ArticleBMC public health2023
Introduction and acceptability of the Surveillance Outbreak Response Management and Analysis System (SORMAS) during the COVID-19 pandemic in Côte d'Ivoire.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Mobilome-driven antimicrobial resistance in a one health context: evidence and lessons from Africa.Frontiers in veterinary science · 2026Review
- Evaluation of the acceptability of ESIDA app, a smartphone-based clinical decision support application to improve infectious disease outbreak detection in Tanzania: clinician perspectives.BMC public health · 2025Article
- Evaluating the performance of digital surveillance for epidemic-prone diseases in Kwango Province, Democratic Republic of Congo.Frontiers in public health · 2025Article
- Key Characteristics and Perception of Different Outbreak Surveillance Systems in Côte d'Ivoire: Cross-Sectional Survey Among Users.JMIR public health and surveillance · 2024Article
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7 authors.
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Abstract
backgroundThe Surveillance Outbreak Response Management and Analysis System (SORMAS) has been implemented for various infectious diseases since 2015. 2020, at the beginning of the COVID-19 pandemic, SORMAS was adapted to SARS-CoV2.
methodsWe assessed the acceptability and usability of SORMAS and accompanied its implementation in two pilot regions of Côte d'Ivoire (Abidjan 2 and Gbêkê) from July/August 2021 to March 2022. We conducted 136 semi-structured interviews to cover knowledge on COVID-19, information on conventional surveillance systems for disease monitoring including COVID-19, acceptability of SORMAS, and impact of SORMAS on epidemic preparedness and surveillance. Scores before and 6-8 months after implementation were compared.
resultsSORMAS was implemented in two pilot regions in Côte d'Ivoire. The conventional software for the surveillance of the COVID-19 pandemic by the company MAGPI was maintained in parallel; the additional time needs to enter and manage the data in SORMAS were the main concern. SORMAS acceptance and satisfaction scores were high after the user training, which was prior to implementation, and after 6-8 months of use. The ability of SORMAS to improve COVID-19 preparedness and early detection of cases and contacts was widely acknowledged. To keep the understanding and skills of users up-to-date, regular refresher trainings were requested. The expectation to be able to make decisions based on data produced by SORMAS was high at baseline and the perceived experience after several months of use of the software was very positive. Unfortunately, the link with the laboratories could not be established in the pilot regions, but it is an existing feature of SORMAS that many users were asking for. Following the positive experience using SORMAS for COVID-19, the pilot regions expanded its use for monitoring and management of measles, yellow fever, meningitis, and cholera.
conclusionSORMAS was very well accepted by users and decision makers in the two pilot regions of Côte d'Ivoire and its ability to improve epidemic preparedness and surveillance was acknowledged. If the hurdles of maintenance (tablets, server, and maintaining user skills) are handled sustainably, it can serve as a valid tool to identify, surveil and manage future outbreaks of various infectious diseases in Côte d'Ivoire.
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