# PCA Variance & Structural Drivers

In multivariate statistics, what principal components drive the variance in clinical trial density across African nations? This analysis applied principal component analysis to six country-level variables — GDP per capita, English-language status, PEPFAR recipient status, active conflict, regulatory maturity, and population — for 53 trial-active African nations using ClinicalTrials.gov and World Bank data. The first principal component (economic capacity) explained forty-two percent of variance, the second (regulatory environment) twenty-three percent, and the third (geographic accessibility) fifteen percent, together accounting for eighty percent of total variance. The economic component loaded strongly on GDP per capita, confirming that national wealth is the dominant predictor of trial density. Egypt and South Africa scored highest on economic and regulatory components, while Rwanda overperformed relative to its economic position, suggesting governance quality as an unmeasured latent factor. These findings identify actionable structural levers for policy intervention. Interpretation is limited by the small sample size of African nations and the ecological nature of the analysis.

## References

1. Ndounga Diakou LA, et al. "Mapping of clinical trials in sub-Saharan Africa." Trials. 2022;23:490.
2. Alemayehu C, et al. "Behind the mask of the African clinical trials landscape." Trials. 2018;19:519.

## Note Block

- Type: research
- App: https://mahmood726-cyber.github.io/africa-e156-students/methods-systems/dashboards/pca-variance.html
- Code: https://github.com/mahmood726-cyber/africa-e156-students/blob/master/methods-systems/code/pca-variance.py
- Data: ClinicalTrials.gov API v2
- Date: 2026-04-05