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Evaluation of the National Influenza Sentinel Surveillance System in Tanzania, March 2021
Abstract
Background
Globally, seasonal epidemics are estimated to result about 3 to 5 million cases of severe illness, and about 290 000 to 650 000 respiratory deaths yearly. In order to facilitate early detection of Avian Influenza (AI), Tanzania through the Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) initiated a sentinel surveillance system in 2008, for determining the disease burden and detect any new strain capable of causing pandemic.: Objectives:To assess the usefulness of the system, its attributes as well as to ascertain if the system meets its objectives.
Methodology: Data were collected through review of documents and interview of key stakeholders involved on the entire cascade of the system. Case definition (ILI and SARI), results and demographic characteristics of each patient were obtained from Laboratory Information System at National Influenza Laboratory (NIL). The system attributes were evaluated using Centre for disease prevention and control updated guidelines for evaluating public health surveillance system (2007)- Morbidity and Mortality Weekly Report (MMWR).
Results : A total of 1731 samples were collected from influenza suspects in 2019 from sixteen sentinel sites where 52.7% were male. Laboratory confirmed cases were 21% (363/1731) with PVP of 21%. Most patients detected for influenza A; those presented with ILI symptoms were more likely to have influenza B than those with SARI. 55% met the TAT, 40% of case-based forms were incomplete filled, data consistency was poor with 23% discrepancy. Data accuracy was good with an average performance of 100%.
Conclusion and recommendations: The System has met its objectives regarding that it is useful, sensitive, flexible, stable, well representative and able to generate accurate data by the average performance of 100%, which entails to a realistic estimation for the burden of influenza disease in the country.
To address incompleteness of case-based forms, supportive supervision and training should also focus on proper documentation. Increasing more sentinel sites will maximize coverage and level of system representativeness. The case definition should be reviewed to improve PVP. We need to develop a full electronic system for capturing surveillance data.