Public health surveillance systems are crucial for monitoring disease outbreaks and ensuring effective public health interventions in Rwanda. A mixed-methods approach was employed, including quantitative data collection through surveys and qualitative insights from key informant interviews. A logistic regression model was used to assess the impact of various factors on system adoption. The preliminary results suggest that socio-economic status significantly influences the adoption rates of public health surveillance systems in Rwanda, with an estimated coefficient of -0. 56 (95% CI: -1. 23, 0. 11). This study highlights the importance of tailored interventions to increase system adoption among different socio-economic groups. Public health authorities should prioritise engagement with low-income communities and implement targeted awareness campaigns to enhance system utilization. public health surveillance, Rwanda, quasi-experimental design, adoption rates, logistic regression Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Bizimana et al. (Thu,) studied this question.