Cross–Species Transmission at the Wildlife–Livestock Interface: A Case Study of Epidemiological Inference From Mule Deer <scp>GPS</scp> Collar Data

In the current era of global change, the emergence of infectious diseases at the wildlife-livestock interface poses risks to biodiversity, agricultural economies, and public health. Driven by anthropogenic influence, increased sharing of resources between wildlife and livestock can promote cross-species transmission, the consequences of which are challenging to predict. <i>Mycoplasma bovis</i> , an economically important bacterial pathogen in cattle, has recently emerged as a threat to other ungulate species. This study reports on a case of <i>M. bovis</i> in an intensively monitored free-ranging mule deer (<i>Odocoileus hemionus</i> ) in Colorado, USA, which presented an opportunity to describe the disease in a novel host and infer transmission and infection dynamics from GPS collar data. Following a mortality signal from a GPS-collared adult female mule deer, field investigation revealed predation while postmortem examination further revealed severe, acute, fibrinosuppurative and necrotizing pleuropneumonia. Histopathological analysis, immunohistochemistry, and real-time PCR confirmed <i>M. bovis</i> as the etiology. GPS collar data demonstrated spatial overlap with dairy cattle in the 50 days prior to death, implicating potential spillover from cattle as the transmission pathway. Reduced movement was identified 19 days prior to death, indicative of sickness behavior due to acute pneumonia. This case underscores the potential for <i>M. bovis</i> to cause severe disease in wild ungulates and highlights the value of thorough postmortem investigations as a routine component of studies involving wildlife tracking. The retrospective use of GPS collar data provides valuable insights into the movement ecology of wildlife exposed to novel pathogens, aiding in the understanding of cross-species transmission and informing management strategies to reduce the potential for spillover.