Optimizing Medical Supply Chain Resilience for Future Pandemics: A Data-Driven Framework Integrating Public Health Risk, Logistics Efficiency, and Predictive Analytics

The COVID-19 pandemic exposed critical vulnerabilities in global medical supply chains, resulting in widespread shortages of essential healthcare products. This study aims to optimize the resilience of medical supply chains against future pandemics by evaluating key mitigation strategies such as inventory buffering, multi-sourcing, and local manufacturing. Using an agent-based simulation model that incorporates realistic demand surges, supplier disruptions, and transportation delays, we quantify the impact of these strategies on supply chain performance metrics including fulfillment rate, lead time, and recovery speed. Our results demonstrate that integrating multiple resilience strategies significantly improves service levels and reduces recovery times compared to traditional supply chain configurations. The findings provide actionable insights for policymakers and healthcare organizations to strengthen preparedness and ensure reliable access to critical medical supplies in times of crisis.

Authors

Publication Details

Journal
Journal of Intelligent Learning Systems and Applications
Published
2025-01-01
DOI
https://doi.org/10.4236/jilsa.2025.173010
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Medical Supply Chain Resilience for Future Pandemics: A Data-Driven Framework Integrating Public Health Risk, Logistics Efficiency, and Predictive Analytics

Mahfuzul Hoque, Sajal K Palit, Kamal Hossain, Mst Hasna Akter et al.
Journal of Intelligent Learning Systems and Applications
Supply Chain Resilience and Risk Management
article

Optimizing Medical Supply Chain Resilience for Future Pandemics: A Data-Driven Framework Integrating Public Health Risk, Logistics Efficiency, and Predictive Analytics

Mahfuzul Hoque, Sajal K Palit, Kamal Hossain, Mst Hasna Akter, Tahera Shabnam
article en

Abstract

The COVID-19 pandemic exposed critical vulnerabilities in global medical supply chains, resulting in widespread shortages of essential healthcare products. This study aims to optimize the resilience of medical supply chains against future pandemics by evaluating key mitigation strategies such as inventory buffering, multi-sourcing, and local manufacturing. Using an agent-based simulation model that incorporates realistic demand surges, supplier disruptions, and transportation delays, we quantify the impact of these strategies on supply chain performance metrics including fulfillment rate, lead time, and recovery speed. Our results demonstrate that integrating multiple resilience strategies significantly improves service levels and reduces recovery times compared to traditional supply chain configurations. The findings provide actionable insights for policymakers and healthcare organizations to strengthen preparedness and ensure reliable access to critical medical supplies in times of crisis.

Journal of Intelligent Learning Systems and ApplicationsVol. 17(03)
Openalex Percentile: Top 72%
Supply Chain Resilience and Risk Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimizing Medical Supply Chain Resilience for Future Pandemics: A Data-Driven Framework Integrating Public Health Risk, Logistics Efficiency, and Predictive Analytics — Mahfuzul Hoque, Sajal K Palit, et al. · Journal of Intelligent Learning Systems and Applications (2025) | TGRS Research Map | TGRS