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水生病原体入侵的空间明确条件。

Spatially explicit conditions for waterborne pathogen invasion.

机构信息

Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milan, Italy.

出版信息

Am Nat. 2013 Sep;182(3):328-46. doi: 10.1086/671258. Epub 2013 Jul 18.

Abstract

Waterborne pathogens cause many possibly lethal human diseases. We derive the condition for pathogen invasion and subsequent disease outbreak in a territory with specific, space-inhomogeneous characteristics (hydrological, ecological, demographic, and epidemiological). The criterion relies on a spatially explicit model accounting for the density of susceptible and infected individuals and the pathogen concentration in a network of communities linked by human mobility and the water system. Pathogen invasion requires that a dimensionless parameter, the dominant eigenvalue of a generalized reproductive matrix J0, be larger than unity. Conditions for invasion are studied while crucial parameters (population density distribution, contact and water contamination rates, pathogen growth rates) and the characteristics of the networks (connectivity, directional transport, water retention times, mobility patterns) are varied. We analyze both simple, prototypical test cases and realistic landscapes, in which optimal channel networks mimic the water systems and gravitational models describe human mobility. Also, we show that the dominant eigenvector of J0 effectively portrays the geography of epidemic outbreaks, that is, the areas of the studied territory that will be initially affected by an epidemic. This is important for planning an efficient spatial allocation of interventions (e.g., improving sanitation and providing emergency aid and medicines).

摘要

水传播病原体可导致许多可能致命的人类疾病。我们在具有特定、空间不均匀特征(水文学、生态学、人口统计学和流行病学)的区域中得出病原体入侵和随后疾病爆发的条件。该标准依赖于一个空间显式模型,该模型考虑了易感个体和感染个体的密度以及由人类流动和水系连接的社区网络中的病原体浓度。病原体入侵需要无量纲参数,即广义繁殖矩阵 J0 的主特征值大于 1。在研究入侵条件的同时,我们还研究了关键参数(人口密度分布、接触和水污染率、病原体增长率)和网络特征(连通性、定向传输、水滞留时间、流动模式)的变化。我们分析了简单的原型测试案例和现实景观,其中最优通道网络模拟了水系,而重力模型描述了人类流动。此外,我们还表明,J0 的主特征向量有效地描绘了疫情爆发的地理情况,即受疫情影响的研究区域的初始区域。这对于规划干预措施的有效空间分配(例如,改善卫生条件以及提供紧急援助和药品)非常重要。

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