Discrete event simulation of a drive-through COVID-19 mass vaccination model: senior population prioritization strategies

  • Anastasia Angelopoulou ,
  • Sonipriya Paul
  • a,b Columbus State University, 4225 University Avenue, Columbus, GA, 31907, USA
Cite as
Angelopoulou A., Paul S. (2021). Discrete event simulation of a drive-through COVID-19 mass vaccination model: senior population prioritization strategies. Proceedings of the 33rd European Modeling & Simulation Symposium (EMSS 2021), pp. 260-265. DOI: https://doi.org/10.46354/i3m.2021.emss.036

Abstract

The COVID-19 pandemic has disrupted the normal operations of countries around the world, which applied different containment and mitigation policies, such as mask-wearing, social distancing, quarantine, and lockdowns, to limit the spread of the virus. More recent mitigation efforts include vaccination strategies, since various vaccines have been authorized for emergency use for the prevention of COVID-19. In fact, vaccination is one of the best proactive mitigation strategies against the virus spread. Mass vaccination strategies have been undertaken by multiple research and development teams in the past when the public needed to be vaccinated on a large scale due to a pandemic, such as the seasonal flu or H1N1. Drive through vaccination, in particular, is more convenient and safer than walk-in vaccinations in clinics due the nature of the contagious virus. In this paper, we present the implementation of a discrete event simulation model of a drive through clinic for mass vaccinations of patients, while prioritizing the senior population. The simulation output is examined in terms of average waiting time in the queue to get vaccinated, number of patients getting vaccinated per week, and utilization of the medical resources. The results are expected to provide insights into the allocation of medical resources across lanes and prioritization strategies for the senior population to achieve higher vaccination rates, while reducing the waiting time in queue.

References

  1. Asgary, A., Najafabadi, M. M., Karsseboom, R., & Wu, J. (2020, December). A drive-through simulation tool for mass vaccination during COVID-19 pandemic. In Healthcare (Vol. 8, No. 4, p. 469). Multidisciplinary Digital Publishing Institute.
  2. Asgary, A., Valtchev, S. Z., Chen, M., Najafabadi, M. M., & Wu, J. (2021). Artificial Intelligence Model of Drive-Through Vaccination Simulation. International journal of environmental research and public health, 18(1), 268. 
  3. Gupta, A., Evans, G. W., & Heragu, S. S. (2013). Simulation and optimization modeling for drive-through mass vaccination–A generalized approach. Simulation modelling practice and theory, 37, 99-106.
  4. Mykoniatis, K. (2015). A Generic Framework For Multi-Method Modeling and Simulation of Complex Systems Using Discrete Event, System Dynamics and Agent Based Approaches. 
  5. Mykoniatis, K., & Angelopoulou, A. (2020). A modeling framework for the application of multi-paradigm simulation methods. SIMULATION, 96(1), 55-73.
  6. Rambhia, K. J., Watson, M., Sell, T. K., Waldhorn, R., & Toner, E. (2010). Mass vaccination for the 2009 H1N1 pandemic: approaches, challenges, and recommendations. Biosecurity and bioterrorism: biodefense strategy, practice, and science, 8(4), 321-330.
  7. Reid, D. E. (2010). What are the Efficiencies of a Mass Vaccination Drive-through Clinic Compared to a Walk-in Clinic?. National Fire Academy. 
  8. Rega, P., Bork, C., Chen, Y., Woodson, D., Hogue, P., & Batten, S. (2010). Using an H1N1 vaccination drive-through to introduce healthcare students and their faculty to disaster medicine. American journal of disaster medicine, 5(2), 129-136.
  9. Shen, Y., Li, C., Dong, H., Wang, Z., Martinez, L., Sun, Z.,... & Xu, G. (2020). Community outbreak investigation of SARS-CoV-2 transmission among bus riders in eastern China. JAMA internal medicine, 180(12), 1665-1671.
  10. Statista Research Department (2021). U.S. - seniors as a percentage of the population 1950-2050. Online. Available at https://www.statista.com/statistics/241488/population-of-the-us-by-sex-and-age/ [Accessed on April 6, 2021]
  11. van de Kracht, T., & Heragu, S. S. (2020). Lessons from Modeling and Running the World’s Largest Drive-Through Mass Vaccination Clinic. INFORMS Journal on Applied Analytics.
  12. Weiss, E. A., Ngo, J., Gilbert, G. H., & Quinn, J. V. (2010). Drive-through medicine: a novel proposal for rapid evaluation of patients during an influenza pandemic. Annals of emergency medicine, 55(3), 268-273.
  13. Wiggers, J., van de Kracht, T., Gupta, A., & Heragu, S. S. (2011). Design and Analysis of a Simulation Model for Drive-Through Mass Vaccination. In IIE Annual Conference. Proceedings (p. 1). Institute of Industrial and Systems Engineers (IISE).
  14. Wood, R. M., Moss, S. J., Murch, B. J., Davies, C., & Vasilakis, C. (2021). Improving COVID-19 vaccination centre operation through computer modelling and simulation. medRxiv.