Introduction to the Epidemiology Team
This article is part of a series: Bennett Institute teams
What is epidemiology?
Epidemiology is the study of how, when, and why medical conditions and diseases occur, and identifying why some groups of people are more or less likely to have poor health. The ultimate goal of epidemiology is to guide public health, health policy, and medical care to improve people’s health and wellbeing. Good epidemiology research is often collaborative, as it requires not just a good understanding of the underlying biological, social, and/or behavioural factors driving health, but also a strong grasp of the methods deployed to collect and analyse relevant data.
Who are we?
The Epidemiology Team consists of:
- Will Hulme (Team Lead) has been at the Bennett Institute since April 2020, following a PhD and postdoctoral roles at the University of Manchester. His work focuses on improving how routinely-collected health data can be used for prediction and inference, and improving transparency and reusability of research data and code.
- Colm Andrews has 5 years of experience working with NHS data as a data analyst with the Eye Research Group Oxford and medical statistician with the Cancer Epidemiology Unit in the Nuffield Department of Population Health. He has an MSc in Evidence Based Healthcare (University of Oxford).
- Millie Green is interested in improving how routinely-collected health is used to deliver urgent answers on key clinical and public health questions, by building exploratory and predictive models to aid future decision making processes. She has an MSc in Mathematical Sciences and a PhD in statistics/pharmacoepidemiology (University of Bath).
- Linda Nab is interested in causal inference from observational data and associated methodology and is keen to improve the reproducibility of epidemiologic research. She has an MSc in Epidemiology (Wageningen University) and recently received her PhD degree from Leiden University (the Netherlands) which was on measurement error in epidemiologic research.
- Andrea Schaffer is experienced in using routinely collected data to evaluate the impact of health policy on outcomes and is interested in quasi-experimental study designs. Following Master’s degrees in Epidemiology (McGill University) and Biostatistics (University of Sydney), she completed a PhD in pharmacoepidemiology from the University of New South Wales (Australia).
- Alex Walker is the Director of Research. He has an interest in time course analysis, risk stratification, prognosis modelling and novel computational methods, and builds tools to make electronic health record research more transparent, reproducible and reusable. He completed his PhD in the Division of Epidemiology and Public Health at Nottingham, preceded by a MSc in Oncology.
What do we do?
We use data platforms and tools run by the Bennett Institute to conduct epidemiology research, collaborating closely with external groups who provide additional clinical and methodological expertise and have hands-on experience with the national response to the COVID-19 pandemic in the UK.
Our focus so far has overwhelmingly been on using the OpenSAFELY platform to contribute to our understanding of the COVID-19 pandemic, including prevention, treatment, and health outcomes. Our research has addressed important, timely questions such as: how effective is the vaccine against COVID-19, and does its protection wane over time? which antiviral is most effective at preventing poor COVID-19 outcomes? how has COVID-19 mortality changed over the pandemic and who is most at risk?
Epidemiology research has the potential to impact health policy and medical care and so it is important that it is done well. An important part of our work is advocating for better, more transparent, ways of conducting research and developing tools to facilitate this. By improving health data research infrastructure and changing norms, we want to make it easier to do good research—that is, research that is reliable, reproducible, but also maintains the privacy of people whose data we are accessing.
The primary outputs of the Epidemiology Team are research papers and reports. An overview of research activity at the Bennett is covered in a previous blog. Consistent with our deep commitment to open science, all analytic code is publicly available on the OpenSAFELY Github page. Below are some highlights of our recent work:
Vaccine effectiveness research
The Epidemiology Team has been heavily involved in evaluating the effectiveness of COVID-19 vaccines, answering questions that were not addressed in randomised controlled trials. One such study published in the BMJ in 2022 (Comparative effectiveness of ChAdOx1 versus BNT162b2 covid-19 vaccines in health and social care workers in England: cohort study using OpenSAFELY) was one of the first head-to-head comparisons of the BNT162b2 mRNA and ChAdOx1 vaccines, finding no substantial differences in SARS-CoV-2 infection or COVID-19-related outcomes up to 20 weeks post-vaccination among health and social care workers. In collaboration with the London School of Hygiene and Tropical Medicine (LSHTM), University of Bristol, and University of Harvard, the team applied sophisticated methodology exploiting the concurrent roll-out of both vaccines in this high risk population.
Effectiveness of monoclonal antibodies and antivirals in community settings
In December 2021, new COVID Medicine Delivery Units (CMDUs) were launched across England, offering antiviral medicines and neutralising monoclonal antibodies (nMABs) to patients with COVID-19 at high risk of severe outcomes. Complementing work from the NHS Service Analytics Team which evaluated the uptake of these medicines, the Epidemiology Team collaborated with the LSHTM to evaluate the comparative effectiveness of molnupiravir versus sotrovimab, which had not been evaluated in randomised clinical trials. This study, published in BMJ in 2022 (Comparative effectiveness of sotrovimab and molnupiravir for prevention of severe covid-19 outcomes in patients in the community: observational cohort study with the OpenSAFELY platform), found that non-hospitalised high-risk adult patients with COVID-19 who received sotrovimab were at lower risk of severe COVID-19 outcomes than those receiving molnupiravir. This work had a direct impact on the 2023 NICE recommendations for COVID-19 treatment.
Changing COVID-19 mortality over the course of the pandemic
Since the start of the COVID-19 pandemic, differences in preventive measures, introduction of vaccination programmes, and changes to the circulating SARS-CoV-2 variants have led to changes in mortality risk over time. A recent study accepted in Lancet Public Health (Changes in COVID-19-related mortality across key demographic and clinical subgroups: an observational cohort study using the OpenSAFELY platform on 18 million adults in England) showed that while there was a consistent decrease in mortality in subsequent waves across all subgroups, the largest decreases in risk were for people at high risk of poor COVID-19 outcomes and thus prioritised for vaccination, such as older people and those with certain comorbidities (e.g. neurological conditions, learning disabilities). An important finding however is that some clinical subgroups remained highly vulnerable, particularly people with conditions associated with impaired immune response or low vaccination coverage. This work was used by the UK Department of Health and Social Care Therapeutics Clinical Review Panel to identify patient groups that warranted further assessments of their risk of severe COVID-19 disease (link).
As the COVID-19 landscape is constantly changing, we continue to work on evaluating the uptake, effectiveness and safety of new COVID-19 therapies and preventive measures (such as booster vaccinations), as well as developing new methods for open, reproducible research. Please keep an eye on this blog where we will be describing our newly published research. We are always keen to find new collaborators, so please do get in touch if you would like to work with us!