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首页> 外文期刊>Philosophical Transactions of the Royal Society of London, Series B. Biological Sciences >Dose-response and transmission: the nexus between reservoir hosts, environment and recipient hosts
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Dose-response and transmission: the nexus between reservoir hosts, environment and recipient hosts

机译：剂量 - 响应和传输：库中的Nexus宿主，环境和收件人主机之间

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摘要

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.
机译：剂量是暴露之间的Nexus和确定病原体压力的所有上游过程，从而具有重要的疾病动态的重要因素。理解剂量和疾病之间的关系在溢出的背景下尤为重要，其中剂量反应中的非线性可以确定变速器的可能性。需要探索用于直接传输和群体病原体的剂量 - 响应模型，以及这些相互作用如何整合在宿主因子内，以考虑宿主敏感性和剂量依赖性拮抗作用。在这里，我们回顾了剂量 - 反应文献，并讨论了独特的作用剂量 - 响应模型必须在理解和预测溢出事件中发挥作用。我们对两种重要的动物园病原体（中东呼吸综合征冠状病毒和NIPAH病毒）进行了重新分析，以举例说明在具有小曝光实验数据集之间的适当模型之间区分潜在困难。我们还讨论了剂量响应模型之间强大选择所需的数据要求。然后，我们建议如何建模这些过程，以获得人畜共速传播结果的更现实的预测，并突出可能在病毒学和流行病学学科之间增加的协作可能产生的令人兴奋的机会。

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