Abstract
Background: 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. Methods: 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. Results: We demonstrate our method using the transmission cycle of West Nile virus to create a simple transmission DAG that lacks a cycle. Conclusions: 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.