ArticleScientific reports2017
Inference of the infection status of individuals using longitudinal testing data from cryptic populations: Towards a probabilistic approach to diagnosis.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Multi-event dynamic capture-recapture model for big data: Estimating undetected COVID-19 cases in British Columbia, Canada.Infectious Disease Modelling · 2026Article
- Efficient modelling of infectious diseases in wildlife: A case study of bovine tuberculosis in wild badgers.PLoS computational biology · 2024Article
- Newcastle disease virus transmission dynamics in wild peridomestic birds in the United Arab Emirates.Scientific reports · 2021Article
- How sure are you? A web-based application to confront imperfect detection of respiratory pathogens in bighorn sheep.PloS one · 2020Article
- Exposure of breeding albatrosses to the agent of avian cholera: dynamics of antibody levels and ecological implications.Oecologia · 2019Article
- Impact of Imperfect Disease Detection on the Identification of Risk Factors in Veterinary Epidemiology.Frontiers in veterinary science · 2019Article
- Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state-space models.Ecology and evolution · 2018Article
- A multi-event capture-recapture analysis of Toxoplasma gondii seroconversion dynamics in farm cats.Parasites & vectors · 2018Article
- Social status mediates the fitness costs of infection with canine distemper virus in Serengeti spotted hyenas.Functional ecology · 2018Article
- Modeling as a Decision Support Tool for Bovine TB Control Programs in Wildlife.Frontiers in veterinary science · 2018Review
- Prior Precision, Prior Accuracy, and the Estimation of Disease Prevalence Using Imperfect Diagnostic Tests.Frontiers in veterinary science · 2018Article
- The Certainty of Uncertainty: Potential Sources of Bias and Imprecision in Disease Ecology Studies.Frontiers in veterinary science · 2018Article
- Robustness of Eco-Epidemiological Capture-Recapture Parameter Estimates to Variation in Infection State Uncertainty.Frontiers in veterinary science · 2018Article
- Longitudinal survey of two serotine bat (Eptesicus serotinus) maternity colonies exposed to EBLV-1 (European Bat Lyssavirus type 1): Assessment of survival and serological status variations using capture-recapture models.PLoS neglected tropical diseases · 2017Article
- Seasonal variation in daily patterns of social contacts in the European badgerEcology and evolution · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective control of many diseases requires the accurate detection of infected individuals. Confidently ascertaining whether an individual is infected can be challenging when diagnostic tests are imperfect and when some individuals go for long periods of time without being observed or sampled. Here, we use a multi-event capture-recapture approach to model imperfect observations of true epidemiological states. We describe a method for interpreting potentially disparate results from individuals sampled multiple times over an extended period, using empirical data from a wild badger population naturally infected with Mycobacterium bovis as an example. We examine the effect of sex, capture history and current and historical diagnostic test results on the probability of being truly infected, given any combination of diagnostic test results. In doing so, we move diagnosis away from the traditional binary classification of apparently infected versus uninfected to a probability-based interpretation which is updated each time an individual is re-sampled. Our findings identified temporal variation in infection status and suggest that capture probability is influenced by year, season and infection status. This novel approach to combining ecological and epidemiological data may aid disease management decision-making by providing a framework for the integration of multiple diagnostic test data with other information.
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