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斯里兰卡当前和预测登革热疫情动态的气候、病毒学和社会学驱动因素。

Climatological, virological and sociological drivers of current and projected dengue fever outbreak dynamics in Sri Lanka.

机构信息

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.

Princeton Environmental Institute, Princeton University, Princeton, NJ 08544, USA.

出版信息

J R Soc Interface. 2020 Jun;17(167):20200075. doi: 10.1098/rsif.2020.0075. Epub 2020 Jun 3.

Abstract

The largest ever Sri Lankan dengue outbreak of 2017 provides an opportunity for investigating the relative contributions of climatological, epidemiological and sociological drivers on the epidemic patterns of this clinically important vector-borne disease. To do so, we develop a climatologically driven disease transmission framework for dengue virus using spatially resolved temperature and precipitation data as well as the time-series susceptible-infected-recovered (SIR) model. From this framework, we first demonstrate that the distinct climatological patterns encountered across the island play an important role in establishing the typical yearly temporal dynamics of dengue, but alone are unable to account for the epidemic case numbers observed in Sri Lanka during 2017. Using a simplified two-strain SIR model, we demonstrate that the re-introduction of a dengue virus serotype that had been largely absent from the island in previous years may have played an important role in driving the epidemic, and provide a discussion of the possible roles for extreme weather events and human mobility patterns on the outbreak dynamics. Lastly, we provide estimates for the future burden of dengue across Sri Lanka using the Coupled Model Intercomparison Phase 5 climate projections. Critically, we demonstrate that climatological and serological factors can act synergistically to yield greater projected case numbers than would be expected from the presence of a single driver alone. Altogether, this work provides a holistic framework for teasing apart and analysing the various complex drivers of vector-borne disease outbreak dynamics.

摘要

2017 年斯里兰卡爆发了有史以来规模最大的登革热疫情,这为研究气候、流行病学和社会学驱动因素对这种具有重要临床意义的虫媒传染病流行模式的相对贡献提供了机会。为此,我们使用空间分辨的温度和降水数据以及时间序列易感-感染-恢复(SIR)模型,为登革热病毒开发了一个气候驱动的疾病传播框架。从这个框架中,我们首先证明了整个岛屿上不同的气候模式在建立登革热典型的年度时间动态方面起着重要作用,但仅凭气候因素本身无法解释 2017 年斯里兰卡观察到的疫情病例数量。使用简化的两株 SIR 模型,我们证明了一种在过去几年中在该岛上基本不存在的登革热病毒血清型的重新引入可能在推动疫情方面发挥了重要作用,并讨论了极端天气事件和人类流动模式对疫情动态的可能作用。最后,我们使用耦合模型比较计划第 5 阶段的气候预测来估计未来斯里兰卡的登革热负担。至关重要的是,我们证明气候和血清学因素可以协同作用,产生比单一驱动因素单独存在时预期的更多的预测病例数。总之,这项工作为剖析和分析虫媒传染病爆发动态的各种复杂驱动因素提供了一个整体框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cb3/7328388/65f22ec5c22c/rsif20200075-g1.jpg

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