Summary
Develop a mathematical simulation model using a systems science approach to explore the impacts of social determinants of health (SDOH) on chronic disease incidence, mortality, and disparities over 5-30 years, and create a multi-user, web-based, public-use version of the model for CDC and public health partners.
What they want
The project involves developing a systems science-based mathematical simulation model to integrate risk and SDOH factors for heart disease, stroke, diabetes, CKD, cancer, and Alzheimer’s disease, accounting for interconnectedness and feedback loops. It will incorporate evidence-based strategies for addressing SDOH in five priority areas: built environment, community-clinical linkages, food and nutrition security, tobacco-free policy, and social connectedness. The model will generate synthetic populations representing SDOH-related characteristics (e.g., race/ethnicity, sex, age, income, education, and urban vs. rural status) and chronic disease risk factors for selected county/state populations, calibrated to national surveillance data. A multi-user, web-based, public-use version of the model will be developed to operate on CDC’s web platforms, allowing users to run scenarios to explore which combinations of programs, policies, or practices (PPPs) would have the greatest impact on reducing chronic disease disparities and outcomes, and how PPPs compare in terms of costs and cost-effectiveness.
Deliverables
- A mathematical simulation model integrating risk and SDOH factors for chronic diseases
- A multi-user, web-based, public-use version of the model
Technical requirements
- Systems science approach
- Mathematical simulation model
- Integration of risk and SDOH factors for heart disease, stroke, diabetes, CKD, cancer, and Alzheimer’s disease
- Accounting for interconnectedness and feedback loops between SDOH and chronic disease
- Incorporation of evidence-based strategies for addressing SDOH in five priority areas (built environment, community-clinical linkages, food and nutrition security, tobacco-free policy, social connectedness)
- Generation of synthetic populations representing SDOH-related characteristics (race/ethnicity, sex, age, income, education, urban vs. rural status) and chronic disease risk factors
- Model calibration to national surveillance data
- Multi-user, web-based, public-use version
- Operation on CDC’s web platforms
