Integrated Model for Evidence-Based Risk Factor Prioritisation and Dynamic Resource Allocation in Hypertension...

Background: Hypertension remains one of the leading causes of cardiovascular morbidity and mortality in South Africa. Although extensive evidence exists on modifiable risk factors, the translation of this evidence into strategic and equitable health investments remains limited. Current models such as the Global Burden of Disease (GBD) and WHO "Best Buys" identify key exposures, but lack operational mechanisms for context-specific prioritisation and dynamic resource allocation. The aim of this study is to develop and validate an integrated decision-support model that links evidence-based risk factor prioritisation with dynamic budget allocation to improve hypertension prevention and control in South Africa. Methods: This study adopts a two-phase mixed-methods design. Phase 1 develops a Risk Factor Prioritisation Model that ranks modifiable exposures using composite indices for the causality strength, implementation feasibility, policy integration, and equity. Phase 2 constructs a Dynamic Resource Allocation Model that distributes health budgets across interventions to maximise Disability-Adjusted Life Years (DALYs) averted, subject to budget and equity constraints. The model integrates data from systematic reviews, GBD 2019 estimates, WHO-CHOICE cost data, and national health expenditure databases. A validated quantitative Risk Priority Score (RPS) for major hypertension risk factors, an optimisation model for resource allocation, and an interactive dashboard that visualises efficiency and equity trade-offs under varying budget scenarios are expected. Conclusions: This study will provide a reproducible model for transforming epidemiological and economic evidence into actionable policy guidance. It bridges the gap between evidence generation and health planning, supporting more equitable and data-driven decision making in noncommunicable disease control.