Assembling evidence for identifying reservoirs of infection

•We review the problem of identifying reservoirs of infection for multihost pathogens and provide an overview of current approaches and future directions.•We provide a conceptual framework for classifying patterns of incidence and prevalence.•We review current methods that allow us to characterise t...

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Veröffentlicht in:Trends in ecology & evolution (Amsterdam) 2014-05, Vol.29 (5), p.270-279
Hauptverfasser: Viana, Mafalda, Mancy, Rebecca, Biek, Roman, Cleaveland, Sarah, Cross, Paul C., Lloyd-Smith, James O., Haydon, Daniel T.
Format: Artikel
Sprache:eng
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Zusammenfassung:•We review the problem of identifying reservoirs of infection for multihost pathogens and provide an overview of current approaches and future directions.•We provide a conceptual framework for classifying patterns of incidence and prevalence.•We review current methods that allow us to characterise the components of reservoir-target systems.•Ecological theory offers promising new ways to prioritise populations when designing interventions.•We propose using interventions as quasi-experiments embedded in adaptive management frameworks.•Integration of data and analysis provides powerful new opportunities for studying multihost systems. Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems.
ISSN:0169-5347
1872-8383
DOI:10.1016/j.tree.2014.03.002