EDWD: The evolutionary epidemiology and demography of "endemic" wildlife disease in an open, fluctuating host population

One of the greatest threats to human health and livelihood, worldwide, is the risk of disease spilling over from wildlife into people or livestock, causing dangerous epidemics or even pandemics. A major knowledge gap is our poor understanding of how diseases persist in wildlife populations. A common presumption is that wildlife disease is somehow “endemic”, persisting at a stable prevalence and difficult to control without culling the wildlife host indiscriminately. We propose a challenge to this “endemic disease” paradigm. Instead, wildlife disease burdens are maintained by multiple drivers, each of which fluctuate through time in association with the ecology, genetics, social structure and demography of the host-pathogen interaction. Our goal is to understand the key drivers of persistence and transmission of bovine tuberculosis (bTB) in a population of badgers that has been studied intensively, free from disease control interventions, for 50 years. The persistence of bTB in badger populations is perhaps the most important wildlife disease controversy in the UK. Using the badger-bTB interaction as a case study, we will radically improve the wider understanding of endemic and epidemic disease in wildlife populations. This new knowledge will transform our ability to predict and manage wildlife disease and emergent epidemics and pandemics of the future. The badger population we study has fluctuated in abundance through time, and the prevalence of bTB has also fluctuated in space and time. The population is open to the influence of badger immigration and emigration, to the risk of infection from livestock herds and to the impact of external population management. Our understanding of the causes of bTB persistence, and its fluctuations, is hampered by the hidden processes that affect all study of wildlife disease. We cannot be sure whether badgers are dead, truly infected, or responsible for onward transmission, because we rely on imperfect monitoring. Instead we use statistical models to infer the important demographic and disease processes. We propose to whole-genome re-sequence 50+ years’ worth of badger tissue samples, allowing us to build powerful host pedigrees; distinguish between resident and immigrant badgers; quantify changes in the genetic composition of the host population over time; and identify genetic associations with infection processes. We propose the development of a complex statistical model to help us infer which badgers are most responsible for the transmission of infection and find out if those superspreader badgers could be targeted to help control disease. We will ask whether bTB prevalence is sustained by birth, death and transmission within social groups, or by immigration and transmission between groups. We will ask whether inbreeding makes badgers more susceptible to disease, and why. We will ask whether badgers become more susceptible with age, and what this means for superspreading behaviours. We will ask whether the drivers of bTB prevalence have changed over the decades, and whether there is any influence of badger culling, badger vaccination and new bTB strains in the wider landscape.