Designing humanitarian logistics network for managing epidemic outbreaks in disasters using Internet-of-Things. A case study: An earthquake in Salas-e-Babajani city. (January 2023)

• Record Type: Journal Article
• Authors: Ehsani, Behdad; Karimi, Hamed; Bakhshi, Alireza; Aghsami, Amir; Rabbani, Masoud
• Is Part Of: Computers & industrial engineering. Volume 175(2023)
• Publication Date: 2023-01
• Subjects: Humanitarian logistics -- Supply Chain Design -- COVID-19 management -- Internet-of-Things -- Location-Allocation problem -- Inventory management; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108821
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Epidemic outbreak amid the disasters is coped with using a supply chain network. Recent experiences to tackle disasters are considered into model parameters. An approach to infected detection is proposed by utilizing IoT-based systems. The proposed network is evaluated by a real-world case. Managerial insights based on sensitivity analyses are presented for managers. Abstract: Along with the destructive effects of catastrophes throughout the world, the COVID-19 outbreak has intensified the severity of disasters. Although the global aid organizations and philanthropists aim to alleviate the adverse impacts, many employed actions are not impactful in dealing with the epidemic outbreak in disasters. However, there is a gap in controlling the epidemic outbreak in the aftermath of disasters. Therefore, this paper proposes a novel humanitarian location-allocation-inventory model by focusing on preventing COVID-19 outbreaks with IoT-based technology in the response phase of disasters. In this study, IoT-based systems enable aid and health-related organizations to monitor people remotely, suspect detection, surveillance, disinfection, and transportation of relief items. The presented model consists of two stages; the first is defining infected cases, transferring patients to temporary hospitals promptly, and accommodating people in evacuation centers. Next, distribution centers are located in the second stage, and relief items are transferred to temporary hospitals and evacuation centers equally regarding shortage minimization. The model is solved by the LP-metric method and applied in a real case study in Salas-e-Babajani city, Kermanshah province. Then, sensitivity analysis on significant model parameters pertaining to the virus, relief items, and capacity has been conducted. Using an IoT-based system in affected areas and evacuation centers reduces the number of infected cases and relief item's shortages. Finally, several managerial insights are obtained from sensitivity analyses provided for healthcare managers.