Long-term temporal trends and estimated transmission rates forMycobacterium bovisinfection in an undisturbed high-density badger (Meles meles) population
Abstract:We describe epidemiological trends in Mycobacterium bovis infection in an undisturbed wild badger (Meles meles) population. Data were derived from the capture, clinical sampling and serological testing of 1803 badgers over 9945 capture events spanning 24 years. Incidence and prevalence increased over time, exhibiting no simple relationship with host density. Potential explanations are presented for a marked increase in the frequency of positive serological test results. Transmission rates (R0) estimated from e… Show more
“…In contrast, badgers that were caught many times over several years and consistently tested negative were unlikely to be truly infected, although this probability never reached zero (see badger 015P in Fig. 3); this is likely due to the imperfect sensitivity of the testing regime and the background prevalence of infection in the population - which was estimated in a recent paper to have reached 30% in 2005, just prior to the start of this study 26 .Figure 3Examples showing variation in the probability of being infected with M. bovis at the time of last capture for a selected sample of badgers, given each individual’s history of capture and test results. The probability of a badger being truly infected varied with its sex, capture history and current and historical diagnostic test results.…”
Section: Resultsmentioning
confidence: 80%
“…of mistakenly removing an individual which is in fact uninfected). For long-term surveillance of disease in this population, applying a probabilistic approach to infection status represents a clear improvement on current practice where a positive or negative diagnosis is usually based on imperfect tests applied at a single sampling point 26, 27 . Our findings suggest it is possible to gain a much deeper insight into the true infection status of individual badgers by interpreting longitudinal diagnostic test results and accounting for uncertainty in biological and behavioural processes.…”
Section: Discussionmentioning
confidence: 99%
“…This is likely to arise owing to fluctuations in weather conditions affecting food availability and foraging behaviour 35, 36 in addition to cubs becoming independent (and therefore more readily trappable) in the summer 37 . Trapping effort during the long term study at Woodchester Park has remained constant from one year to the next 26 and therefore should not have influenced these estimates. Our model output indicated very clear seasonality of M .…”
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.
“…In contrast, badgers that were caught many times over several years and consistently tested negative were unlikely to be truly infected, although this probability never reached zero (see badger 015P in Fig. 3); this is likely due to the imperfect sensitivity of the testing regime and the background prevalence of infection in the population - which was estimated in a recent paper to have reached 30% in 2005, just prior to the start of this study 26 .Figure 3Examples showing variation in the probability of being infected with M. bovis at the time of last capture for a selected sample of badgers, given each individual’s history of capture and test results. The probability of a badger being truly infected varied with its sex, capture history and current and historical diagnostic test results.…”
Section: Resultsmentioning
confidence: 80%
“…of mistakenly removing an individual which is in fact uninfected). For long-term surveillance of disease in this population, applying a probabilistic approach to infection status represents a clear improvement on current practice where a positive or negative diagnosis is usually based on imperfect tests applied at a single sampling point 26, 27 . Our findings suggest it is possible to gain a much deeper insight into the true infection status of individual badgers by interpreting longitudinal diagnostic test results and accounting for uncertainty in biological and behavioural processes.…”
Section: Discussionmentioning
confidence: 99%
“…This is likely to arise owing to fluctuations in weather conditions affecting food availability and foraging behaviour 35, 36 in addition to cubs becoming independent (and therefore more readily trappable) in the summer 37 . Trapping effort during the long term study at Woodchester Park has remained constant from one year to the next 26 and therefore should not have influenced these estimates. Our model output indicated very clear seasonality of M .…”
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.
“…The study area consists of a mosaic of largely deciduous woodland and pasture (see [14] for detailed composition). During routine capture-markrecapture exercises [15] in January 2012, an adult female European badger (Meles meles) with a body mass of 9.0 kg was captured in a steel mesh live-trap and transferred to an examination facility where it was anaesthetised by intramuscular administration of two parts butorphanol tartrate (Torbugesic ® , Wyeth, Ontario, Canada), two parts ketamine hydrochloride (Ketaset ® , Wyeth, Ontario, Canada) and one part medetomidine (Domitor ® , Orion Corporation, Espoo, Finland) [16]. Samples of faeces, urine, and tracheal and oesophageal aspirate were collected for mycobacterial culture [17], and a sample of jugular blood was taken for gamma interferon (IFNγ ) [18] testing and STAT-PAK serological assay (BrockTB STAT-PAK ® ; Chembio Diagnostic Systems, New York, USA) [19].…”
Background:The European badger (Meles meles) is involved in the maintenance of bovine tuberculosis infection and onward spread to cattle. However, little is known about how transmission occurs. One possible route could be through direct contact between infected badgers and cattle. It is also possible that indirect contact between cattle and infected badger excretory products such as faeces or urine may occur either on pasture or within and around farm buildings. A better understanding of behaviour patterns in wild badgers may help to develop biosecurity measures to minimise direct and indirect contact between badgers and cattle. However, monitoring the behaviour of free-ranging badgers can be logistically challenging and labour intensive due to their nocturnal and semi-fossorial nature. We trialled a GPS and tri-axial accelerometer-equipped collar on a free-ranging badger to assess its potential value to elucidate behaviour-time budgets and functional habitat use. Results: During the recording period between 16:00 and 08:00 on a single night, resting was the most commonly identified behaviour (67.4%) followed by walking (20.9%), snuffling (9.5%) and trotting (2.3%). When examining accelerometer data associated with each GPS fix and habitat type (occurring 2 min 30 s before and after), walking was the most common behaviour in woodland (40.3%) and arable habitats (53.8%), while snuffling was the most common behaviour in pasture (61.9%). Several nocturnal resting periods were also observed. The total distance travelled was 2.28 km.
Conclusions:In the present report, we demonstrate proof of principle in the application of a combined GPS and accelerometer device to collect detailed quantitative data on wild badger behaviour. Behaviour-time budgets allow us to investigate how badgers allocate energy to different activities and how this might change with disease status. Such information could be useful in the development of measures to reduce opportunities for onward transmission of bovine tuberculosis from badgers to cattle.
“…A larger total number of badgers will be killed than in option one, with the possibility of M bovis not being eradicated. M bovis can persist and spread in badger populations for years in the absence of infection from cattle 8. (It is noted that the Bovine TB Strategy Review9 states: ‘There is no scientific consensus about whether the disease is self-sustaining in badgers.’)…”
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