Vaccination programmes need to be stress-tested by independent mathematical models before they are rolled out to the public. The problem is that the relationship between how many people get vaccinated and how far a disease spreads is not straightforward—it is non-linear, and factors like age, geography, and behaviour all interact in complex ways. This research will build bespoke infectious disease and health economic models to provide an alternative, transparent opinion on the modelling work already done by the UK Health Security Agency. The team will produce policy-ready reports that lay out every assumption, data gap, and uncertainty, so decision-makers can see exactly where conclusions might be fragile. If successful, this programme will give the Department of Health a second, independent lens on vaccine strategy—catching blind spots in existing models before they lead to suboptimal policy. The impact is quiet but critical: better-targeted vaccination campaigns, fewer preventable infections, and public money spent where it delivers the most health benefit. This is not fundamental science; it is applied modelling that directly shapes how the NHS and government protect the population.
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Background. Vaccination programmes are a fundamental part of public-health services and provide individual-level and population-level defence against a number of pathogens. However, new vaccines are being continuously developed and evaluation in terms of potential impact is required. Mathematical and health economic modelling play vital roles in determining the likely dynamic health implications of vaccination and the associated costs and benefits. Predictions of impact are complicated by the non-linear relationship between vaccination and prevalence and the interplay between multiple heterogeneities. Detailed bespoke infection and economic models are therefore required to provide robust advice and assess the impact of multiple uncertainties. Aims. The primary aim is to provide an alternative and complementary opinion on both the infectious disease dynamic modelling and health economic modelling that is undertaken by Health Protection England. This will be presented in the form of policy-ready reports that provide a transparent account of the modelling assumptions, knowledge and data gaps, and how these could affect the conclusions. Research Plan and Methods. The precise infections and scenarios that will be modelled in this programme will be driven by DH policy makers through HPAT. Therefore, the research plan and methods require considerable flexibility to respond to rapidly changing demands. However, there are several key elements that form the core of our proposal: Regular meetings with DH to define current priorities and future work programme. Transparency of methodology and assumptions, playing particular attention to knowledge and data gaps. The use of peer-review publication and other methods as mechanisms to validate our modelling assumptions. The application of cutting-edge research methods for handling variability, uncertainty and heterogeneity within the models, and for indicating the need for and value of additional research in each. The development of novel modelling approaches to determine the impact of vaccination in heterogeneous populations. Retrospective assessment of model predictions once sufficient data become available on the impact of a vaccine programme. A symbiotic approach to each project that draws upon the methodological approaches of each discipline represented within our multidisciplinary team. Research Team. Prof Keeling (Lead Applicant) holds a joint position in the Mathematics Institute and School of Life Sciences, and is director of the WIDER (Warwick Infectious Disease Epidemiology Research) Centre. He has published over 90 peer-reviewed articles on infection dynamics, with a particular focus on the impact of control measures. Keeling is a member of JCVI and SPI-Modelling for DH. Prof Petrou has substantial experience of leading high quality economic evaluations and research alongside large Phase III clinical trials and within health technology appraisal reviews. His work has encompassed a range of decision-analytic modelling techniques. He is a member of the ISPOR Taskforce developing new reporting standards for health economic evaluation, including modelling-based evaluations. Prof Medley has researched and published on infectious disease epidemiology since 1983, including many relevant infectious diseases (e.g. RSV, HBV) in 150 scientific, peer-reviewed publications. He has advised the DH on HIV/AIDS and vCJD, was a member of a NICE CJD Advisory Sub-Committee (CJDAS), was a member of SEAC, and is current a member of ACDP TSE Risk Assessment sub-group. Prof Martin Underwood will provide detailed medical advice from a GP perspective Dr Sophie Staniszewska will advise on Patient and Public Involvement. Potential Impact. In providing an alternative and complementary opinion to the modelling work of HPE, the proposed programme of work will help to address potential concerns over model uncertainty and provide an unbiased counterpoint to the modelling work o
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