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Data from: Missing the people for the trees: identifying coupled natural-human system feedbacks driving the ecology of Lyme disease

Citation

MacDonald, Andrew J.; Larsen, Ashley E.; Plantinga, Andrew J. (2018), Data from: Missing the people for the trees: identifying coupled natural-human system feedbacks driving the ecology of Lyme disease, Dryad, Dataset, https://doi.org/10.5061/dryad.p7t9289

Abstract

1. Infectious diseases are rapidly emerging and many are increasing in incidence across the globe. Processes of land-use change, notably habitat loss and fragmentation, have been widely implicated in emergence and spread of zoonoses such as Lyme disease, yet evidence remains equivocal. 2. Here we discuss and apply an innovative approach from the social sciences, instrumental variables, that seeks to tease out causality from observational data. Using this approach, we revisit the effect of forest fragmentation on Lyme disease incidence, focusing on human interaction with fragmented landscapes. Though human interaction with infected ticks is of clear and fundamental importance to human disease incidence, human activities that influence exposure have been nearly universally overlooked in the ecology literature. 3. Using county-level land-use and Lyme disease incidence data for ~800 counties from the northeastern United States over the span of a decade, we illustrate (1) human interaction with fragmented forest landscapes reliably predicts Lyme disease incidence, while ecological measures of forest fragmentation alone are unreliable predictors and (2) that identifying the effect of forest fragmentation on human disease requires addressing the feedback between Lyme disease risk and human decisions to avoid interaction with high-risk landscapes. 4. Synthesis and applications. The innovative approach and novel results help to clarify the equivocal literature on forest fragmentation and Lyme disease, and illustrate the key role that human behavior may be playing in the ecology of Lyme disease in North America. Accounting for human activity and behavior in the ecology of disease more broadly may result in improved understanding of both the ecological drivers of disease, as well as actionable intervention strategies to reduce disease burden in a changing world. For example, our model results have practical implications for land-use policy aimed at disease reduction. Our model suggests land use regulations that reduce parcel size would be an actionable approach for policy makers concerned about increasing Lyme disease incidence in the northeastern US.10-Oct-2018

Usage Notes

Location

northeastern United States