GDP, language, and conflict predict 80% of Africa's trial distribution.
Countries Modeled
30
Adj. R-squared
0.80
Top Predictor
GDP/capita
Outlier: Rwanda
Overperforms
Key Finding
GDP per capita was the single strongest predictor (standardised beta 0.85), followed by English-language status and PEPFAR recipient status.
Regional Comparison
Hiv — Condition Analysis
Multi-Dimensional Equity Profile
Design Feature & Temporal Trend
Inequality Decomposition & Statistics
Hiv — Computed Statistics
Africa: 1,793 | US: 5,071 | Europe: 1,451 | Ratio: 2.8x
Africa share: 21.6% | HHI4-region = 0.449 | Shannon H = 1.47 bits
Adaptive: AF 140 vs US 2,986 (21.3x gap)
Ginicountry = 0.857 [0.61, 0.90] | αpower-law = 1.40 | Atkinson A(2) = 0.979
KL(obs||uniform) = 2.93 bits | ρSpearman(pop, trials/M) = −0.01
Why It Matters
A regression model of 30 African nations explains 80% of the variance in trial density using six structural predictors. GDP per capita is the dominant factor, followed by English-language status and PEPFAR recipient status. Nigeria massively underperforms relative to its structural predictors, while Rwanda dramatically overperforms — suggesting that unmeasured governance quality may be the most important latent factor determining research capacity.
The Evidence 127 words · target 156
What country-level structural factors determine the distribution of 23,873 interventional clinical trials across 53 trial-active African nations? This ecological regression analysed log-transformed trials per million population as the dependent variable using six predictors: log GDP per capita, English-language status, PEPFAR recipient status, active conflict, WHO regulatory maturity level, and log population. The model achieved an adjusted R-squared of 0.80 using ordinary least squares with Gauss-Jordan matrix inversion implemented in pure Python. GDP per capita was the single strongest predictor (standardised beta 0.85), followed by English-language status and PEPFAR recipient status. Nigeria (379 trials, 223.8M population) massively underperformed while Rwanda (138 trials, 14.1M) dramatically overperformed. These findings suggest that governance quality is the dominant latent factor beyond structural predictors. Interpretation is limited by cross-sectional design and unmeasured confounders.
Sentence Structure
Question
What country-level structural factors determine the distribution of 23,873 interventional clinical trials across 53 trial-active African nations?
Dataset
This ecological regression analysed log-transformed trials per million population as the dependent variable using six predictors: log GDP per capita, English-language status, PEPFAR recipient status, active conflict, WHO regulatory maturity level, and log population.
Method
The model achieved an adjusted R-squared of 0.80 using ordinary least squares with Gauss-Jordan matrix inversion implemented in pure Python.
Primary Result
GDP per capita was the single strongest predictor (standardised beta 0.85), followed by English-language status and PEPFAR recipient status.