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Business and Social Sciences

Volume 3 Number 1 2026

Article Contents

Figures and Tables
RESEARCH ARTICLE   (Open Access)
Contents Vol 3 (1)

From Scarcity to Fairness: A Closed-Loop Reinforcement Learning and Geospatial Analytics Framework for Equitable Healthcare Supply Chain Preparedness

Adib Hossain 1*, Fahad Ahmed 2, Khandaker Ataur Rahman 3, Shaid Hasan 3

+ Author Affiliations

Business and Social Sciences 3 (1) 1-8 https://doi.org/10.25163/business.3110666

Submitted: 04 December 2025 Revised: 03 February 2026  Published: 08 February 2026 

Abstract

Healthcare supply shortages during crises are often framed as failures of production or procurement. Yet recent public health emergencies suggest something more complicated—resources may exist nationally while still failing to reach the populations that need them most. This study proposes an integrated predictive–prescriptive framework designed to operationalize equity in healthcare resource distribution rather than treating it as a retrospective performance metric. The framework combines probabilistic spatiotemporal demand forecasting, geospatial accessibility modeling, and reinforcement learning–based sequential allocation within a closed-loop decision architecture. Using multi-source operational, epidemiological, and social vulnerability data, the model learns adaptive allocation policies that respond to evolving demand uncertainty and access constraints across regions. Results suggest that socially vulnerable regions exhibit both higher demand variability and greater forecast uncertainty, reinforcing the need for probabilistic and equity-aware allocation strategies. Compared with baseline rule-based and static optimization approaches, the proposed framework improves service levels in high-vulnerability regions, reduces cumulative shortage days, and maintains strong overall system performance. Importantly, the findings challenge the traditional assumption that equity necessarily reduces operational efficiency. Instead, early integration of equity signals appears to enhance system resilience and reduce downstream crisis-response costs. Collectively, the study demonstrates that equitable preparedness is not solely a policy aspiration but can be translated into a measurable, learnable, and implementable operational objective.

Keywords: Healthcare supply chain resilience, Health equity analytics, Reinforcement learning in healthcare operations, Geospatial accessibility modeling, Pandemic logistics optimization.

References

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