Development of a Synthetic Population Model for Assessing Excess Risk for Cardiovascular Disease Death

Evaluating the association of social determinants of health with chronic diseases at the population level requires access to individual-level factors associated with disease, which are rarely available for large populations. This study used data concerning disease status and various biological, social and other variables from Allegheny County, Pennsylvania, collected from January 2015 to December 2016, to build a semisynthetic population. The results of the study suggest that creating a geographically explicit synthetic population from real and synthetic data is feasible and that synthetic populations are useful for modeling disease in large populations and for estimating the outcome of interventions.