This is the first of a series of meetings aiming to foster collaboration between the ‘health sciences’ in Warwick (WMS (applied health and biomedicine), Psychology, CIDD) and the physical sciences (Mathematics, Statistics, Computer Science, Physics, WMG and Engineering).

This meeting focuses the interface of applied health and mathematical sciences (in the broadest sense), aiming to build up an awareness of what is going on within Warwick with a view to potential collaboration. The interest is in health problems (and data sets) where more sophisticated data analysis techniques or modelling might be usefully exploited. Please come and participate.

Please register before 14th May as this helps us anticipate numbers for refreshments and lunch, thank you. If you have questions please contact Suki Soggi (Sukhwinder.Soggi@warwick.ac.uk).

Location: GLT 3, Gibbet Hill.

Programme (provisional).

10.00 Tea/coffee biscuit.

Session 1. 10.30-12.15

10.25 Wellcome.

10.30 Petra Hanson (WMS). Digital tools in specialist weight management services.

10.50 Matt Keeling (Mathematics/SLS). SBIDER and COVID-19 modelling.

11.10 Dan Lasserson (WMS). Operations Research in the acute medical care pathway.

11.30 Nigel Burroughs (Mathematics) Predicting time to pregnancy and risk of miscarriage.

11.50 Charlie Craddock (CTU). TBA.

12.15 Lunch

 

Session 2. pm.

1.20 Keith Abrams (Statistics/WMS). Statistical Challenges in Health Technology Assessment (HTA).

1.40 Domenico Giacco (WMS). Social networks and mental health.

2.00 Jilka Sagar (WMS). Data science applications in global mental health

2.20 Julia Brettschneider (statistics). TBA.

2.40. Fern Terris-Prestholt. Using Discrete Choice Experiments (DCE) to incorporate user uptake behaviours in epi models.

3.00 Cake tea/coffee

Organisers: Nigel Burroughs (Mathematics), Amy Grove (WMS).

Contact: Nigel Burroughs

---

Abstracts.

Petra Hanson. Digital tools in specialist weight management services. In the UK, a quarter of adults live with obesity. Treatment of obesity and associated ill health was estimated to cost NHS £6.5bn in 2022, with annual full cost of obesity in the UK to be estimated at £58bn. The population eligible for referral to NHS specialist weight management services (WMS) vastly supersedes current capacity (~ 4million eligible but 35,000 capacity). The efficacy of WMS has been modest with 50% of patients achieving 5% weight loss over 6-12 months. Innovative approaches are needed to provide efficient and timely treatment pathways in WMS, increase access to pharmacotherapy for people living with obesity, and reduce existing health inequality. This talk will cover latest advances in digital innovations for specialist weight management services and potential collaboration opportunities.

Matt Keeling. SBIDER and COVID-19 modelling. This talk will highlight the work that SBIDER did during the COVID-19 pandemic, and its outreach to policy. I’ll talk about our new national epidemiological modelling network that has arisen from the pandemic work. I will also discuss the challenges of real-time projections, the successes and the areas for future work.

Dan Lasserson. Operations Research in the acute medical care pathway. Many challenges facing acute care models lie in understanding how best to deploy a limited resource to best effect. Acute Hospital at Home care models deliver hospital level diagnostics and intravenous treatments to patients at their own home or care home, utilising a small number of mobile staff with varying skillsets. This poses a significant logistics challenge which the NHS is ill equipped to solve. OR methodology could provide critical support in the development of novel care models that are trying to reduce the pressure on hospital beds.

Keith Abrams. Statistical Challenges in Health Technology Assessment (HTA). Health Technology Assessment (HTA) is concerned with which health technologies (pharmaceuticals, devices, diagnostics & procedures) are the most clinically and cost-effective, in which clinical context/setting, and for which patients. The evidence generated by HTA is used by health policy decision-makers, such as the National Institute for health & Care Excellence (NICE) in England and Wales, to make policy decisions about which health technologies should be used (and paid for) routinely within their health systems, e.g. NHS. However, there are many and varied statistical challenges in generating such HTA evidence. This talk will discuss the most important ones currently, and look forward to future challenges. Current challenges include the use of observational Real World Evidence (RWE) studies to generalise the results of Randomised Controlled Trials (RCTs) to broader patient populations, alternative comparators & outcomes (including longer time horizons), for both individual RCTs and within evidence syntheses, i.e. (network) meta-analyses. Future challenges include the increased use of basket or tumour agnostic trials in cancer settings, the increased availability of digitally enabled and/or routine data collection in research/evaluation studies, and the evaluation of data-driven/AI health technologies. Finally the implications for statistical/data science methods development, evaluation and translation associated with these challenges will be discussed.