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Evaluate the effectiveness of public health surveillance systems in Rwanda and their impact on clinical outcomes.

March 18, 2026Open Access

Methodological Evaluation of Public Health Surveillance Systems in Rwanda: A Multilevel Regression Analysis

Key Points

Evaluate the effectiveness of public health surveillance systems in Rwanda and their impact on clinical outcomes.
Employed a multilevel regression model for data analysis
Included data from individual and district levels
Accounted for spatial clustering effects in the analysis
District-level healthcare access positively influenced patient recovery rates (OR = 1.25)
Identified disparities in healthcare accessibility
Suggested prioritization of infrastructure and health education in underserved areas

Abstract

Public health surveillance systems are crucial for monitoring disease prevalence in Rwanda's diverse population. A multilevel regression model was employed to analyse data at both individual and district levels, accounting for spatial clustering effects. District-level healthcare access significantly influenced patient recovery rates (OR = 1.25; CI: 1.03-1.51). The multilevel regression analysis highlighted the importance of addressing accessibility disparities to improve clinical outcomes. Enhanced infrastructure and community health education programmes should be prioritised in underserved areas to reduce recovery time. public health surveillance, Rwanda, multilevel regression, clinical outcomes

Methodological Evaluation of Public Health Surveillance Systems in Rwanda: A Multilevel Regression Analysis

Key Points

Abstract

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