Deciphering Serology to Understand the Ecology of Infectious Diseases in Wildlife

Authors

Amy T. Gilbert, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, United States Department of Agriculture, National Wildlife Research CenterFollow
A. R. Fooks, Animal Health and Veterinary Laboratories Agency, University of Liverpool
D. T. S. Hayman, University of Cambridge, Institute of Zoology, Zoological Society of London, Colorado State University, Wildlife Zoonoses and Vector-Borne Disease Group, Animal Health and Veterinary Laboratories AgencyFollow
D. L. Horton, Wildlife Zoonoses and Vector-Borne Disease Group, Animal Health and Veterinary Laboratories Agency
T. Muller, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health
R. Plowright, Pennsylvania State University
A. J. Peel, University of Cambridge, Institute of Zoology, Zoological Society of London
R. Bowen, Colorado State University - Fort Collins
J. L. Wood, University of Cambridge
J. Miils, Emory University
A. A. Cunningham, Institute of Zoology, Zoological Society of LondonFollow
C. E. Rupprecht, Global Alliance for Rabies Control, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention

Document Type

Article

Date of this Version

2013

Citation

EcoHealth 10, 298–313, 2013 DOI: 10.1007/s10393-013-0856-0

Comments

This article is a U.S. government work, and is not subject to copyright in the United States.

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