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异质种群模型中用于疫情控制的随机和定向干预措施。

Random and targeted interventions for epidemic control in metapopulation models.

作者信息

Tanaka Gouhei, Urabe Chiyori, Aihara Kazuyuki

机构信息

1] Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan [2] Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan.

Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan.

出版信息

Sci Rep. 2014 Jul 16;4:5522. doi: 10.1038/srep05522.

Abstract

In general, different countries and communities respond to epidemics in accordance with their own control plans and protocols. However, owing to global human migration and mobility, strategic planning for epidemic control measures through the collaboration of relevant public health administrations is gaining importance for mitigating and containing large-scale epidemics. Here, we present a framework to evaluate the effectiveness of random (non-strategic) and targeted (strategic) epidemic interventions for spatially separated patches in metapopulation models. For a random intervention, we analytically derive the critical fraction of patches that receive epidemic interventions, above which epidemics are successfully contained. The analysis shows that the heterogeneity of patch connectivity makes it difficult to contain epidemics under the random intervention. We demonstrate that, particularly in such heterogeneously connected networks, targeted interventions are considerably effective compared to the random intervention. Our framework is useful for identifying the target areas where epidemic control measures should be focused.

摘要

一般来说,不同国家和社区会根据各自的控制计划和方案应对疫情。然而,由于全球人口迁移和流动,通过相关公共卫生管理部门的合作进行疫情控制措施的战略规划对于减轻和遏制大规模疫情变得愈发重要。在此,我们提出一个框架,用于评估在集合种群模型中针对空间分离斑块的随机(非战略)和针对性(战略)疫情干预措施的有效性。对于随机干预,我们通过分析得出接受疫情干预的斑块的临界比例,超过该比例疫情就能成功得到控制。分析表明,斑块连通性的异质性使得在随机干预下难以控制疫情。我们证明,特别是在这种连接性异质的网络中,与随机干预相比,针对性干预相当有效。我们的框架有助于确定应重点实施疫情控制措施的目标区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6974/4099978/22dcdd02fe4e/srep05522-f1.jpg

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