Evaluation of the measles surveillance system in Chereponi District, Ghana, 2019-2024

Objectives To evaluate the design, implementation, and performance of the measles surveillance system in Chereponi District, Ghana, from 2019 to 2024 using the United States Centers for Disease Control and Prevention (CDC) Updated Guidelines for Evaluating Public Health Surveillance Systems. Study design Cross-sectional mixed-methods surveillance system evaluation. Methods A mixed-methods evaluation was conducted across all 26 health facilities implementing measles surveillance and 13 purposively selected key informants. Quantitative data were collected through facility assessments and review of Surveillance Outbreak Response Management and Analysis System (SORMAS) records. Qualitative data were obtained through semi-structured interviews. Descriptive statistics, predictive value positive (PVP), Cochran–Armitage trend analysis, and thematic analysis were performed. Results Timeliness was the strongest surveillance attribute (100%), followed by data quality (96.2%) and representativeness (88.5%). Acceptability (80.8%), simplicity (73.1%), and flexibility (61.5%) showed moderate performance, whereas usefulness (42.3%) and stability (38.5%) were weakest. During 2019-2024, 167 suspected measles cases were reported, of which 31 were laboratory confirmed (PVP = 18.6%; 95% CI: 13.4-25.3%). Laboratory confirmation rates increased significantly from 0% during 2019-2021 to 30.8% in 2024 (Cochran-Armitage χ 2 = 14.57, P < 0.001). Qualitative findings attributed operational weaknesses to inadequate refresher training, staff attrition, transport constraints, delayed laboratory feedback, unreliable internet and electricity, and inconsistent community-based reporting. Conclusions The measles surveillance system was functional and supported timely case detection, laboratory confirmation, and outbreak response within Ghana's IDSR framework. However, strengthening workforce capacity, logistics, laboratory feedback, digital infrastructure, and community-based surveillance is essential to improve system stability and advance measles elimination effort.