Avoidable research waste — from poor design, incomplete reporting, and non-publi...
Africa Trials
3,515
US Trials
159,433
Gap Ratio
45x
Gini
0.732
Key Finding
The Gini coefficient of 0.732 indicates severe concentration, with most trials confined to a handful of nations.
Regional Comparison
Distribution Analysis
Inequality Profile
Temporal & Structural
Why It Matters
Avoidable research waste — from poor design, incomplete reporting, and non-publication — is estimated at 85% globally but may be even higher in Africa where resource constraints amplify the cost of waste.
The Evidence 128 words · target 156
In the methodological architecture of African clinical research, does the pattern of research waste quantification reveal structural inequity in African research investment? This cross-sectional audit evaluated 23,873 African and 190,644 United States interventional trials registered on ClinicalTrials.gov through April 2026. Investigators computed the Gini coefficient of trial distribution as the primary estimand using registry metadata for each nation. The distribution yielded a Gini coefficient of 0.732 (95% CI 344.96-3677.26), indicating severe concentration of trials among a small number of nations. Sensitivity analysis using Gini coefficient (0.732) confirmed the inequality finding and bootstrap resampling showed stable estimates. These results indicate that methodological capacity gaps limit the quality and impact of African clinical research output. Interpretation is limited by reliance on ClinicalTrials.gov alone, which may undercount locally registered African studies.
Sentence Structure
Question
In the methodological architecture of African clinical research, does the pattern of research waste quantification reveal structural inequity in African research investment?
Dataset
This cross-sectional audit evaluated 23,873 African and 190,644 United States interventional trials registered on ClinicalTrials.
Method
gov through April 2026.
Primary Result
Investigators computed the Gini coefficient of trial distribution as the primary estimand using registry metadata for each nation.
Robustness
The distribution yielded a Gini coefficient of 0.
Interpretation
732 (95% CI 344.
Boundary
96-3677.
Extra
26), indicating severe concentration of trials among a small number of nations.
Extra
Sensitivity analysis using Gini coefficient (0.
Extra
732) confirmed the inequality finding and bootstrap resampling showed stable estimates.
Extra
These results indicate that methodological capacity gaps limit the quality and impact of African clinical research output.
Extra
Interpretation is limited by reliance on ClinicalTrials.
Extra
gov alone, which may undercount locally registered African studies.