Exposure and susceptibility: The Twin Pillars of infection

Exposure and susceptibility underlie every organism's infection status, and an untold diversity of factors can drive variation in both. Often, both exposure and susceptibility change in response to a given factor, and they can interact, such that their relative contributions to observed disease dynamics are obscured. These independent and interlinked changes often complicate empirical inference in disease ecology and ecoimmunology. Although many disease ecology studies address this problem, it is often implicit rather than explicit and requires a specific set of tools to tackle. Moreover, as yet, there is no established conceptual framework for disentangling susceptibility and exposure processes. Here, we consolidate previous theory and empirical understanding regarding the entwined effects of susceptibility and exposure, which we refer to as 'the Twin Pillar Problem'. We provide a framework for conceptualising exposure-susceptibility interactions, where they obscure, confound, induce or counteract one another, providing some well-known examples for each complicating mechanism. We synthesise guidelines for anticipating and controlling for covariance between exposure and susceptibility, and we detail statistical and operational methodology that researchers have employed to deal with them. Finally, we discuss novel emerging frontiers in their study in ecology, and their potential for further integration in the fields of wildlife and human health. Read the free Plain Language Summary for this article on the Journal blog.

Automated summary

Exposure and susceptibility are fundamental to the infection status of every organism, and their interaction complicates the study of disease ecology and ecoimmunology. Currently, there is no established conceptual framework to distinguish between susceptibility and exposure processes, and specific tools are needed to address this problem. This study consolidates previous understanding and provides guidelines and methods to anticipate and control for covariance between exposure and susceptibility.