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

  1. Healy Hamiltone
  1. aEcoHealth Alliance, New York, NY 10001;
  2. bFogarty International Center, National Institutes of Health, Bethesda, MD 20892;
  3. cDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544;
  4. dEnvironmental Systems Graduate Group, University of California, Merced, CA 95344; and
  5. eMarine Conservation Institute, Glen Ellen, CA 95442
  1. Edited by Jeffrey Shaman, Columbia University, New York, NY, and accepted by the Editorial Board July 3, 2012 (received for review January 26, 2012)

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.

Footnotes

  • ?1To whom correspondence should be addressed. E-mail: daszak{at}ecohealthalliance.org.
  • Author contributions: P.D., C.Z.-T., T.L.B., M.F., and H.H. designed research; C.Z.-T., M.F., K.A.M., and H.H. performed research; J.H.E. and H.H. contributed new reagents/analytic tools; C.Z.-T., T.L.B., K.A.M., and H.H. analyzed data; and P.D., C.Z.-T., T.L.B., M.F., J.H.E., K.A.M., and H.H. wrote the paper.

  • The authors declare no conflict of interest.

  • This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sciences, “Fostering Advances in Interdisciplinary Climate Science,” held March 31–April 2, 2011, at the AAAS Auditorium in Washington, DC. The complete program and audio files of most presentations are available on the NAS Web site at www.nasonline.org/climate-science.html.

  • This article is a PNAS Direct Submission. J.S. is a guest editor invited by the Editorial Board.

  • This article contains supporting information online at www.danielhellerman.com/lookup/suppl/doi:10.1073/pnas.1201243109/-/DCSupplemental.

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