Transmission of infectious diseases is strongly influenced by who contacts whom. Despite the global distribution of tuberculosis (TB) in free-living wild mammal populations, little is known of the mechanisms of social transmission of Mycobacterium bovis between individuals. Here, I use a network approach to examine for correlations between five distinct types of intra-and intergroup social interaction and changes in TB status of 110 wild meerkats (Suricata suricatta) in five social groups over two years. Contrary to predictions, the most socially interactive animals were not at highest risk of acquiring infection, indicating that in addition to contact frequency, the type and direction of interactions must be considered when quantifying disease risk. Within social groups, meerkats that groomed others most were more likely to become infected than individuals who received high levels of grooming. Conversely, receiving, but not initiating, aggression was associated with M. bovis infection. Incidence of intergroup roving by male meerkats was correlated with the rovers themselves subsequently testing TB-positive, suggesting a possible route for transmission of infection between social groups. Exposure time was less important than these social interactions in influencing TB risk. This study represents a novel application of social network analysis using empirical data to elucidate the role of specific interactions in the transmission of an infectious disease in a free-living wild animal population.

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Disease surveillance programmes ought to be evaluated regularly to ensure they provide valuable information in an efficient manner. Evaluation of human and animal health surveillance programmes around the world is currently not standardized and therefore inconsistent. The aim of this systematic review was to review surveillance system attributes and the methods used for their assessment, together with the strengths and weaknesses of existing frameworks for evaluating surveillance in animal health, public health and allied disciplines. Information from 99 articles describing the evaluation of 101 surveillance systems was examined. A wide range of approaches for assessing 23 different system attributes was identified although most evaluations addressed only one or two attributes and comprehensive evaluations were uncommon. Surveillance objectives were often not stated in the articles reviewed and so the reasons for choosing certain attributes for assessment were not always apparent. This has the potential to introduce misleading results in surveillance evaluation. Due to the wide range of system attributes that may be assessed, methods should be explored which collapse these down into a small number of grouped characteristics by focusing on the relationships between attributes and their links to the objectives of the surveillance system and the evaluation. A generic and comprehensive evaluation framework could then be developed consisting of a limited number of common attributes together with several sets of secondary attributes which could be selected depending on the disease or range of diseases under surveillance and the purpose of the surveillance. Economic evaluation should be an integral part of the surveillance evaluation process. This would provide a significant benefit to decision-makers who often need to make choices based on limited or diminishing resources.

BackgroundAccurate diagnosis of tuberculosis (TB) due to infection with Mycobacterium bovis is notoriously difficult in live animals, yet important if we are to understand the epidemiology of TB and devise effective strategies to limit its spread. Currently available tests for diagnosing TB in live Eurasian badgers (Meles meles) remain unvalidated against a reliable gold standard. The aim of the present study was to evaluate the diagnostic accuracy and optimal use of three tests for TB in badgers in the absence of a gold standard.Methodology/Principal FindingsA Bayesian approach was used to evaluate the diagnostic accuracy and optimal use of mycobacterial culture, gamma-interferon assay and a commercially available serological test using multiple samples collected from 305 live wild badgers. Although no single test was judged to be sufficiently sensitive and specific to be used as a sole diagnostic method, selective combined use of the three tests allowed guidelines to be formulated that allow a diagnosis to be made for individual animals with an estimated overall accuracy of 93% (range: 75% to 97%). Employing this approach in the study population of badgers resulted in approximately 13 out of 14 animals having their true infection status correctly classified from samples collected on a single capture.Conclusions/SignificanceThis method of interpretation represents a marked improvement on the current procedure for diagnosing M. bovis infection in live badgers. The results should be of use to inform future test and intervention strategies with the aim of reducing the incidence of TB in free-living wild badger populations.

Knowledge of the way in which animals interact through social networks can help to address questions surrounding the ecological and evolutionary consequences of social organisation, and to understand and manage the spread of infectious diseases. Automated proximity loggers are increasingly being used to record interactions between animals, but the accuracy and reliability of the collected data remain largely un-assessed. Here we use laboratory and observational field data to assess the performance of these devices fitted to a herd of 32 beef cattle (Bos taurus) and nine groups of badgers (Meles meles, n  = 77) living in the surrounding woods. The distances at which loggers detected each other were found to decrease over time, potentially related to diminishing battery power that may be a function of temperature. Loggers were highly accurate in recording the identification of contacted conspecifics, but less reliable at determining contact duration. There was a tendency for extended interactions to be recorded as a series of shorter contacts. We show how data can be manipulated to correct this discrepancy and accurately reflect observed interaction patterns by combining records between any two loggers that occur within a 1 to 2 minute amalgamation window, and then removing any remaining 1 second records. We make universally applicable recommendations for the effective use of proximity loggers, to improve the validity of data arising from future studies.

The organism that causes tuberculosis in meerkats (Suricata suricatta) has been poorly characterized. Our genetic analysis showed it to be a novel member of the Mycobacterium tuberculosis complex and closely related to the dassie bacillus. We have named this epidemiologically and genetically unique strain M. suricattae.

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify 'hidden' aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.