Models of disease and vaccination scenarios in the UK

Our analytical research priorities range across a wide range of disease areas, with many cross-cutting methodologies and challenges; integration and analysis of diverse surveillance data; statistical methods for estimating unknown model parameters; genetic analysis of whole genome sequence data; and the development of simulation tools.

The HPRU in Modelling and Health Economics facilitates translation of its research into sustained gains in PHE’s capacity to collect, analyse, model and interpret diverse datasets by developing robust easy-to-use computer software for use by non-modellers and via a comprehensive training and capacity building programme.


Research themeDescription

Theme 1

Analysis, forecasting and response to outbreaks and acute health-system pressures
Infectious disease outbreaks cause substantial burden in communities and healthcare settings. More generally, unpredicted surges in healthcare demand (due to both infectious and non-infectious causes) require allocating expensive spare capacity, risk compromising patient care and impose extreme pressures on the NHS. This theme will elucidate key drivers of outbreak spread and healthcare demand surges, integrating these insights into forecasting and modelling/evaluation of mitigation approaches. By combining mathematical and statistical approaches with novel data sources, we will characterise the relative contributions of vaccination coverage, prior infections, outbreak response, and social behaviour to outbreak frequency and dynamics. We will also estimate the contribution of both infections and non-infectious causes (e.g. temperature fluctuations, exacerbated by climate change) to pressures on health care systems and model how these systems can be optimised. With Theme 3 we will estimate the cost of demand surges and mitigation measures. This will deliver more accurate, timely, and relevant public health forecasting.

Theme 2

Changing disease burden: drivers and intervention strategies
The UK is experiencing long-term changes in the burden of both infectious and non-communicable disease, with the ageing population (and consequent increased frequency of co-morbidities) and environmental change being key drivers. This theme will develop methods to synthesise evidence from empirical studies, surveillance, and electronic health records (EHRs), using big data to better-understand changes in the aetiology and epidemiology of disease – including interactions between environment, climate, chronic and infectious disease. It will elucidate drivers of disease trends, and design and assess cost-effectiveness of interventions to improve health and reduce inequalities in a changing world.

Theme 3

Behavioural and economic drivers of disease transmission and intervention policy effectiveness
This theme's objectives are to investigate the implications of methodological choices in economic evaluations of public health interventions; conduct a systematic assessment to understand the behavioural data requirements of health protection modelling; explore modelling and health economic analyses to respond to PHE's needs during the ongoing COVID-19 pandemic; analyse data from the contact-patterns survey for use in transmission models; explore changes since the previous POLYMOD study; explore public health interventions (e.g. COVID-19 non-pharmaceutical interventions, antibiotic use) which are beneficial in some groups but detrimental in others, and investigate vaccine hesitancy; conduct a large-scale, UK population-based survey of social mixing patterns relevant to infectious disease spread; develop models around public values, predictors and economic impacts of behaviour change; develop methods and pilot studies for collecting social contact data from target groups, including those in closed settings (e.g. hospitals, nursing homes); link contact-pattern data with Theme 1 to better-understand dynamics of outbreaks, and behavioural surveys to understand behavioural change drivers during outbreaks.

Theme 4

Capacity-building, dissemination, translation, and tools
This theme's main aim is to ensure the translation of our quantitative, model-based understanding of the drivers of public health threats into operationalised tools. These tools will need to be sufficiently robust for routine application by frontline professionals and national-level decision-makers. We have adapted the strategy to address the COVID-19 pandemic and early outputs are already contributing to the UK response.
Summary of the table's contents