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This research aims to evaluate the efficiency of public health surveillance systems in Kenya across different governance levels.

March 3, 2026Open Access

Multilevel Regression Analysis to Evaluate and Enhance Public Health Surveillance Systems in Kenya: An Efficiency Gain Assessment

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Multilevel regression analysis reveals efficiency differences in public health surveillance systems in Kenya, suggesting targeted improvements.

This research aims to evaluate the efficiency of public health surveillance systems in Kenya across different governance levels.
Analyzed data from national and subnational surveillance databases in Kenya.
Employed multilevel regression models to account for both fixed and random effects.
Utilized hierarchical clustering based on administrative regions.
Subnational surveillance systems demonstrated 15% higher efficiency in detecting disease outbreaks compared to national levels.
Confidence interval for this efficiency gain was reported as 95% CI: 7%, 23%.
Recommendations include increased funding for subnational health departments and better data sharing.

Ngugi et al. (2006) studied this question.

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Multilevel regression analysis reveals efficiency differences in public health surveillance systems in Kenya, suggesting targeted improvements.