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Integrated Model for Evidence-Based Risk Factor Prioritisation and Dynamic Resource Allocation in Hypertension
Martins Nweke1, Julian Pillay1
1Department of Basic Medical Sciences, Durban University of Technology, Durban 4001, South Africa.
Healthcare (Basel, Switzerland)
|May 4, 2026
Summary
This study introduces a novel decision-support model for hypertension control in South Africa. It prioritizes risk factors and allocates budgets dynamically to improve public health investments and reduce cardiovascular disease.
Area of Science:
- Public Health
- Health Economics
- Epidemiology
Background:
- Hypertension is a major cause of cardiovascular disease in South Africa.
- Existing models lack mechanisms for context-specific prioritization and dynamic resource allocation.
- Translating evidence on modifiable risk factors into strategic health investments is limited.
Purpose of the Study:
- To develop and validate an integrated decision-support model for hypertension prevention and control.
- To link evidence-based risk factor prioritization with dynamic budget allocation.
- To improve strategic and equitable health investments in South Africa.
Main Methods:
- A two-phase mixed-methods design was employed.
- Phase 1: Developed a Risk Factor Prioritization Model using composite indices (causality, feasibility, policy integration, equity).
- Phase 2: Constructed a Dynamic Resource Allocation Model to maximize Disability-Adjusted Life Years (DALYs) averted within budget and equity constraints, integrating data from systematic reviews, GBD 2019, WHO-CHOICE, and national health expenditure.
Main Results:
- A validated quantitative Risk Priority Score (RPS) for hypertension risk factors.
- An optimization model for resource allocation.
- An interactive dashboard visualizing efficiency and equity trade-offs under various budget scenarios.
Conclusions:
- The study provides a reproducible model for translating epidemiological and economic evidence into actionable policy guidance.
- It bridges the gap between evidence generation and health planning for noncommunicable disease control.
- Supports more equitable and data-driven decision-making in public health.
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