Standardizing COVID-19 surveillance data into the OMOP common data model: a first implementation case study from Senegal

The COVID-19 pandemic highlighted the need for interoperable health data infrastructures supporting reproducible observational research. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) provides a widely adopted standard for harmonizing heterogeneous health data, but adoption remains limited in francophone Africa where language barriers and non-standardized surveillance systems pose additional challenges. We developed a complete Extract-Transform-Load (ETL) pipeline to convert a heterogeneous Senegalese COVID-19 surveillance dataset into OMOP CDM version 5.4. Source data recorded in French were translated into English through an iterative process interleaved with vocabulary mapping using ATHENA and Usagi. Semantic standardization used SNOMED CT for conditions, LOINC for measurements, and RxNorm for drugs. All 214 mappings underwent expert review by clinical and data science specialists. Data quality was assessed using the OHDSI Data Quality Dashboard (DQD) and Achilles. The standardized database achieved complete transformation (100%) for eight of the eleven source-populated domain tables, including person, visit_occurrence, measurement, and death. Partial transformation was observed for condition_occurrence (95.3%) and observation (68.1%), primarily due to incomplete vocabulary coverage for occupation categories and context-specific variables. The DQD produced an overall pass rate of 97% and a corrected pass rate of 98%, comparable to other published African OMOP implementations. Among the 19 data-quality failures, conformance and completeness issues predominated; the conformance failures were largely foreign-key checks, reflecting placeholder concept values (concept_id = 0) for metadata fields without meaningful equivalents in surveillance data. Iterative translation refinement was required when French-to-English translations did not align with OHDSI vocabulary terminology. This work documents, to our knowledge, the first OMOP CDM implementation on COVID-19 surveillance data in Senegal and francophone West Africa and provides a reusable methodological blueprint for future OMOP deployments in the region.