Enhancing home delivery of emergency medicine and medical supplies through clustering and simulation techniques: A case study of COVID-19 home isolation in Bangkok
Issued Date
2024-06-30
Resource Type
ISSN
24058440
Scopus ID
2-s2.0-85196259226
Journal Title
Heliyon
Volume
10
Issue
12
Rights Holder(s)
SCOPUS
Bibliographic Citation
Heliyon Vol.10 No.12 (2024)
Suggested Citation
Kritchanchai D., Srinon R., Kietdumrongwong P., Jansuwan J., Phanuphak N., Chanpuypetch W. Enhancing home delivery of emergency medicine and medical supplies through clustering and simulation techniques: A case study of COVID-19 home isolation in Bangkok. Heliyon Vol.10 No.12 (2024). doi:10.1016/j.heliyon.2024.e33177 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/98989
Title
Enhancing home delivery of emergency medicine and medical supplies through clustering and simulation techniques: A case study of COVID-19 home isolation in Bangkok
Corresponding Author(s)
Other Contributor(s)
Abstract
This study investigates the enhancement of the home delivery distribution network for COVID-19 Home Isolation (HI) kits during the Delta variant outbreak of the SARS-CoV-2 virus in Bangkok Metropolitan Area, Thailand. It addresses challenges related to limited resources and delays in delivering HI kits, which can exacerbate symptoms and increase mortality rates. A k-means clustering approach is utilized to optimize the assignment of service areas within the COVID-19 HI program, while discrete event simulation (DES) evaluates potential changes in the home delivery logistics network. Real-world data from the peak outbreak is used to determine the optimal allocation of resources and propose a new logistics network based on proximity to patients' residences. Experimental results demonstrate a significant 44.29% improvement in overall performance and a substantial 40.80% decrease in maximum service time. The findings offer theoretical and managerial implications for effective HI management, supporting practitioners and policymakers in mitigating the impact of future outbreaks.