Optimization of Vaccination Clinics to Improve Staffing Decisions for COVID-19: A Time-Motion Study

Abstract

As the COVID-19 pandemic disturbed people’s daily life for more than 2 years, many COVID-19 vaccines have been carried forward systematically to curb the transmission of the virus. However, high vaccination tasks bring great challenges to personnel allocation. We observed nine vaccination clinics in Huzhou and Shanghai and built a discrete-event simulation model to simulate the optimal staffing of vaccination clinics under 10 different scenarios. Based on the result of the simulations, we optimized the allocation of vaccination staff in different stages of epidemic development by province in China. The results showed that optimizing staffing could both boost service utilization and shorten the queuing time for vaccination recipients. Taking Jilin Province as an example, to increase the booster vaccination rate within 3 months, the number of vaccination staff members needed was 2028, with a continuous small-scale breakout and 2,416 under a stable epidemic situation. When there was a shortage of vaccination staff, the total number of vaccination clinic staff members needed could be significantly reduced by combining the preview and registration steps. This study provides theoretical support for the personnel arrangement of COVID-19 vaccinations of a booster dose by province and the assessment of current vaccination staff reserves.