African Air Quality Research (Environmental Science) | 17 May 2005
Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Nigeria,
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Abstract
Public health surveillance systems in Nigeria have been established to monitor infectious diseases such as tuberculosis (TB). However, their effectiveness and cost-effectiveness remain under scrutiny. A multilevel regression model was employed with fixed effects for geographical clusters and random intercepts for individual healthcare facilities. Uncertainty in estimates is addressed through robust standard errors. The model revealed a significant positive effect of surveillance intensity on TB case detection rates (\(OR = 1\).05, $p$-value < 0.001), with moderate precision around the estimate. Despite challenges in resource allocation, the surveillance system is effective and cost-effective in enhancing TB case identification across regions. Further studies should explore strategies to optimise resource distribution for better overall performance. Public Health Surveillance, Multilevel Regression Analysis, Cost-Effectiveness, Tuberculosis (TB), Nigeria