A System Dynamics Approach for Analyzing the Behavior and Control of COVID-19 in Iran: Focus on the Sixth (Omicron) Wave

Abstract

To analyze how vaccines can affect the highest number of infections per day, the highest mortality rates, and ultimately public health efforts to combat COVID-19, we use a System Dynamics approach to simulate the behavior of the virus over time focusing specifically on Iran’s 6th wave of the virus which occurred at the beginning of 2022 due to the Omicron variant. We are able to better understand the way in which diseases spread through their ability to classify the population into specific groups, as well as identify how interventions may impact the spread of disease. In order to simulate the COVID-19 virus using the System Dynamics method, we developed a full mathematical model with 7 different classifications of population ("Vulnerable", "Suspected", "Infected", "Hospitalized", "Quarantined", "Recovered" and "Deceased"). Our model simulated COVID-19 under three different scenarios: Current Conditions; 40% Initial Vaccination Rate; and 30% Reduction in Vulnerability due to Restrictions. We also included Quarantine and Intervention classifications in our model to simulate the effects of these methods on transmission. The research supports that the use of both increased levels of vaccinated individuals and reduced exposure to COVID-19 are necessary to decrease the severity of a pandemic; The findings of this study provide evidence-based recommendations for policies to minimize the amount of infections, hospitalizations and deaths in populations with limited resources, such as Iran, through the achievement of high (> 60%) vaccination rates in addition to the implementation of other complementary measures during an omicron-like wave of COVID-19."