Nithyanandham, D.Augustin, F.Narayanamoorthy, S.Ijaz, B.Ranganathan, S.Dhivya, S.Ahmadian, A.2025-11-152025-11-1520259780443338717978044333872410.1016/B978-0-443-33871-7.00014-32-s2.0-105019731228https://doi.org/10.1016/B978-0-443-33871-7.00014-3https://hdl.handle.net/20.500.14517/8545Centrality measure is one of the important tools in graph theory to measure the significance of the vertices in the graph. When uncertainty exists in the vertices and their relations, the fuzzy graph helps to handle such scenarios. Bipolar intuitionistic fuzzy graph is an extension of fuzzy graph, effectively deal with uncertainty by assigning membership and nonmembership degrees in a bipolar perspective. In this chapter, the centrality measures such as degree, in-degree, and out-degree centrality measures in the bipolar intuitionistic fuzzy graph are defined. Additionally, a decision-making model is designed based on the degree centrality measure. Further, an illustration of this model is provided for prioritizing the locations to setup healthcare camp during COVID-19 pandemics. © 2025 Elsevier B.V., All rights reserved.eninfo:eu-repo/semantics/closedAccessApplied LinguisticsBipolar Intuitionistic Fuzzy GraphDecision-MakingDegree CentralityInfectious DiseaseKnowledge Representation and ReasoningLocation SelectionMathematical OptimizationOperations ResearchBook PartN/AN/A297309