wp4

Data entry, model analyses and validation in Palestine, Syria, Tunisia and Turkey

The work package is led by Simon Capewell with assistance from Martin O'Flaherty at Liverpool University.

Ojectives:

- To enter data obtained in WP2 into generic IMPACT models, developed and tested in WP3.
- To create parallel IMPACT models for each partner country (Palestine, Syria, Tunisia and Turkey).
- To validate each partner country's model by comparing model estimates with observed estimates of the disease burden or trends in the country, or with estimates from other models of studies using different methodologies (e.g. WHO Global Burden of Disease study).

Achievements
Data sources     
National and local surveys; routine national and WHO statistics were identified and reviewed.


Analysis                
Data on populations, mortality, patient groups and numbers, treatments and risk factor trends were collated and critically appraised. 
Data were integrated and analysed using a previously validated CHD policy model.


Disease modelling
The IMPACT CHD model estimates were apparently able to explain approximately 75%-100% of the observed mortality changes in the four countries.

We also developed a DIABETES model for adults in each population.
The model integrates population, obesity and smoking trends to estimate future diabetes prevalence using a Markov approach.
Model parameters were derived from the literature, except for diabetes incidence which was estimated using DISMOD II from the baseline estimation of diabetes prevalence. 
The final model outputs were reasonably comparable with subsequent diabetes prevalence surveys conducted in 2010.

We developed a novel STROKE model to explore policy questions regarding the prevention and treatment of ischemic strokes. We first developed the model using high quality Dutch data, for testing and validation purposes.

Currently the model allows the user to simulate a cohort of a national population over 30 years. One can then calculate incremental outputs comparing a baseline model to a series of policy scenarios, including primary prevention (both at population and high risk levels), acute stroke treatments and secondary prevention.

The model thus has the ability to run “what if Scenarios” and provide as outputs number of deaths, number of life years and life expectancy in the cohort.  The initial national versions of the model are using local data for the population structure and transition probabilities reflecting stroke incidence and CVD mortality and using uptakes from hospital and community sources already available from work done in the project.  However, transitions probabilities for stroke clinical pathways are derived from the Dutch development model.

The four teams are currently working on populating initial versions of the model.
Further validation of the the Dutch model is also underway. 

Emerging results and tentative conclusions: The CHD and diabetes models provide reasonable estimates of the current CHD and diabetes burden,  compared with contemporary independent prevalence surveys in the same population.
Countries in the Eastern Mediterranean region have reached different stages in the CHD and diabetes epidemics.

Diabetes burden is now a significant public health challenge, and our model predicts that its burden will increase significantly in the next two decades.  Tackling obesity and other diabetes risk factors needs therefore urgent action.

CHD death rates are rising in Tunisia and Syria, as in many other middle income countries but Turkey and Palestine demonstrate clear mortality falls as in most Westernised countries. These mortality trends mainly reflect changes in major cardiovascular risk factors, modestly alleviated by treatment contributions. However, there is no room for complacency. Obesity and diabetes levels are rising across the Eastern Mediterranean and globally.
Powerful prevention policies exist and should now be implemented for tobacco control and healthier diets.     

The CHD, Diabetes and stroke models may therefore represent a useful suite of policy decision tools that can be employed to gain insights in controlling the increasing burden of non-communicable disease in Eastern Mediterranean  populations.