South East Public Health Information Group Tuesday, 9 th December 2014 “Modelling Future Health Trends” Dr Jürgen C Schmidt, Principal Epidemiologist English Burden of Disease team

2 JC Schmidt, Modelling Future Health Trends Data flows in PHE

3 JC Schmidt, Modelling Future Health Trends Current modelling in PHE

What do we mean by modelling? Simulation and modelling provide public health science with means for testing and experimenting with potential improvements and future scenarios. Several types of models might be used in the future, including: models for accountability and management; population effects models; prevalence models; and systems dynamics models. Public health agencies will look to modelling and simulation techniques to understand the ‘future state’ of public health conditions under alternative demographic, economic and technological assumptions. (The future of public health: A horizon scan; 2013 RAND Corporation) 4 JC Schmidt, Modelling Future Health Trends

Current situation in PHE Infectious disease (outbreak and control) modelling, with Health Protection Prevalence modelling, with different Knowledge and Intelligence Teams, building upon previous PHO work Scenario modelling, Health Checks, with Health and Wellbeing Economic modelling Context: Knowledge strategy Digital Strategy R&D Strategy Integrated Health Intelligence Strategic Group on Modelling 5 JC Schmidt, Modelling Future Health Trends

Strategic Group on Modelling.. ensure that PHE has the capacity to deliver high-quality, robust modelling in epidemiology, health economics, [..] to answer corporate queries; this capacity is internal, and complemented as appropriate by external support; the process for identifying the need for a modelling input, and the implementation of it follows a stringent set of procedures and is in-built into individual directorates’ work programmes. This Strategic Group will produce consensus on definitions, work programmes, utilisation of resources, and capacity building.” 6JC Schmidt, Modelling Future Health Trends Chief Knowledge Officer (Lead, Brian Ferguson) Health and Wellbeing Health protection Strategy Operations Other (e.g. DPHs)

Micro-simulation Computer model of a specified population Simulations specifically target relationship between individuals’ evolving risk factors and disease incidence. Risk factor distributions determined by past and current trends Model can simulate and compare the impact and cost of various public health interventions. Individuals can give birth and die in the model, they can be exposed to risk factors and contract, survive and die from particular diseases based on risks or probabilities. Events compete to occur in each simulated life Individual life trajectories are simulated until death. 7JC Schmidt, Modelling Future Health Trends

UK Health Forum simulation model Obesity-related diseases: e.g. CHD, stroke, T2DM, cancers Smoking-related diseases: CHD, COPD, stroke, cancers Risk factors scenarios (obesity, smoking, salt consumption and blood pressure) ‘steady progress’, ‘best case’, ‘worst case’. Prevalence of risk factors by age group and sex, social class and income quintile Incidence and prevalence cases avoided or gained given each agreed scenario Quality Adjusted Life Years (QALY) and Disability Adjusted Life Years (DALY) Indicative impact on healthcare/public sector costs 8 JC Schmidt, Modelling Future Health Trends

9 “steady progress “ Projected overweight and obesity prevalence in year old males, steady progress

10 JC Schmidt, Modelling Future Health Trends “worst case” Projected overweight and obesity prevalence in year old males, worst case

11 JC Schmidt, Modelling Future Health Trends Cumulative incidence cases added and avoided per 100,000 relative to steady progress scenario in 2034

12 JC Schmidt, Modelling Future Health Trends Costs added and avoided relative to steady progress scenario in 2034

Health Checks to create a microsimulation model of the Health Checks process how do changes to attendance at Health Checks (either by changing inclusion criteria or other targeting) affect both the risk profile of those attending and health outcomes baseline population taken from HSE individuals are given trajectories in metabolic risk factors over time initially focus on Qrisk to cardiovascular diseases (IHD and stroke considered separately), diabetes, lung cancer and dementia working but not finalised version of the model February 2015 report by May; journal article submitted soon after model publicly available with a graphical user interface (GUI) 13 JC Schmidt, Modelling Future Health Trends

Current issues “All models are wrong” Clarity of scope Data Assumptions Technical limitations Technical expertise IT firepower Univariate model, no interaction, no feedback loops, no multiple conditions or effects, the idea that each aspect of a complicated disease control strategy can be managed and evaluated separately 14JC Schmidt, Modelling Future Health Trends

What next UK Health Forum MIDRIF model multi-disease, multi-risk factor micro-simulation model simulating the lives and related medical costs of virtual people in the presence of Multiple Interacting Diseases and Risk Factors. Diseases are modelled with varying complexity depending on the availability of suitable data. Complex diseases can have multiple dynamic stages. Multi-stage diseases modelling allows for more accurate cost analyses and the assessment of preventative health care interventions. 15JC Schmidt, Modelling Future Health Trends

PHE‘s Population Health model: Definition: health outcomes of a group of individuals, and their distribution, factors influencing population health, and the policy and programme implications of the population health model identified simultaneous impact of multiple factors requires a multi-level model a given factor may influence health differently according to different environmental, social economic conditions, and other factors. Importance of attributable risk at population level rather than the relative risk at individual level population health model to include social factors (inequalities, support, cohesion, structure, stress), natural environment, socioeconomic factors (material resources at the individual level, income inequality at the contextual level), biology and early childhood development built environment (e.g., transportation) 16 JC Schmidt, Modelling Future Health Trends

Population Health Model interrelated conditions and factors that influence the health of populations over the life course, identifies systematic variations in their patterns of occurrence, applies the resulting knowledge to develop and implement policies and actions to improve the health and well being of those populations 17JC Schmidt, Modelling Future Health Trends Population health is “the aggregate health outcome of health adjusted life expectancy (quantity and quality) of a group of individuals, in an economic framework that balances the relative marginal returns from the multiple determinants of health. This definition proposes a specific unit of measure of population health and also includes consideration of the relative cost-effectiveness of resource allocation to multiple determinants.

18 Data provided JC Schmidt, Modelling Future Health Trends