Causal inference in disease ecology: investigating ecological drivers of disease emergence

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Abstract

Despite awareness that disease emergence may be related to ecological change, few studies have rigorously analyzed the underlying environmental drivers of the dynamics of disease emergence. This may be due to the fact that ecological change and disease emergence are often mediated through complex and large-scale processes that are not amenable to traditional reductionist approaches to causal inference. Here, we suggest strategies assembled from diverse disciplines, including ecology, epidemiology, and the social sciences, to analyze complex relationships, promote cooperation, increase efficiency, and minimize bias when investigating the ecological drivers of disease emergence. These techniques, which complement traditional hypothesis testing, include epidemiologic causal criteria, strong inference, causal diagrams, model selection, and triangulation. We also present several examples from recent emerging infectious disease investigations, including Hendra virus, Nipah virus, coral diseases, and avian influenza, where these techniques were successfully applied. Here, we outline some of the barriers to advancing our understanding of causation in disease ecology and offer some solutions for investigating large-scale ecological drivers, such as global warming, pollution, and land-use change.

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