Modeling the Impact of Chronic Disease Prevalence on COVID-19 Mortality

A model of the COVID-19 epidemic in a population heterogeneous by chronic noncommunicable diseases is presented. A synthetic population is recreated, preserving the causal relationships between chronic diseases, sex, and age. Infection of individuals in the population is simulated, and the effect of the dependence of the course of COVID-19 on the presence and type of specific chronic diseases in infected individuals is modeled. The results of the epidemic modeling in the original population are compared with those in populations with reduced prevalence of chronic non-communicable diseases. Diseases whose reduced prevalence leads to the greatest reduction in COVID-19 mortality, the number of years of life lost, and the load on intensive care equipment are identified.