Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada.
Centre de recherche en santé publique (CReSP), Université de Montréal and Centre intégré universitaire de santé et de services sociaux du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada.
Vector Borne Zoonotic Dis. 2023 Mar;23(3):129-135. doi: 10.1089/vbz.2022.0040. Epub 2023 Feb 27.
The life cycles of zoonotic and vector-borne diseases can be complex. This complexity makes it challenging to identify factors that confound the association between an exposure of interest and infection in one of the susceptible hosts. In epidemiology, directed acyclic graphs (DAGs) can be used to visualize the relationships between exposures and outcomes and also to identify which factors confound the association between exposure and the outcome of interest. However, DAGs can only be used in situations where no cycle exists in the causal relationships being represented. This is problematic for infectious agents that cycle between hosts. Zoonoses and vector-borne diseases pose additional challenges with DAG construction since multiple required or optional hosts of different species may be part of the cycle. We review the existing examples of DAGs created for nonzoonotic infectious agents. We then demonstrate how to cut the transmission cycle to create DAGs where infection of a specific host species is the outcome of interest. We adapt our method to create DAGs using examples of transmission and host characteristics common to many zoonotic and vector-borne infectious agents. We demonstrate our method using the transmission cycle of West Nile virus to create a simple transmission DAG that lacks a cycle. Using our work, investigators can create DAGs to help identify confounders of the relationships between modifiable risk factors and infection. Ultimately, a better understanding and control of confounding in measuring the impact of such risk factors can be used to inform health policy, guide public health and animal health interventions, and uncover gaps needing further research attention.
人畜共患和媒介传播疾病的生命周期可能很复杂。这种复杂性使得确定混淆感兴趣的暴露与其中一个易感宿主感染之间关联的因素变得具有挑战性。在流行病学中，可以使用有向无环图（DAG）来可视化暴露与结局之间的关系，也可以确定哪些因素混淆了暴露与感兴趣结局之间的关联。然而，DAG 只能用于表示因果关系中不存在循环的情况。对于在宿主之间循环的传染性病原体来说，这是一个问题。人畜共患和媒介传播疾病在 DAG 构建方面带来了额外的挑战，因为不同物种的多个必需或可选宿主可能是循环的一部分。我们回顾了为非人畜共患传染病病原体创建的现有 DAG 示例。然后，我们展示了如何切断传播循环，以创建感染特定宿主物种为感兴趣结局的 DAG。我们采用我们的方法来创建使用许多人畜共患和媒介传播传染病常见的传播和宿主特征的 DAG。我们使用西尼罗河病毒的传播周期来创建一个简单的传播 DAG 来演示我们的方法，该 DAG 没有循环。使用我们的工作，研究人员可以创建 DAG 来帮助确定可改变的危险因素与感染之间关系的混杂因素。最终，可以更好地理解和控制混杂因素，从而衡量这些危险因素的影响，为卫生政策提供信息，指导公共卫生和动物卫生干预措施，并揭示需要进一步研究关注的差距。
