Mass Vaccination Scheduling: Trading Off Infections, Throughput, and Overtime

• 成果类型: Article; Early Access
• 署名作者: Luo, Shanshan; Shechter, Steven M.
• 署名单位: University of British Columbia
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.02958
• 发表日期: 2025
• 关键词: Appointment Scheduling; Multimodularity; health care

摘要

Mass vaccination is essential for epidemic control, but long queues can increase infection risk. We study how to schedule arrivals at a mass vaccination center to minimize a tri-objective function of (a) the expected number of infections acquired while waiting, (b) throughput, and (c) overtime. Leveraging multimodularity results of a related optimization problem, we construct a solution algorithm and apply it to a case study of COVID-19. We find that although the standard equally distributed, equally spaced schedule sits near the Pareto-optimal frontier, it is located away from a sharp elbow in the tradeoff between infections and overtime. Specifically, the elbow policy achieves approximately 38% fewer expected infections for nearly the same expected overtime. We also discuss managerial insights around the structure of the optimal schedule and compare it to the well-known dome-shaped policies found in other appointment scheduling settings.