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Translating Predictions of Zoonotic Viruses for Policymakers
Authors:Seth D. Judson  Matthew LeBreton  Trevon Fuller  Risa M. Hoffman  Kevin Njabo  Timothy F. Brewer  Elsa Dibongue  Joseph Diffo  Jean-Marc Feussom Kameni  Severin Loul  Godwin W. Nchinda  Richard Njouom  Julius Nwobegahay  Jean Michel Takuo  Judith N. Torimiro  Abel Wade  Thomas B. Smith
Affiliation:1.David Geffen School of Medicine at UCLA,Los Angeles,USA;2.Mosaic,Yaoundé,Cameroon;3.University of California,Los Angeles,USA;4.Ministry of Public Health,Yaoundé,Cameroon;5.Metabiota Cameroon,Yaoundé,Cameroon;6.Ministry of Livestock, Fisheries and Animal Industries,Yaoundé,Cameroon;7.Epidemiology-Public Health-Veterinary Association (ESPV),Yaoundé,Cameroon;8.The Chantal Biya International Reference Centre for Research on the Prevention and Management of HIV/AIDS (CIRCB),Yaoundé,Cameroon;9.Center Pasteur,Yaoundé,Cameroon;10.Military Health Research Center,Yaoundé,Cameroon;11.National Veterinary Laboratory (LANAVET) Annex,Yaoundé,Cameroon
Abstract:Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers.
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