和拉丁美洲造成了超过 100 万例确诊或疑似病例,这是由感染人类的流动和适合蚊子传播疾病的关键栖息地的存在共同驱动的。人类流动和蚊子媒介丰度都具有季节性,我们研究的目标是分析疾病媒介密度和人口流动在复合种群中的相互作用效应对疾病传播强度和超级传播者事件发生概率的影响。我们的研究采用了将蚊子存在的地理建模与人类流动的网络建模相结合的新方法,为寨卡病毒疫情提供了一个全面的模拟环境,与文献相比,考虑了大量的时空因素。具体来说,我们检验了以下假设:1)蚊子存在概率最高的地区在蚊子可能更丰富的旱季将有更多的超级传播者事件,2)依赖旅游业的地区在雨季将有更多的超级传播者事件,因为由于旅行增加,它们更有可能导致网络级别的病原体传播。我们使用哥伦比亚的案例研究,该国人口约为 5000 万人,其日历可以划分为重叠的旱季和雨季周期,以及旅游旺季和淡季,这些周期驱动着蚊子丰度和人类流动的明显周期性模式。我们的研究结果表明,第一个被感染的人是在雨季还是旱季,以及在旅游旺季还是淡季进入网络,这对疫情的严重程度和轨迹有着深远的影响。例如,寨卡病毒于 2015 年 10 月在哥伦比亚首次检测到。如果它起源于 1 月,即旱季且旅游业发达的月份,那么它可能会感染多达 60%的人,并且可能会发生多达 40%的超级传播者事件。此外,像巴兰基亚和卡塔赫纳这样的热门旅游目的地在冬季发生超级传播者事件的风险最高,而像麦德林和波哥大这样人口稠密的地区在夏季旱季发生持续传播的风险更高。我们的研究表明,对媒介传播疾病爆发的公共卫生规划和应对需要深入了解由于环境条件和人类流动动态的季节性变化,媒介和宿主模式如何变化。这项研究对旅游政策和紧急疫情爆发时的潜在应对策略也具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/139d/11540183/ca70420cdc3d/pntd.0012571.g001.jpg

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