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.

SUMMARYAccurate detection of infection with Mycobacterium bovis in live badgers would enable targeted tuberculosis control. Practical challenges in sampling wild badger populations mean that diagnosis of infection at the group (rather than the individual) level is attractive. We modelled data spanning 7 years containing over 2000 sampling events from a population of wild badgers in southwest England to quantify the ability to correctly identify the infection status of badgers at the group level. We explored the effects of variations in: (1) trapping efficiency; (2) prevalence of M. bovis; (3) using three diagnostic tests singly and in combination with one another; and (4) the number of badgers required to test positive in order to classify groups as infected. No single test was able to reliably identify infected badger groups if <90% of the animals were sampled (given an infection prevalence of 20% and group size of 15 badgers). However, the parallel use of two tests enabled an infected group to be correctly identified when only 50% of the animals were tested and a threshold of two positive badgers was used. Levels of trapping efficiency observed in previous field studies appear to be sufficient to usefully employ a combination of two existing diagnostic tests, or others of similar or greater accuracy, to identify infected badger groups without the need to capture all individuals. To improve on this, we suggest that any new diagnostic test for badgers would ideally need to be >80% sensitive, at least 94% specific, and able to be performed rapidly in the field.

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The diagnosis and control of Mycobacterium bovis infection (bovine tuberculosis: TB) continues to present huge challenges to the British cattle industry. A clearer understanding of the magnitude and duration of immune response to M. bovis infection in the European badger (Meles meles) - a wildlife maintenance host - may assist with the future development of diagnostic tests, and vaccination and disease management strategies. Here, we analyse 5280 diagnostic test results from 550 live wild badgers from a naturally-infected population to investigate whether one diagnostic test (a gamma interferon release [IFNγ] assay, n = 550 tests) could be used to predict future positive results on two other tests for the same disease (a serological test [n = 2342 tests] and mycobacterial culture [n = 2388 tests]) and hence act as an indicator of likely bacterial excretion or disease progression. Badgers with the highest IFNγ optical density (OD) values were most likely to subsequently test positive on both serological and culture tests, and this effect was detectable for up to 24 months after the IFNγ test. Furthermore, the higher the original IFNγ OD value, the greater the chance that a badger would subsequently test positive using serology. Relationships between IFNγ titres and mycobacterial culture results from different types of clinical sample suggest that the route of infection may affect the magnitude of immune response in badgers. These findings identify further value in the IFNγ test as a useful research tool, as it may help us to target studies at animals and groups that are most likely to succumb to more progressive disease.