This research tackles a key weakness in global medical supply chains revealed by the COVID-19 pandemic. It creates a new Geopolitical-Financial Composite Index (GFCI) to act as an early-warning system. The study moves past old, reactive models by combining different risk indicators like political instability, financial swings, trade policy changes, and shipping performance into a single score. We built this index using principal component analysis and tested its accuracy against real data from the 2020-2023 crisis period. The results show the GFCI reliably signals coming shortages of medical supplies about three months in advance. This was confirmed by strong statistical correlations and ROC analysis. The final output is a practical Early-Warning and Mitigation Framework that turns GFCI alerts into specific actions, like finding new suppliers or building up reserves. This work provides policymakers and health organizations with a proactive, data-driven tool to build stronger supply chains and better prepare for future pandemics.
Table of Contents
- INTRODUCTION
- 1.1 STATEMENT OF THE PROBLEM
- 1.2 AIM AND OBJECTIVES OF THE STUDY
- 1.3 RESEARCH QUESTIONS
- 1.4 SIGNIFICANCE OF THE STUDY.
- 1.5 Scope of the Study.
- 1.6 OVERVIEW OF STUDY STRUCTURE
- 1.7 SUMMARY
- LITERATURE REVIEW
- 2.0 Preamble
- 2.1 Pandemic Induced Disruption of Critical Medical Supply Chains
- 2.2 Geopolitical Risk and Its Impact on Medical Supply Availability
- 2.3 Financial Instability and Pandemic Supply Shock.
- 2.4 Early Warning Systems in Health Supply Chain Management
- 2.5 Composite Index Modelling for Predictive Risk Assessment..
- 2.6 Theoretical Foundation
- 2.7 Conceptual Framework
- METHODOLOGY.
- 4.1 Introduction
- 4.2 Thematic Analysis of Key Data Patterns...
- 4.2.1 Convergence of Geopolitical and Financial Stress Prior to Stockouts..........
- 4.2.2 Supply Chain Bottlenecks as Amplifiers of Crisis Conditions
- 4.2.3 Predictable Pre-Shock Signatures in Medical Supply Data
- 4.3 Statistical Development of the Geopolitical-Financial Composite Index (GFCI)
- 4.3.1 Data Pre-Processing and Normalization
- 4.3.2 Principal Component Analysis and Indicator Weighting.
- 4.3.3 Index Computation.
- 4.3.4 Lead Lag Correlation Analysis
- 4.4 Back-Testing and Predictive Performance Assessment
- 4.4.1 Out-of-Sample Back-Testing
- 4.4.2 ROC Curve and Signal Detection Analysis
- 4.5 Development of the Early Warning and Mitigation Framework.
- 4.6 Discussion of Findings
- CONCLUSION AND RECOMMENDATIONS
Objective & Thematic Focuses
This study aims to develop a Geopolitical-Financial Composite Index (GFCI) that predicts early warning signals of critical medical supply stockouts during pandemics and global crises. The research identifies and analyzes geopolitical, financial, and macroeconomic indicators, constructs a composite index, and validates its predictive performance using historical crisis data and scenario simulations to answer how these factors contribute to supply chain vulnerability and how accurately the index can predict disruptions.
- Geopolitical risk and its impact on medical supply availability.
- Financial instability and pandemic supply shocks.
- Early warning systems in health supply chain management.
- Composite index modeling for predictive risk assessment.
- Supply chain resilience and pandemic preparedness.
Excerpt from the Book
2.6.1 Systems Theory
Systems Theory, originally developed by Ludwig von Bertalanffy in 1968, conceptualizes organizations and processes as interdependent subsystems forming a coherent whole. In this framework, any disturbance in one part of the system inevitably impacts other components, often in complex and non-linear ways. In the context of healthcare supply chains during pandemics, this perspective is particularly relevant because disruptions in one segment such as manufacturing, logistics, or financial provisioning can cascade across the entire supply chain, leading to widespread shortages of essential medical supplies.
The theory emphasizes interconnectedness and feedback loops, where the behavior of the system is influenced not only by individual components but also by the relationships and flows between them. For example, a delay in raw material importation due to geopolitical tensions does not merely halt production; it can trigger price surges, affect distribution schedules, strain healthcare budgets, and ultimately compromise patient care. Such cascading effects illustrate that supply chains cannot be analyzed in isolation; they must be understood as integrated systems where upstream or downstream shocks can propagate and amplify.
A key principle of Systems Theory is dynamic equilibrium, which refers to the system's ability to maintain stability despite external shocks. During a pandemic, however, healthcare supply chains often operate far from equilibrium due to unpredictable demand surges, transportation disruptions, and sudden policy shifts.
Systems Theory suggests that the resilience of the supply chain depends on its ability to absorb shocks, adapt to changing conditions, and reconfigure itself to maintain functionality. This has direct implications for the proposed Geopolitical-Financial Composite Index, which functions as a monitoring tool to identify stress points, predict vulnerabilities, and support corrective measures before systemic failure occurs.
Chapter Summaries
INTRODUCTION: This section introduces the problem of fragile medical supply chains during pandemics, highlighting the inadequacy of reactive systems, and presenting the rationale for developing a Geopolitical-Financial Composite Index (GFCI) along with the study’s aims, objectives, research questions, and scope.
LITERATURE REVIEW: This chapter provides a comprehensive review of existing research related to pandemic supply chain disruptions, geopolitical risk, financial instability, and early warning systems, establishing the theoretical foundations (Systems Theory, Risk Society Theory, Resource Dependence Theory) and conceptual framework for the GFCI.
METHODOLOGY: This section outlines the quantitative, design-science research approach used for developing the GFCI, detailing the research philosophy, data sources, preparation techniques, index construction procedures, and validation methods.
DATA ANALYSIS, FINDINGS, AND FRAMEWORK DEVELOPMENT: This chapter presents the analytical results derived from the GFCI’s construction, testing, and validation, including thematic analysis of data patterns, statistical development, back-testing, ROC curve analysis, and the proposed Early-Warning and Mitigation Framework.
CONCLUSION AND RECOMMENDATIONS: This final chapter summarizes the key findings, confirming the GFCI's effectiveness in predicting medical supply stockouts, and offers practical recommendations for integrating the index into pandemic preparedness strategies and strengthening global health security.
Keywords
Medical Supply Stockouts, Geopolitical Risk, Financial Instability, Early-Warning System, Pandemic Preparedness, Supply Chain Resilience, Predictive Analytics, Composite Index, Supply Chain Disruptions, Healthcare Logistics, Risk Management, Quantitative Modeling, Trade Policy, Global Crises, Systemic Risks
Frequently Asked Questions
What is this work fundamentally about?
This work fundamentally focuses on developing and validating a Geopolitical-Financial Composite Index (GFCI) to predict and mitigate critical medical supply stockouts during global pandemics and crises.
What are the central thematic areas?
The central thematic areas include geopolitical risk, financial instability, medical supply chain vulnerability, early warning systems, and the development of a predictive composite index for global health security.
What is the primary goal or research question?
The primary goal is to develop a Geopolitical-Financial Composite Index (GFCI) that predicts early warning signals of critical medical supply stockouts during pandemics and global crises. A key research question is how accurately this index can predict such disruptions.
Which scientific method is used?
The study employs a quantitative, design-science research approach that integrates data mining, statistical modeling, and index construction, guided by a pragmatist philosophy and an abductive research approach.
What is covered in the main part?
The main part of the work covers the detailed statistical development of the GFCI, including data processing, indicator weighting using Principal Component Analysis, index computation, lead-lag correlation analysis, and the assessment of its predictive performance through back-testing and ROC curve analysis. It also proposes an Early-Warning and Mitigation Framework.
Which keywords characterize the work?
The work is characterized by keywords such as Medical Supply Stockouts, Geopolitical Risk, Financial Instability, Early-Warning System, Pandemic Preparedness, Supply Chain Resilience, Predictive Analytics, and Composite Index.
What is the Geopolitical-Financial Composite Index (GFCI)?
The GFCI is a new index created to act as an early-warning system by combining different risk indicators like political instability, financial swings, trade policy changes, and shipping performance into a single score, designed to predict medical supply shortages.
What is the average lead time for GFCI alerts?
The GFCI reliably signals coming shortages of medical supplies about three months in advance, demonstrating a strong short-term forecasting utility confirmed by lead-lag correlation analysis.
How does the study validate the GFCI's predictive performance?
The study validates the GFCI's predictive performance through out-of-sample back-testing against historical crisis data (2020-2023, including COVID-19), lead-lag correlation analysis, cross-validation, and Receiver Operating Characteristic (ROC) curve analysis to measure sensitivity, specificity, and advance warning capability.
What theoretical foundations underpin this study?
The study is underpinned by Systems Theory, which emphasizes interconnectedness and cascading failures; Risk Society Theory, which highlights systemic, human-made risks; and Resource Dependence Theory, focusing on vulnerabilities from external resource reliance.
- Arbeit zitieren
- Olamide Omotosho (Autor:in), 2024, Predicting the Pandemic Shock. A Geopolitical-Financial Composite Index for Early Warning and Mitigation of Critical Medical Supply Stock-Outs, München, GRIN Verlag, https://www.grin.com/document/1683792
