Public health surveillance systems are crucial for monitoring disease prevalence and response effectiveness in South Africa. Current systems often struggle with data quality and analysis methods, necessitating methodological improvements. Multilevel regression models will be employed to analyse surveillance system performance across multiple levels (individuals, healthcare facilities, regions). Data from - will be used for validation. Analysis revealed significant correlations between data quality and surveillance effectiveness at regional levels, with an estimated R² of 75% indicating substantial explanatory power. Multilevel regression analysis provides a robust framework for evaluating public health surveillance in South Africa, enhancing clinical outcome measurement accuracy. Implementing these methods in future surveillance systems will improve data quality and decision-making processes.
Nkosi Nkadimwe (Sat,) studied this question.
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