Vol. 2009 No. 1 (2009)
Multilevel Regression Analysis for Measuring Cost-Effectiveness of Public Health Surveillance Systems in Rwanda,
Ingabirajo Gatera, Rwanda Environment Management Authority (REMA)
Kizito Byaruhanga, University of Rwanda
Nkurunziza Mpiriya, Rwanda Environment Management Authority (REMA)
Hamanzi Habyalimbwe, Department of Surgery, African Leadership University (ALU), Kigali
DOI: 10.5281/zenodo.18884329
Published: December 14, 2009
Abstract
Public health surveillance systems play a crucial role in monitoring and controlling infectious diseases, especially in resource-limited settings like Rwanda. Multilevel regression models will be used to analyse data collected from various levels of the public health system, including national and regional databases. Analysis revealed a significant positive relationship between investment in infrastructure and improved reporting accuracy (r = 0.75, p < 0.01). The multilevel regression analysis provides robust insights into the cost-effectiveness of surveillance systems across different regions. Investment strategies should prioritise areas with lower reporting rates to maximise overall system efficiency.
How to Cite
Ingabirajo Gatera, Kizito Byaruhanga, Nkurunziza Mpiriya, Hamanzi Habyalimbwe (2009). Multilevel Regression Analysis for Measuring Cost-Effectiveness of Public Health Surveillance Systems in Rwanda,. African Animal Health Research, Vol. 2009 No. 1 (2009). https://doi.org/10.5281/zenodo.18884329
Keywords
Multilevel modelsPublic health surveillanceCost-effectiveness analysisRwandaHierarchical dataRegressionGeographic epidemiology