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Data-driven identification of potential Zika virus vectors

View ORCID ProfileMichelle V. Evans, Tad A. Dallas, Barbara A. Han, Courtney C. Murdock, John M. Drake
doi: https://doi.org/10.1101/077966
Michelle V. Evans
1Odum School of Ecology, University of Georgia, Athens, GA, USA
5Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA
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  • ORCID record for Michelle V. Evans
  • For correspondence: mvevans@uga.edu
Tad A. Dallas
1Odum School of Ecology, University of Georgia, Athens, GA, USA
2Department of Environmental Science and Policy, University of California-Davis, Davis, CA, USA
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Barbara A. Han
3Cary Institute of Ecosystem Studies, Millbrook, NY, USA
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Courtney C. Murdock
1Odum School of Ecology, University of Georgia, Athens, GA, USA
4Department of Infectious Disease, University of Georgia, Athens, GA, USA
5Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA
6Center for Tropical Emerging Global Diseases, University of Georgia, Athens, GA, USA
7Center for Vaccines and Immunology, University of Georgia, Athens, GA, USA
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John M. Drake
1Odum School of Ecology, University of Georgia, Athens, GA, USA
5Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA
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Abstract

Zika is an emerging, mosquito-borne virus recently introduced to the Americas, whose rapid spread is unprecedented and of great public health concern. Knowledge about transmission – which depends on the presence of competent vectors – remains incomplete, especially concerning potential transmission in geographic areas in which it has not yet been introduced. To identify presently unknown vectors of Zika, we developed a data-driven model linking candidate vector species and the Zika virus via vector-virus trait combinations that confer a propensity toward associations in the larger ecological network connecting flaviviruses and their mosquito vectors. Our model predicts that thirty-five species may be able to transmit the virus, twenty-six of which are not currently known vectors of Zika virus. Seven of these species are found in the continental United States, including Culex quinquefasciatus and Cx. pipiens, both of which are common mosquito pests and vectors of West Nile Virus. Because the range of these predicted species is wider than that of known vectors Aedes aeygpti and Ae. albopictus, we reason that a larger geographic area is at risk for autochthonous transmission of Zika virus than reported by maps constructed from the ranges of only the two Aedes species. Consequently, the reach of existing vector control activities and public health campaigns may need to be expanded.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 27, 2016.
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Data-driven identification of potential Zika virus vectors
Michelle V. Evans, Tad A. Dallas, Barbara A. Han, Courtney C. Murdock, John M. Drake
bioRxiv 077966; doi: https://doi.org/10.1101/077966
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Data-driven identification of potential Zika virus vectors
Michelle V. Evans, Tad A. Dallas, Barbara A. Han, Courtney C. Murdock, John M. Drake
bioRxiv 077966; doi: https://doi.org/10.1101/077966

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