Presenting an efficient scenario to deal with the prevalence of COVID-19 disease using a system dynamics approach in Iran. (19th June 2023) - Emroozi, Vahideh Bafandegan; Modares, Azam; Roozkhosh, Pardis
The COVID-19 disease has adversely affected all countries in the world, due to its impact on public health and the lack of a basic solution. In this study, a model of the disease status in Iran is presented using system dynamics (SD). Even though static models that leverage mathematical programming and analytical models have been widely studied, simulation methods in the anticipation policies to deal with infectious diseases are scarce despite their potential. To this end, SD modelling is suitable to account for the dynamic and complexity of systems and supporting strategic decision-making. In this study, the SD method is used to model the behaviour of variables such as the number of patients, population of deaths, recovered population, susceptible population, social distance, observance of health issues, and so on. Finally, to prevent comprehensive outbreak, three different scenarios are proposed, and the effect of the scenarios on the problem variables in dealing with this disease is investigated.