Abstract for: Simulation-based What-if Analysis for Georgia Vaccination Distribution Policy
The global pandemic of COVID-19 has exposed how under-prepared healthcare systems and their interconnected systems are to deal with such an event. Our focus in this paper is to implement system dynamic modeling to assess policies aimed to prevent the transmission of the virus and to save lives in the state of Georgia. In our scenario analysis, we utilize SEIRD-based model and connect it to a vaccine distribution model composed of multiple variables that account for timing, efficiency, willingness, and prioritization of different population categories. The hypotheses that we test in our connected model are: (1) distribution of vaccine solely based on age will result to lower death rate, but it might increase the community spread within the first months and (2) distribution of first doses of vaccine to a wider population while postponing the second dose, will result in lower death rates and lower community spread.