Title: Optimizing Supply Chain Management for Disease Prevention: A Case Study Approach
Authors: Ogechi Thelma Uzozie, Ekene Cynthia Onukwulu, Iyadunni Adewola Olaleye, Christian Onyinyechi Makata Patience Okpeke Paul , Oluwafunmilayo Janet Esan
Volume: 9
Issue: 4
Pages: 145-152
Publication Date: 2025/04/28
Abstract:
This paper explores the optimization of Supply Chain Management (SCM) for disease prevention through a comprehensive analysis of its challenges and effective strategies. The research highlights key issues such as demand unpredictability, logistical constraints, coordination gaps, supplier dependencies, regulatory hurdles, and financial constraints that significantly impact SCM during health crises. By examining past outbreaks like Ebola and COVID-19, the study underscores the critical need for resilient supply chains. It discusses innovative approaches, including blockchain, artificial intelligence (AI), Internet of Things (IoT), and 3D printing, transforming SCM by enhancing efficiency, transparency, and responsiveness. The paper also emphasizes the importance of collaborative efforts among governments, non-governmental organizations (NGOs), and the private sector. Best practices, such as strategic stockpiling, real-time visibility tools, public-private partnerships, capacity building, and regulatory harmonization, are vital for optimizing SCM. The findings suggest that embracing these strategies can lead to more robust and responsive supply chains, ultimately improving disease prevention and control. The study calls for further research into advanced predictive analytics, global supply chain dynamics, and the effectiveness of various partnership models to strengthen future SCM practices.