Agent-Based Simulation Modeling For Covid-19 Vaccination Policies: Single-Dose And DoubleDose Applications


Gül N. N. , Hasgül Z., Aytöre C.

40. Yöneylem Araştırması ve Endüstri Mühendisliği Kongresi, İstanbul, Turkey, 4 - 07 July 2021, pp.98-99

  • Publication Type: Conference Paper / Summary Text
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.98-99

Abstract

In this study, the goal is to compare double and single-dose vaccination policies. What-if analyses for various vaccine efficacies and age group prioritization strategies are conducted. Interpretations for scenarios such as different population demographics and vaccine availability are explored using agentbased modeling and simulation. Many countries have been conducting various vaccination studies against the Covid19 virus, which emerged in December 2019 and has affected the whole world. Vaccines are known to be the most effective way to manage pandemics. At the end of 2020 multiple vaccines for Covid19 have been discovered. In general, Covid19 vaccines are applied in two doses. Vaccines provide protection starting from the first dose; nonetheless it becomes fully effective after the second dose. With a single dose application, more people can be covered however with a double dose application higher protection is provided. Thus, in countries with limited vaccine resources, single-dose application strategy can be considered. Around the world, different countries follow somewhat similar policies for vaccination rollout. Commonly, senior citizens are given priority and receive double-dose of vaccines. On the other hand, it is argued that younger individuals spread the disease more. Therefore, prioritizing to vaccinate super spreaders could be more effective to take the pandemic under control. As of today, there are still discussions about how benefits from vaccines can be optimized. Furthermore, it is expected that Covid19 vaccinations will be required to be applied annually. It can be concluded that, determining the best vaccine policy is still a recent and important problem. In real life, comparing the results of several policies is not possible as it has real consequences. Under these circumstances, modeling and simulation techniques are effective tools. Among different simulation methodologies, this study considers an agent-based modeling approach. Since; the mechanisms that lead to the pandemic are dynamic, the individuals interact with each other to spread the disease, and their interactions are related to the outcome of interest. To observe the results, the model is simulated using the NetLogo software.