Detecting superspreaders in wildlife reservoirs of disease

Abstract

AbstractWild animals commonly harbour infectious diseases with risk of spillover to humans and livestock. Bovine tuberculosis (bTB) is one such disease, posing significant socio-economic and welfare threats to the cattle industry worldwide. Identifying superspreaders, those individuals most responsible for onward transmission of infection, is critical for disease management. In practice, superspreaders are hard to identify because monitoring relies on imperfect surveillance and imperfect diagnostic tests, hence key epidemiological events, including transmission, are only partially observed. To infer the hidden dynamics of disease spread in wildlife, we fitted an individual-level stochastic spatial meta-population model of bTB transmission to data from a longitudinal study of the European badger (Meles meles). We develop a novel estimator for the individual effective reproduction number, providing quantitative evidence for the presence of superspreader badgers, despite the population-level effective reproduction number being less than one. The efficiency of bTB control in badgers could be substantially increased by targeting interventions at the relatively small proportion of individuals responsible for most onward transmission. Our modelling framework provides a flexible, efficient and generalisable means of fitting state-space models to individual-level data, to identify high-risk individuals and explore important epidemiological questions about bTB and other diseases of wildlife, livestock and humans.