Identifying social behaviours related to disease transmission in banded mongoose from accelerometer data

Résumé fourni par la source

Abstract Current methods for identifying and predicting infectious disease dynamics in wildlife populations are limited. Pathogen transmission dynamics can be complex, influenced by behavioural interactions between and among hosts, pathogens and their environments. These behaviours may also be influenced directly by observers, with observational research methods being limited to habituated species. Banded mongoose Mungos mungo are social, medium size carnivores infected with the novel tuberculosis pathogen Mycobacterium mungi . This pathogen is principally transmitted during normal olfactory communication behaviours. Banded mongoose behavioural responses to humans change over the landscape, limiting the use of direct observational approaches in areas where mongoose are threatened and flee. The accelerometers in bio‐logging devices have been used previously to identify distinct behaviours in wildlife species, providing a tool to quantifying specific behaviours in ecological studies. We deployed Axy‐5X model accelerometers (TechnoSmArt) on captive mongoose to determine whether accelerometers could be used to identify key mongoose behavioural activities previously associated with M. mungi transmission. After two collaring periods, we determined that three distinct behavioural activities could be identified in the accelerometer data: bipedal vertical vigilance, running and scent marking activity; behaviours that have been shown to vary across land type in the banded mongoose. Results from this work advance current data analytics and provide modifications to data analysis works flows, updating and expanding upon current methodologies. We also provide preliminary evidence of successful mathematical classification of the target behaviours, supporting the future use of these devices. Methods applied here may allow model estimates of M. mungi transmission in free‐ranging mongoose to be refined with possible application to other systems where direct observation approaches have limited application.

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