Public health surveillance systems in Kenya are essential for monitoring disease prevalence and guiding intervention strategies. A stratified random sampling approach was employed to select participants from urban and rural populations across Kenya. Data collection included standardised questionnaires and laboratory tests for disease markers. The analysis revealed that the prevalence of malaria in rural areas (25%) is significantly higher than in urban areas (10%), with a confidence interval of ±3%. The findings suggest that current surveillance systems may need to be adjusted to better reflect regional health disparities, particularly for vector-borne diseases like malaria. Public health officials should prioritise the development and implementation of targeted interventions in rural areas to improve disease control outcomes. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Odhiambo Kinyanjui (2003) studied this question.