"background": "Public health surveillance systems are critical for early disease detection and response, yet their operational yield—the proportion of true cases identified—is often inadequately measured. In many settings, including Nigeria, evaluations have been hampered by fragmented data and a lack of longitudinal analytical frameworks. ", "purpose and objectives": "This case study aimed to methodologically evaluate the yield of integrated disease surveillance in Nigeria and to estimate longitudinal improvements using a panel-data econometric approach. The objective was to quantify the effect of systematic investments in surveillance infrastructure on case detection rates. ", "methodology": "We constructed a balanced panel dataset from national and sub-national surveillance records. Yield was operationalised as the ratio of confirmed cases to suspected cases reported. The core analysis employed a two-way fixed effects model: Y{it = \0 + \1 Interventionit + \ + \ +, where Yit is the yield in state i at time t. Robust standard errors were clustered at the state level. ", "findings": "The fixed effects estimation indicated a statistically significant positive association between the phased rollout of integrated support and surveillance yield (p<0. 01). A one-unit increase in the intervention index was associated with an approximate 17% increase in yield, with a 95% confidence interval of 12% to 22%. Data completeness showed marked improvement in later phases of the programme. ", "conclusion": "The application of panel-data methods provides a robust framework for quantifying surveillance system performance over time. The analysis confirms that targeted, systemic investments can substantially improve the yield of public health surveillance. ", "recommendations": "Routine surveillance evaluations should adopt longitudinal, quantitative designs to attribute changes in performance. Policymakers should prioritise sustained investment in core surveillance infrastructure and data quality management to maintain yield improvements. ", "key words": "surveillance yield, panel data, fixed effects, health systems, econometric evaluation, disease detection", "
Okonkwo et al. (Sat,) studied this question.