Designing a Health Data Analytics Platform for State-Level Disease Surveillance in Plateau State

Real-time disease surveillance requires integrated health data platforms that can ingest, clean, and analyse data from multiple facility sources, and designing such a platform for Plateau State addresses a critical gap in North Central Nigeria's public health infrastructure. This study designed a health data analytics platform for the Plateau State Ministry of Health, drawing on assessment of current disease surveillance data flows, infrastructure gaps, and reporting bottlenecks. A professional design methodology was employed, with structured interviews conducted with 18 disease surveillance officers, 12 PHC facility data managers, and 6 state Ministry of Health IT officials. The platform designed incorporates four components: a standardised electronic reporting module for PHC facilities, a data integration layer connecting facility data to the state HMIS, an automated anomaly detection engine for outbreak signals, and an interactive visualisation dashboard for health managers. ETL pipeline specifications for merging DHIS2 and paper-based reporting data are provided. The anomaly detection component applies a negative binomial control chart approach validated on five years of historical case data. Expert review by eight health informatics and data engineering specialists confirmed the platform's technical soundness. The study recommends phased rollout across the 17 LGAs with highest disease burden in Phase 1, training of facility data focal persons in digital reporting, and integration with the Nigeria Centre for Disease Control SORMAS platform as the national reporting endpoint.

Keywords: health data platform, disease surveillance, Plateau State, HMIS, public health analytics