Discrete event simulation model of sudden cardiac death predicts high impact of preventive interventions

Sudden Cardiac Death (SCD) is responsible for at least 180,000 deaths a year and incurs an average cost of $286 billion annually in the United States alone. Herein, we present a novel discrete event simulation model of SCD, which quantifies the chains of events associated with the formation, growth, and rupture of atheroma plaques, and the subsequent formation of clots, thrombosis and on-set of arrhythmias within a population. The predictions generated by the model are in good agreement both with results obtained from pathological examinations on the frequencies of three major types of atheroma, and with epidemiological data on the prevalence and risk of SCD. These model predictions allow for identification of interventions and importantly for the optimal time of intervention leading to high potential impact on SCD risk reduction (up to 8-fold reduction in the number of SCDs in the population) as well as the increase in life expectancy.