Badger Ageing, Demographic, Genomic and Epidemiological Research
Badger Ageing, Demographic, Genomic and Epidemiological Research
Wildlife disease systems are difficult to study because many important processes are hidden. We may not know exactly when an animal became infected, whether an uncaptured animal has died or moved away, which individuals interacted or how infection moved through a population.
This project combines long-term monitoring, genomic information, diagnostic data, social and spatial information, immunological markers and Bayesian statistical models to estimate these hidden processes.
A central question is how bTB persists in the badger population over time. We will ask whether infection is maintained mainly through transmission within social groups, between adults, between mothers and offspring, between neighbouring groups, through movement across the landscape or through external inputs of infection.
Understanding these routes matters because different processes can produce similar patterns in observed data. Careful modelling helps separate possible explanations.
The badger population is open: individuals can be born, die, immigrate, emigrate or disperse between social groups. These demographic processes can strongly influence estimates of infection prevalence and transmission.
The project will use integrated population models to separate mortality from emigration, recruitment from immigration and movement within the population from movement beyond the study area.
Genomic sequencing can help reconstruct family relationships, identify genetic structure, distinguish residents from immigrants and investigate whether genetic variation is associated with disease susceptibility, tolerance or progression.
The project will generate a detailed genomic resource from decades of archived and recent samples, providing new insight into kinship, inbreeding, population structure and disease processes like immunity, resitance, tolerance and transmission.
In many infectious disease systems, not all individuals contribute equally to transmission. Some animals may have more contacts, move more widely, occupy key social positions or remain infectious for longer.
The project will investigate whether social, spatial, genetic, demographic or health-related traits help explain variation in transmission potential among individual badgers.
Ageing can affect survival, reproduction, immune function, movement and social behaviour. These changes may influence an animal’s susceptibility to infection, tolerance of disease, progression of infection and potential to transmit disease onwards.
The project will investigate whether age-related changes in health and immune function help explain differences in bTB dynamics among individuals.
The project will also examine whether different pathogen strains show different epidemiological patterns and whether new strains entering the population help explain changes in infection through time.
This wider landscape perspective is important because the monitored population is not isolated. It exists within a broader ecological, agricultural and management context.
Statistical models allow researchers to combine incomplete information from many sources. In this project, models will be used to estimate hidden states such as true infection status, survival, movement, parentage and transmission.
The goal is not to replace field data, but to make the best possible use of long-term evidence while being transparent about uncertainty.