Documentation
Methodology & Framework
Comprehensive documentation regarding data sourcing, calculation logic, and benchmarking criteria utilized across the African Health Financing Dashboard.
1. Indicator Framework
The dashboard operates on a rigorously structured framework consisting of 33 primary indicators broken down across 5 overarching categories. The selection parameters were established explicitly targeting standard international directives:
- The Africa Scorecard on Domestic Financing for Health.
- The ALM Declaration commitments regarding domestic allocation targets.
- Standardised WHO Health System Building Blocks paradigms.
- United Nations SDG-3 targets concerning global health access.
33
Core Indicators
5
Data Categories
55
AU Member States
2. Metric Categories
2.1 Finances
How much funding is available, and from what source?
Tracks 10 primary indicators
2.2 General Fiscal Space
What is the government's room for policy making?
Tracks 6 primary indicators
2.3 Finance Utilisation
What does 1 USD buy?
Tracks 8 primary indicators
2.4 Health Impact
Outcomes and impact on population health
Tracks 3 primary indicators
3. Benchmarking Methodology
Comparative analytics across the continent are inherently skewed without standardized geographic or economic peer groups. To establish fair comparisons, the application benchmarks quantitative records alongside 4 primary categorizations:
3.1 By Geographic Region
Sourced via African Union
3.2 By Regional Economic Community (REC)
Sourced via African Union
3.3 By World Bank Income Classification
Sourced via World Bank
3.4 By Mo Ibrahim Index of African Governance (IIAG)
Sourced via Mo Ibrahim Foundation
4. Data Sources
Raw Data Repository
Access the aggregate spreadsheet consolidating all queried APIs.
- WHO Global Health Expenditure Database (GHED)
Primary source for domestic health financing data — government health expenditure, out-of-pocket spending, and external resources.
- World Bank World Development Indicators (WDI)
GDP, income classification, tax-to-GDP, and cross-check for health expenditure indicators.
- IMF World Economic Outlook (WEO)
Debt-to-GDP, debt service, interest payments, and fiscal space indicators with projections to 2030.
- WHO Global Health Observatory (GHO)
UHC service coverage index, health workforce density, maternal mortality, child mortality, and facility data.
- UNICEF/WHO Joint Database
Skilled birth attendance and RMNCH coverage indicators.
5. Geographic Coverage
Database queries systematically span exactly 55 African Union Member States, recognizing the Sahrawi Arab Democratic Republic (SADR). We maintain strict territorial mappings aligned explicitly with authorized AU spatial demarcations. No auxiliary unrecognized sub-regions occupy standalone dataset clusters. Operations isolate reporting explicitly across Central, Eastern, Northern, Southern, and Western administrative sub-regions.
6. Limitations & Caveats
Analytical fidelity within public sector health tracking remains universally subject to empirical tracking caveats. Interpretation of output datasets should account for:
- Dataset Asymmetry: Reporting integrity varies considerably depending on the administrative capacities of the targeted nations. Structural workforce capabilities data are routinely outdated compared to fiscal mapping tools.
- Reporting Latency: Consolidated indices like the WHO Global Health Expenditure Database suffer intrinsic two-year publishing chronologies, resulting in modern queries largely reflecting states prior to current macroeconomic events.
- SADR Exclusion Limits: The Sahrawi Arab Democratic Republic generates virtually zero independent health finance modelling observable utilizing standard WHO/IMF parameters, leaving significant gaps natively representing the state.
- Forecasting Uncertainty: Metrics dependent on the IMF World Economic Outlook implicitly rely on structural projections passing current calendar checkpoints subject to shifting volatile domestic inflation.
- Inflationary Distortions: Longitudinal comparisons across sovereign budgets routinely fracture unadjusted for aggressive localized currency hyperinflation or systemic purchasing power parity shifts.
- Definition Divergence: Decentralized governmental data registries often misalign semantic definitions regarding "General Government Expenditure" limits, masking external debt relief overlaps.