ArticlePloS one2025
Evaluation of the performance of the Influenza-like Illness (ILI) surveillance system in the Okai Koi North District, Greater Accra Region, 2022.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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8 authors.
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Abstract
backgroundInfluenza-like Illness (ILI) caused by the influenza virus, causes morbidity in Ghana. Records of ILI outbreaks in recent times and the COVID-19 pandemic disrupted surveillance activities, raises the quest to evaluate the ILI surveillance system. We evaluated the ILI surveillance system of Okai Koi North District to assess the system performance. MATERIALS AND
methodsWe adapted the CDC Updated guidelines for evaluating public health surveillance systems for this evaluation at Okai Koi North District. We extracted and reviewed ILI 2018-2021 morbidity data from the district's sentinel site and the National Influenza Center (NIC). We observed surveillance activities and interviewed key informants using an observational checklist and semi-structured questionnaire. Data were analyzed for frequencies and proportions, and results presented in charts and tables.
resultsOf the 525 suspected samples reported from the district's sentinel site, 58 (11%) of 525 were Influenza positive with PVP, 11%. The system detected outbreaks over the evaluation period and has a year-round case detection. The system requires PCR for the detection of influenza virus. Nine (70%) of 13 staff indicated ILI surveillance system served as the backbone for case identification during the COVID-19 pandemic period. There is (89%) data completeness among sampled forms and data from the district and National Influenza Center. The system relies mostly on international donors. Nine (64%) of 13 staff confirmed no budget allocation for system operation. About 58% (306/525) of the ILI samples were transported to NIC for confirmatory test within the set 48 hours timeline.
conclusionThe system is useful as its meeting most of its objectives and it is sensitive. The system though complex, is flexible, representative, timely in most activities and has good data quality. We urge national stakeholders to establish thresholds for system.
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