ABSTRACT
This chapter develops a novel integrated approach for optimizing costs and public benefits within the influenza vaccine supply chain (VSC). The VSC has a hierarchical structure and can be presented as a tree-like graph in which the upper node depicts the entire VSC without identifying its elements; the first tier of nodes contains its main components, that is, manufacturers, DCs, clinics, and the population. The chapter considers the subproblem of identifying the most significant risk factors and most vulnerable components in a VSC and, therefore, in reducing the supply chain (SC) size, using the entropy approach. The data related to a real-life VSC in the health care organizations (HCOs) CLALIT have been provided by the CLALIT's experts and used for the implementation and verification of the suggested analytics tool. The chapter recommends that the suggested methodology is universal and applicable for processing and compressing other types of Big Data in different health care SCs.
