Environmental Futures Research Institute, Griffith University, Kessels Road, Nathan, Queensland 4111, Australia.
Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
Philos Trans R Soc Lond B Biol Sci. 2019 Sep 30;374(1782):20190016. doi: 10.1098/rstb.2019.0016. Epub 2019 Aug 12.
Dose is the nexus between exposure and all upstream processes that determine pathogen pressure, and is thereby an important element underlying disease dynamics. Understanding the relationship between dose and disease is particularly important in the context of spillover, where nonlinearities in the dose-response could determine the likelihood of transmission. There is a need to explore dose-response models for directly transmitted and zoonotic pathogens, and how these interactions integrate within-host factors to consider, for example, heterogeneity in host susceptibility and dose-dependent antagonism. Here, we review the dose-response literature and discuss the unique role dose-response models have to play in understanding and predicting spillover events. We present a re-analysis of dose-response experiments for two important zoonotic pathogens (Middle East respiratory syndrome coronavirus and Nipah virus), to exemplify potential difficulties in differentiating between appropriate models with small exposure experiment datasets. We also discuss the data requirements needed for robust selection between dose-response models. We then suggest how these processes could be modelled to gain more realistic predictions of zoonotic transmission outcomes and highlight the exciting opportunities that could arise with increased collaboration between the virology and epidemiology disciplines. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
剂量是暴露与所有上游过程的交汇点，这些过程决定了病原体压力，因此是疾病动态的重要基础。在溢出的背景下，理解剂量与疾病之间的关系尤为重要，因为剂量反应中的非线性可能决定传播的可能性。需要探索直接传播和人畜共患病病原体的剂量反应模型，以及这些相互作用如何整合宿主因素，例如宿主易感性和剂量依赖性拮抗作用的异质性。在这里，我们回顾了剂量反应文献，并讨论了剂量反应模型在理解和预测溢出事件方面的独特作用。我们重新分析了两种重要的人畜共患病病原体（中东呼吸综合征冠状病毒和尼帕病毒）的剂量反应实验，以说明在使用小暴露实验数据集区分合适的模型时可能存在的困难。我们还讨论了在剂量反应模型之间进行稳健选择所需的数据要求。然后，我们建议如何对这些过程进行建模，以更现实地预测人畜共患病传播结果，并强调随着病毒学和流行病学学科之间增加合作，可能会出现令人兴奋的机会。本文是主题为“理解病原体溢出的动态和综合方法”的特刊的一部分。
