A simulation approach for COVID-19 pandemic assessment based on vaccine logistics, SARS-CoV-2 variants, and spread rate

Abstract

Despite advances in clinical care for the coronavirus (COVID-19) pandemic, population-wide interventions are vital to effectively manage the pandemic due to its rapid spread and the emergence of different variants. One of the most important interventions to control the spread of the disease is vaccination. In this study, an extended Susceptible-Infected Healed (SIR) model based on System Dynamics was designed, considering the factors affecting the rate of spread of the COVID-19 pandemic. The model predicts how long it will take to reach 70% herd immunity based on the number of vaccines administered. The designed simulation model is modeled in AnyLogic 8.7.2 program. The model was performed for three different vaccine supply scenarios and for Turkey with ~83 million population. The results show that, with a monthly supply of 15 million vaccines, social immunity reached the target value of 70% in 161 days, while this number was 117 days for 30 million vaccines and 98 days for 40 million vaccines.