Capacity Assessment and Planning of COVID-19-Vaccination Sites: A Mathematical and Simulation Approach

Abstract

Background: To control and minimize the spread of COVID-19, vaccination among the population to achieve herd immunity is important. However, optimizing the vaccination capacity for facility-based vaccination sites and mass vaccination sites is challenging. Additionally, evaluating the impacts of different patient flow arrangements for mass vaccination sites is hard in practice. A study to answer those questions is needed to improve the operation of COVID-19 vaccination sites and reduce the waiting time for patients and cost. Methods: Initially, the time-motion method was used to evaluate the real-world health facilities’ COVID-19 vaccination capacity in China. Then, optimization models were built to determine the optimal capacity levels for different vaccination sites based on the time-motion data. Furthermore, the impacts of different patient flow arrangements were investigated in mass vaccination sites through a discrete event simulation approach. Results: The optimization models established in this study provide tools for policymakers to optimize the capacity level of walk-in COVID-19 vaccination sites for different vaccination targets while considering the cross-infectious risk. Compared to facility-based vaccination sites, a single mass vaccination site will require fewer service desks than using multiple facility-based vaccination sites. The mass vaccination site arranged with an optimal capacity level using a pooled queue tends to be more flexible compared to real-world arrangements. Conclusions: This research developed a modeling framework that can help to optimize the service capacity level, identify the trade-off points for vaccination planning, and reduce the cost of operating the vaccination sites to aid in the planning of the COVID-19 vaccination site.