Ng Wee Hao, Myers Christopher R, McArt Scott H, Ellner Stephen P
Department of Entomology, Cornell University, Ithaca, New York, USA.
Center for Advanced Computing & Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, New York, USA.
Ecol Lett. 2022 Feb;25(2):453-465. doi: 10.1111/ele.13932. Epub 2021 Dec 8.
Pathogen transport by biotic or abiotic processes (e.g. mechanical vectors, wind, rain) can increase disease transmission by creating more opportunities for host exposure. But transport without replication has an inherent trade-off, that creating new venues for exposure decreases the average pathogen abundance at each venue. The host dose-response relationship is therefore required to correctly assess infection risk. We model and analyse two examples-biotic mechanical vectors in plant-pollinator networks, and abiotic-facilitated long-distance pathogen dispersal-to illustrate how oversimplifying the dose-response relationship can lead to incorrect epidemiological predictions. When the minimum infective dose is high, mechanical vectors amplify disease transmission less than suggested by simple compartment models, and may even dilute transmission. When long-distance dispersal leads to infrequent large exposures, models that assume a linear force of infection can substantially under-predict the speed of epidemic spread. Our work highlights an important general interplay between dose-response relationships and pathogen transport.
通过生物或非生物过程(如机械传播媒介、风、雨)进行的病原体传播,会通过为宿主接触创造更多机会来增加疾病传播。但无复制的传播存在内在权衡,即创造新的接触场所会降低每个场所的病原体平均丰度。因此,需要宿主剂量反应关系来正确评估感染风险。我们对两个例子进行建模和分析——植物-传粉者网络中的生物机械传播媒介,以及非生物促进的远距离病原体传播——以说明过度简化剂量反应关系如何导致错误的流行病学预测。当最小感染剂量较高时,机械传播媒介对疾病传播的放大作用小于简单的 compartments 模型所表明的,甚至可能稀释传播。当远距离传播导致不频繁但大规模的接触时,假设感染力呈线性的模型可能会大幅低估疫情传播速度。我们的工作突出了剂量反应关系与病原体传播之间重要的普遍相互作用。