Data-Driven Identification of Potential Zika Virus Vectors Michelle V Evans1,2*, Tad a Dallas1,3, Barbara a Han4, Courtney C Murdock1,2,5,6,7,8, John M Drake1,2,8
RESEARCH ARTICLE Data-driven identification of potential Zika virus vectors Michelle V Evans1,2*, Tad A Dallas1,3, Barbara A Han4, Courtney C Murdock1,2,5,6,7,8, John M Drake1,2,8 1Odum School of Ecology, University of Georgia, Athens, United States; 2Center for the Ecology of Infectious Diseases, University of Georgia, Athens, United States; 3Department of Environmental Science and Policy, University of California-Davis, Davis, United States; 4Cary Institute of Ecosystem Studies, Millbrook, United States; 5Department of Infectious Disease, University of Georgia, Athens, United States; 6Center for Tropical Emerging Global Diseases, University of Georgia, Athens, United States; 7Center for Vaccines and Immunology, University of Georgia, Athens, United States; 8River Basin Center, University of Georgia, Athens, United States Abstract Zika is an emerging virus whose rapid spread is of great public health concern. Knowledge about transmission remains incomplete, especially concerning potential transmission in geographic areas in which it has not yet been introduced. To identify unknown vectors of Zika, we developed a data-driven model linking vector species and the Zika virus via vector-virus trait combinations that confer a propensity toward associations in an ecological network connecting flaviviruses and their mosquito vectors. Our model predicts that thirty-five species may be able to transmit the virus, seven of which are found in the continental United States, including Culex quinquefasciatus and Cx. pipiens. We suggest that empirical studies prioritize these species to confirm predictions of vector competence, enabling the correct identification of populations at risk for transmission within the United States. *For correspondence: mvevans@ DOI: 10.7554/eLife.22053.001 uga.edu Competing interests: The authors declare that no competing interests exist.
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