Evaluating the performance of digital surveillance for epidemic-prone diseases in Kwango Province, Democratic Republic of Congo - Hirai, Ayuko; Silenou, Bernard; Bukasa, Tommy; Barka, Baweye M.; Mwakisenda, François; Dörrbecker, Juliane; Dixon, Tshotsho; Aaron, Aruna; Altmann, Mathias (Frontiers in Public Health, 2025)
BackgroundStrengthening infectious disease surveillance systems is critical to prevent the spread of diseases, particularly in resource-limited settings. Digital health tools such as the Surveillance Outbreak Response Management and Analysis System (SORMAS) offer real-time reporting and data management. This study assessed the performance of SORMAS in Kwango Province, Democratic Republic of Congo (DRC), focusing on two implementation models: facility-level model, where health workers at health facilities entered data directly into SORMAS, and health zone-level model, where data entry was centralized at the health zone office.MethodsFrom July 2022 to December 2024, SORMAS was piloted for case-based reporting of epidemic-prone diseases in the Kenge Health Zone via the facility-level model and in 13 other health zones via the health zone-level model. We evaluated the completeness and timeliness of case-based reporting, as well as concordance with the conventional paper-based weekly epidemiological reports (WERs). SORMAS user characteristics were obtained through a telephone survey.ResultsA total of 2,950 cases were registered in SORMAS between July 2022 and August 2024. The completeness of non-mandatory epidemiological data exceeded 80% across both implementation models. Timely reporting (within 1 day) was significantly greater under the facility-level model (46.0%) than under the health zone-level model (5.0%). SORMAS reported more cases than WERs under facility-level implementation, whereas WERs captured more cases than SORMAS under the health zone-level model.ConclusionSORMAS is a viable tool for enhancing disease surveillance in the DRC, particularly when implemented at the health facility level. This pilot demonstrates the potential of digital tools to improve outbreak preparedness and response in resource-limited settings.