Concepedia

TLDR

Forecasts of CHD outcomes may be inaccurate due to erroneous assumptions or misestimated baseline data, pending validation. The study develops a computer simulation model to project future mortality, morbidity, and cost of coronary heart disease in the U.S. population. The model comprises a demographic‑epidemiologic submodel that simulates risk‑factor distribution and CHD incidence, a bridge submodel that determines outcomes of initial events, and a disease‑history submodel that simulates subsequent events, allowing users to evaluate preventive or therapeutic interventions over up to 30 years.

Abstract

A computer simulation model was developed to project the future mortality, morbidity, and cost of coronary heart disease (CHD) in the United States population. The model contains a demographic-epidemiologic (DE) submodel, which stimulates the distribution of coronary risk factors and the conditional incidence of CHD in a demographically evolving population; a "bridge" submodel, which determines the outcome of the initial CHD event; and a disease history (DH) submodel, which simulates subsequent events in persons with a previous CHD event. The user of the model may simulate the effects of interventions, either preventive (i.e., risk factor modification) or therapeutic, upon mortality, morbidity, and cost for up to a 30-year period. If there were no future changes in risk factors or the efficacy of therapies after 1980, baseline projections indicate that the aging of the population, and especially the maturation of the post-World War II baby-boom generation, would increase CHD prevalence and annual incidence, mortality, and costs by about 40-50 per cent by the year 2010. Unprecedented reductions in risk factors would be required to offset these demographic effects on the absolute incidence of CHD. The specific forecasts could be inaccurate, however, as a consequence of erroneous assumptions or misestimated baseline data, and the model awaits validation based on actual future data.

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