The Pandemic Institute (TPI) has awarded funding across the partnership to employ key research or technical staff to carry out a range of pandemic preparedness projects and be ready to pivot to respond rapidly against any new threat that arises. In this post, Dr Edward Hill shares his research to date, and plans for the future as a TPI Strategic Post.

Why is your work important?

I’m interested in understanding how people’s behaviour affects the spread of diseases and how we can better respond to outbreaks—whether in humans, animals, or plants. In the past, disease models have often struggled to fully take into account how people actually behave during a health emergency. My work aims to improve this by combining maths, computer simulations, and real-world data to build better models and test what might happen under different scenarios, like introducing new treatments or public health measures.

Working with experts from different fields is also a big part of what I do. By bringing together knowledge from science, technology, and public health, we can build more realistic and useful tools to help prepare for future outbreaks. I’m part of the Civic Health Innovation Labs (CHIL) at the University of Liverpool, which uses local data and technology to tackle big health challenges and make a positive impact in the Liverpool City Region and beyond.

What do you enjoy most about your work

It is a privilege to be in a position where our scientific work can help contribute to health policy and have a tangible impact on global health.

Through my research in infectious disease modelling and health protection data science, I work on a range of issues that affect public health, animal health, and even plant health. This includes helping to evaluate the benefits and costs of vaccination programmes, studying diseases that can spread between animals and humans (called zoonoses), and supporting the “One Health” approach—which recognises that the health of people, animals, and the environment are closely connected.

Another important part of my work is helping to train and support the next generation of researchers, so we’re better prepared for future health challenges. I’m part of the Joint UNIversities Pandemic & Epidemiological Research Partnership (JUNIPER), a UK-wide network of researchers working together to improve how we use science and modelling to inform decisions during disease outbreaks. To find out more about the JUNIPER Partnership, visit https://maths.org/juniper/

What are you working on now?

I am building on my expertise in studying health problems that involve aspects of behaviour. Here are three activities I’m currently involved in:

• As part of the NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, I’m leading a PhD project focused on improving how vaccination campaigns reach people. The project combines insights from behaviour, disease modelling, and artificial intelligence to help make these efforts more effective.
• I’m guest editing a special issue of a scientific journal that focuses on behavioural epidemiology—how people’s actions influence the spread of disease. This collection brings together research that uses data, maths, and statistics to better reflect real-life behaviour in health models (Papers from the Special Issue are available at https://www.tandfonline.com/journals/tmls20/collections/Behavioural_Epidemiology).
• I am co-organising an Isaac Newton Institute for Mathematical Sciences satellite programme on ‘Maths of Human Behaviour: modelling sociality, mobility and protectionism’ https://www.newton.ac.uk/event/mhb/). This 4-week programme takes place in the summer of 2026 at the University of Nottingham. Our vision for the programme is to connect researchers who have shared interests in improving behavioural realism in their models. By bringing mathematicians, modellers, statisticians and data-scientists together with social scientists with expertise on drivers and determinants of behaviours and behavioural change, this programme will facilitate the development of mathematical and statistical frameworks for capturing realistic behaviour in modelling approaches.