People

Barbara Tschirren | Associate Professor | University of Exeter

I am an evolutionary ecologist at the University of Exeter with broad interests in eco‑evolutionary processes in host–pathogen systems. In the BADGER project, I lead the Genetics and Genomics work package. This work will integrate whole‑genome re‑sequencing data from 2,500 badgers sampled over 50 years with detailed infection and life‑history records to investigate how genetic variation influences bTB susceptibility, disease progression, and onward transmission. We will also examine how inbreeding and gene flow shape disease dynamics, and how bTB has influenced the evolutionary trajectories of the badger population over the past five decades. In addition, we will test key evolutionary hypotheses for the maintenance of genetic variation in disease susceptibility, including resistance vs. reproduction trade‑offs and fluctuating selection. 

Dave Hodgson | Professor of Ecology | University of Exeter

I am a population biologist with broad interests in the dynamics of wild populations, the evolution of life histories, and the epidemiology of wildlife disease. I use statistical analysis, modelling and theory to explain patterns in population dynamics, endangerment and invasiveness, in nature. Armed with detailed demographic and genomic information, I lead this NERC-funded large project to help understand the genetic, demographic and ecological drivers of fluctuations in bovine tuberculosis prevalence in the Woodchester Park badger population.

Andy Young | Professor of Evolutionary Ecology | University of Exeter

Andy is an evolutionary ecologist, with particular interests in evolution of social behaviour and senescence (ageing). His group use long-term field studies of wild social vertebrates to address emerging questions in both fields. Andy leads the senescence component of the badger project, studying the evolution and mechanisms of ageing in European badgers and how the altered contact networks and immune systems of older animals impact their susceptibility to and transmission of bovine tuberculosis.

Tj McKinley | Associate Professor | University of Exeter

I am currently an Associate Professor in Bayesian Statistics in the Department of Clinical and Biomedical Sciences at the University of Exeter. My research interests include the application and development of Bayesian statistical methodology for the study of infectious disease dynamics. I have worked on diseases such as bovine tuberculosis, COVID-19, HIV, Salmonella, avian influenza and chytridiomycosis. Recently I have contributed to methodological advances / applications of methods such as data augmented and pseudo-marginal Markov chain Monte Carlo, Approximate Bayesian Computation, and History Matching with emulation, as ways of calibrating complex epidemic models to partially observed data. I am working on the compartmental modelling side of the BADGER project.

Dr Ruth Cox | Research Leader | National Wildlife Management Centre

I am Research Leader at the National Wildlife Management Centre, Woodchester Park, home to the long-running European badger ecology and disease dynamics study.

My research focuses on wildlife disease ecology, especially bovine tuberculosis in badgers. Current projects use camera traps, GPS proximity collars and genetic data to study badger population density, movement, contact rates, relatedness and population size. I am also involved in UK wildlife coronavirus surveillance.

I have a background in ecological and epidemiological research, with previous roles at Operation Wallacea Conservation Expeditions and the Universities of Oxford, Liverpool and Prince Edward Island.

Dr Clare Benton | Wildlife Project Office Team Leader | Animal and Plant Health Agency

Clare Benton is a wildlife epidemiologist at the Animal and Plant Health Agency (APHA), where she leads the Wildlife Health Field Services team. Her work focuses on how badger social structure, genetics, and inbreeding influence tuberculosis transmission, using approaches such as whole‑genome sequencing to understand host–pathogen interactions. Through the NERC‑funded project, she is keen to build on her previous research, collaborate with partners, and help translate scientific findings into practical, on‑the‑ground insights. 

Dr Matthew Silk | Research Fellow | University of Edinburgh

Having previously worked on this long-term badger research system, I am now a research fellow in the Institute of Ecology and Evolution at the University of Edinburgh where my group works at the interface of behaviour, population ecology and epidemiology. My team will be bringing our expertise on network analysis and modelling to the BADGER project to understand how social and spatial behaviour fit into the bigger picture in terms of long-term M. bovis epidemiology, as well as integrating behaviour alongside other aspects of the research including senescence and demography. 

Dr Arthur Newbury| Research Fellow | University of Exeter

I am a researcher working on advancing Bayesian statistical methods for the analysis of disease transmission and ecological dynamics. On the BADGER project, I am applying these approaches to interrogate 50+ years of data on badgers and bovine tuberculosis, with the aim of answering both evolutionary and ecological questions about the host-pathogen system. In my previous research I have drawn on controlled experiments, field data, mathematical modelling, and novel Bayesian methodology to tackle questions relating to host-plasmid transmission networks and more general community ecology.

Dr Dave Hudson | Research Fellow | University of Exeter

I am a Postdoctoral Researcher at the University of Exeter with expertise in ecological modelling, Bayesian statistics and wildlife population dynamics. My research focuses on developing and applying quantitative methods to help understand survival, movement and disease processes in wild populations with a particular interest in badgers and bovine tuberculosis. I also have wider experience developing ecological data tools and biodiversity monitoring approaches, including eDNA and passive biodiversity sensors.