We consult with government and other agencies, as well as business and other research groups to evaluate the health, health expenditure, and income impacts of population interventions through state-of-the-art simulation methods

Our services

SHINE quantifies the future health gains, health inequality impacts, health expenditure and income impacts of population interventions. Interventions such as denicotinising tobacco, health star rating labels on packaged food, eliminating cold housing, COVID-19 policy options. We specialize in preventive interventions, but we also tackle screening and early detection interventions, and health services and treatments.  We specialize in quantifying health impacts by ‘heterogeneity’, which includes differential impacts of interventions by: sex and age; ethnicity and Indigeneity; socioeconomic status; and disease risk stratification (e.g. absolute risk of a cardiovascular event or cancer diagnosis in the next five years).

For whatever evaluation we undertake, we then pull back to compare its health and cost impacts, and cost effectiveness, with other similarly conducted evaluations - using league tables and graphs.  

SHINE-Consulting is that part of SHINE that provides services to clients in policy institutions, NGOs and the private sector. These clients likely need estimates of health, cost and cost effectiveness to aid decision making and prioritisation of resources.

SHINE also provides support to other researchers, either as part of SHINE-Consulting or a more traditional collaborative approach as outlined on the SHINE-Research page. Much research stops at the point of saying something like “this putative intervention changes X by y%”. ‘X’ varies across research projects, perhaps being blood pressure, BMI, or disease incidence or severity – meaning one research output is not directly comparable to another.  SHINE can take standard research a step further, to quantifying likely health gains in a common metrics of health adjusted life years and quantifying likely health expenditure impacts, making research findings more easily comparable for both researchers and policy makers.


“The modelling work Tony, Driss and team did for us was extremely useful. They were able to model all the key policies we were considering for the Smokefree Aotearoa 2025 Action Plan, to show when each policy would get our population groups to the 5% goal. They were able to meet our requirement for a strong equity focus, by focusing on key population groups. The results were clearly presented in accessible graphs. The financial savings they modelled were key to making the case for these policies. This was an example of research being well designed and executed, with the crucial end result of influencing policy. And that policy will have a huge impact on improving outcomes. The results of their research will be of interest to a wide range of researchers and policy makers, around the world.”

-Katharine Good, Senior Advisor, New Zealand Ministry of Health

An independent review of 25 international tobacco control models rate the BODE3 tobacco model top.  This BODE3 tobacco model was developed by Professor Blakely whilst Director of BODE3, and the model is now further evolved e.g. to include vaping) and embedded in SHINE.  The SHINE PMSLT uses the same ‘back end’ as in the tobacco model, conferring a stamp of quality for any other intervention modelling SHINE does.

-Huang V, Head A, Hyseni L, O'Flaherty M, Buchan I, Capewell S, Kypridemos C. Identifying best modelling practices for tobacco control policy simulations: a systematic review and a novel quality assessment framework. Tob Control 2022

Risk prediction to target treatments and screening

SHINE is contributing to the early stages of research planning on evaluations of interventions by risk strata, for example tobacco cessation advice and other secondary prevention interventions for people stratified by risk of developing chronic obstructive pulmonary disease.

International collaborators

SHINE works with a range of international research groups on tobacco, diet and other interventions – helping to quantify health and cost impacts.