Abstract for: Using System Dynamics Models as Policy Decision Support Tools for the COVID-19 Epidemic Control in Thailand
Epidemiological modeling can be a critical tool for planning disease control strategies. However, the COVID-19 pandemic is a complex problem, with the interconnectedness of health and socioeconomic issues. Systems thinking can help create well-rounded policy options by investigating all interconnected relationships that can influence both epidemic and socioeconomic outcomes. We conducted system dynamics models of the COVID-19 epidemic control in Thailand to support policy decisions on mitigation strategies and minimizing socioeconomic impacts. Our ongoing analyses point out that many problems can be a result of adaptations of stakeholders. For instance, after the clustered epidemics at pubs, bars, and a boxing stadium in March 2020, policymakers implemented closing workplace, stay-at-home, work-from-home, and travel bans policies nationwide. Our model revealed these intensive measures cut off 77% of community transmissions within two months, but the prolonged policies created adverse socioeconomic outcomes. We also found the relaxation of control measures since May 2020 can increase domestic infections in late 2020, but still within the national healthcare capacity. Therefore, policymakers may use intensive disease control strategies only for a limited time to avoid the negative impacts on the economy and society while maintaining sufficient disease control.