Optimization of Drug Transportation Logistics for Home Isolation Patients: A Case Study in Thailand
Issued Date
2025-01-01
Resource Type
Scopus ID
2-s2.0-105022511080
Journal Title
8th International Conference on Transportation Information and Safety Transportation Artificial Intelligence and Green Energy Making A Sustainable World Ictis 2025
Start Page
1654
End Page
1663
Rights Holder(s)
SCOPUS
Bibliographic Citation
8th International Conference on Transportation Information and Safety Transportation Artificial Intelligence and Green Energy Making A Sustainable World Ictis 2025 (2025) , 1654-1663
Suggested Citation
Kritchanchai D., Niemsakul J., Chanpuypetch W., Srisakunwan S., Niemsakul S. Optimization of Drug Transportation Logistics for Home Isolation Patients: A Case Study in Thailand. 8th International Conference on Transportation Information and Safety Transportation Artificial Intelligence and Green Energy Making A Sustainable World Ictis 2025 (2025) , 1654-1663. 1663. doi:10.1109/ICTIS68762.2025.11214896 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/113293
Title
Optimization of Drug Transportation Logistics for Home Isolation Patients: A Case Study in Thailand
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Corresponding Author(s)
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Abstract
The COVID-19 pandemic has led to a global shortage of medical workers, drugs, supplies, and hospital beds, including in Thailand. To address these challenges, home isolation (HI) has been implemented for asymptomatic or mildly symptomatic COVID-19 patients in Bangkok and its surrounding areas. Pripta Clinic, a non-profit virtual hospital, provides medical care to approximately 70% of these patients. However, the rising number of cases has strained drug management systems, causing delays in medication delivery and difficulties in recruiting healthcare professionals for the HI program. These inefficiencies increase the risk of severe symptoms and mortality among patients.To enhance the effectiveness of drug distribution for HI patients, this study focuses on optimizing transportation logistics by improving last-mile delivery. A scheduling optimization model is developed and applied to real-world case studies, comparing single-hub and multi-hub distribution models. The analysis evaluates cost-effectiveness, efficiency, and delivery speed. The results identify the most optimized transport schedules for each route, enabling operators to enhance service efficiency, minimize costs, and accelerate medication delivery. Additionally, this model serves as a strategic guide for policymakers and healthcare providers to develop more effective logistics frameworks for future infectious disease outbreaks.