Interdisciplinary approaches to understanding disease emergence: the past, present, and future drivers of Nipah virus emergence - PubMed (original) (raw)

. 2013 Feb 26;110 Suppl 1(Suppl 1):3681-8.

doi: 10.1073/pnas.1201243109. Epub 2012 Aug 30.

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Interdisciplinary approaches to understanding disease emergence: the past, present, and future drivers of Nipah virus emergence

Peter Daszak et al. Proc Natl Acad Sci U S A. 2013.

Abstract

Emerging infectious diseases (EIDs) pose a significant threat to human health, economic stability, and biodiversity. Despite this, the mechanisms underlying disease emergence are still not fully understood, and control measures rely heavily on mitigating the impact of EIDs after they have emerged. Here, we highlight the emergence of a zoonotic Henipavirus, Nipah virus, to demonstrate the interdisciplinary and macroecological approaches necessary to understand EID emergence. Previous work suggests that Nipah virus emerged due to the interaction of the wildlife reservoir (Pteropus spp. fruit bats) with intensively managed livestock. The emergence of this and other henipaviruses involves interactions among a suite of anthropogenic environmental changes, socioeconomic factors, and changes in demography that overlay and interact with the distribution of these pathogens in their wildlife reservoirs. Here, we demonstrate how ecological niche modeling may be used to investigate the potential role of a changing climate on the future risk for Henipavirus emergence. We show that the distribution of Henipavirus reservoirs, and therefore henipaviruses, will likely change under climate change scenarios, a fundamental precondition for disease emergence in humans. We assess the variation among climate models to estimate where Henipavirus host distribution is most likely to expand, contract, or remain stable, presenting new risks for human health. We conclude that there is substantial potential to use this modeling framework to explore the distribution of wildlife hosts under a changing climate. These approaches may directly inform current and future management and surveillance strategies aiming to improve pathogen detection and, ultimately, reduce emergence risk.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Fig. 1.

Conceptual model of our methods. (A) Models of a single species’ current bioclimate, based on Worldclim. (B) Projected future suitable bioclimate based on 20 downscaled GCMs, where presence was defined as suitable by at least 50% of the GCMs. (C) Expansion/contraction maps based on the subtraction of the present from the future multi-GCM predictions. (D) All 13 species expansion/contraction maps were combined into three composite maps that show habitat expansion, contraction, and stability. (E) Synthetic map across GCMs and species that shows habitat expansion, contraction, and stability.

Fig. 2.

Fig. 2.

Synthetic generalization of the predicted expansion and contraction potential climatic habitat for the midcentury A2 emission scenario based on 20 GCMs and 13 bat species. Because each species was modeled individually, expansion is defined as the presence of at least one species and no change in the other species and contraction was defined as the absence of at least one species and no change in the other species.

Fig. 3.

Fig. 3.

Potential climatic habitat expansion (A), contraction (B), and stability (C) maps for the midcentury A2 emissions scenario based on agreement of 20 GCMs and 13 bat species.

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