Novel control strategies and iterative approaches to order various COVID-19 vaccines to prevent shortages and immunisation expansion

Abstract

This paper suggests control strategies for ordering various COVID-19 vaccines and assigning vaccine recipients to immunisation stations in order to minimise shortages. To determine the optimal quantity of multiple vaccines to order, a fuzzy periodic review model is proposed. Furthermore, vaccine recipients are prioritised into different groups based on their occupation (e.g. essential workers), age cohort, co-morbidities, and pre-existing diseases. To model vaccine recipients’ waiting and improve vaccination effectiveness by reducing congestion in immunisation stations, a queuing framework is utilised. Due to the suppliers’ lack of commitment to the mass production of vaccines during the COVID-19 pandemic, the number of orders delivered to the cross-docking facility is considered uncertain. A rolling planning horizon approach is implemented using an iterative method to prevent vaccine shortages. To validate the proposed model, a case study is conducted using data from Arak City in Iran, and sensitivity analysis is performed on the model parameters. The analysis of the results indicates that the rolling planning horizon approach and the possibilistic chance-constrained programming improve network performance against operational risks, including the COVID-19 pandemic. Moreover, implementing this method reduces costs and vaccine shortages in the network compared to the current situation.