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Deciphering Serology to Understand the Ecology of Infectious Diseases in Wildlife |
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| Authors: | Amy T Gilbert A R Fooks D T S Hayman D L Horton T Müller R Plowright A J Peel R Bowen J L N Wood J Mills A A Cunningham C E Rupprecht |
| Institution: | 1. National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30333, USA 11. United States Department of Agriculture, National Wildlife Research Center, 4101 LaPorte Ave, Fort Collins, CO, 80521, USA 2. Wildlife Zoonoses and Vector-Borne Disease Group, Animal Health and Veterinary Laboratories Agency, Woodham Lane, Weybridge, Surrey, KT15 3NB, UK 3. The National Consortium for Zoonosis Research, University of Liverpool, Leahurst, Chester High Road, Neston, CH64 7TE, UK 4. Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge, CB3 0ES, UK 5. Institute of Zoology, Zoological Society of London, Regent’s Park, London, NW1 4RY, UK 6. Department of Biology, Colorado State University, Fort Collins, CO, 80523, USA 7. Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, 16868, Wusterhausen, Germany 8. Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, PA, 16802, USA 9. Department of Biomedical Sciences, Colorado State University, Fort Collins, CO, 80523, USA 10. Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, 30322, USA 12. Global Alliance for Rabies Control, Manhattan, KS, USA |
| Abstract: | The ecology of infectious disease in wildlife has become a pivotal theme in animal and public health. Studies of infectious disease ecology rely on robust surveillance of pathogens in reservoir hosts, often based on serology, which is the detection of specific antibodies in the blood and is used to infer infection history. However, serological data can be inaccurate for inference to infection history for a variety of reasons. Two major aspects in any serological test can substantially impact results and interpretation of antibody prevalence data: cross-reactivity and cut-off thresholds used to discriminate positive and negative reactions. Given the ubiquitous use of serology as a tool for surveillance and epidemiological modeling of wildlife diseases, it is imperative to consider the strengths and limitations of serological test methodologies and interpretation of results, particularly when using data that may affect management and policy for the prevention and control of infectious diseases in wildlife. Greater consideration of population age structure and cohort representation, serological test suitability and standardized sample collection protocols can ensure that reliable data are obtained for downstream modeling applications to characterize, and evaluate interventions for, wildlife disease systems. |
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