Prioritizing high-risk sub-groups in a multi-manufacturer vaccine distribution program. Issue 2 (8th May 2017)

• Record Type: Journal Article
• Authors: Hovav, Sharon; Herbon, Avi
• Is Part Of: International journal of logistics management. Volume 28:Issue 2(2017)
• Page Start: 311
• Page End: 331
• Publication Date: 2017-05-08
• Subjects: Vaccination -- Distribution problem -- Influenza -- Medical supply chain -- MIP -- Prioritizing high-risk sub-groups; Business logistics -- Management -- Periodicals; Physical distribution of goods -- Management -- Periodicals; Web sites; 658.5
• DOI: 10.1108/IJLM-12-2015-0227
• Languages: English
• ISSNs: 0957-4093

Abstract

Abstract : Purpose: Annual influenza epidemics cause great losses in both human and financial terms. The purpose of this paper is to propose a model for optimizing a large-scale influenza vaccination program (VP). The goal is to minimize the total cost of the vaccination supply chain while guaranteeing a sufficiently high level of population protection. From a practical point of view, the analysis returns the number of shipments and the quantity of vaccines in each periodic shipment that should be delivered from the manufacturers to the distribution center (DC), from the DC to the clinics, and from the clinics to each sub-group of customers during the vaccination season. Design/methodology/approach: A mixed-integer programming optimization model is developed to describe the problem for a supply chain consisting of vaccine manufacturers, the healthcare organization (HCO) (comprising the DC and clinics), and the population being vaccinated (customers). The model suggests a VP that implemented by a nation-wide HCO. Findings: The benefits of the proposed approach are shown to be particularly salient in cases of limited resources, as the model distributes demand backlogs in an efficient manner, prioritizing high-risk sub-groups of the population over lower-risk sub-groups. In particular, the authors show a reduction in direct medical burden of consumers, such as the need for doctors, hospitalization resources, and reduction of indirect, non-medical burden, such as loss of workdays. Practical implications: Drawing from the extended enterprise paradigm, and, in particular, taking consumer benefits into account, the authors suggest an operational-strategic model that creates impressive added value in a highly constrained supply chain. The model constitutes a powerful decision tool for the deployment of large-scale seasonal products, and its implementation can yield multiple benefits for various consumer segments. Originality/value: The model proposed herein constitutes a decision support tool comprising operational-tactical and tactical-strategic perspectives, which logistics managers can utilize to create an enterprise-oriented plan that takes into account medical and non-medical costs.