Disease outbreak thresholds emerge from interactions between movement behavior, landscape structure, and epidemiology
Disease outbreak thresholds emerge from interactions between movement behavior, landscape structure, and epidemiology
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DOI：
10.1073/pnas.1801383115
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发表时间：
2018-07-10
影响因子：
11.1
通讯作者：
Craft, Meggan E.
中科院分区：
文献类型：
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作者：
White, Lauren A.;Forester, James D.;Craft, Meggan E.
关于空间异质性是促进还是阻碍病原体持久性，疾病模型提供了相互矛盾的证据。此外，关于动物运动行为如何与景观中资源的空间组织(例如，集群、随机、统一)相互作用以影响传染病动态的理论研究有限。重要的是，资源的空间异质性有时会导致非线性或违反直觉的结果，这取决于寄主和病原体系统。显然有必要开发一个通用的理论框架，可以用来为特定的宿主-病原体系统创建可测试的预测。在这里，我们开发了一个基于个体的模型，结合运动生态学的方法来研究宿主运动行为如何与景观异质性(以不同水平的资源丰度和聚集性的形式)相互作用来影响病原菌的动态。对于大多数参数空间，我们的结果支持反直觉的观点，即碎片促进了病原菌的持久性，但这一发现在很大程度上取决于宿主的感知范围、同种密度和回收率。对于同种密度高、恢复速度较慢、感知范围较大的模拟，出现了更复杂的疾病动力学，最分散的景观不一定最有利于爆发或病原体持久性。这些结果表明，景观结构、个体运动行为和病原体传播之间的相互作用对于预测和了解疾病动态具有重要意义。
Disease models have provided conflicting evidence as to whether spatial heterogeneity promotes or impedes pathogen persistence. Moreover, there has been limited theoretical investigation into how animal movement behavior interacts with the spatial organization of resources (e.g., clustered, random, uniform) across a landscape to affect infectious disease dynamics. Importantly, spatial heterogeneity of resources can sometimes lead to nonlinear or counterintuitive outcomes depending on the host and pathogen system. There is a clear need to develop a general theoretical framework that could be used to create testable predictions for specific host-pathogen systems. Here, we develop an individual-based model integrated with movement ecology approaches to investigate how host movement behaviors interact with landscape heterogeneity (in the form of various levels of resource abundance and clustering) to affect pathogen dynamics. For most of the parameter space, our results support the counterintuitive idea that fragmentation promotes pathogen persistence, but this finding was largely dependent on perceptual range of the host, conspecific density, and recovery rate. For simulations with high conspecific density, slower recovery rates, and larger perceptual ranges, more complex disease dynamics emerged, and the most fragmented landscapes were not necessarily the most conducive to outbreaks or pathogen persistence. These results point to the importance of interactions between landscape structure, individual movement behavior, and pathogen transmission for predicting and understanding disease dynamics.