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Background: Influenza is the major public health of concern that accounts for up to one million of total health related global death annually. Objectives: To determine epidemiological trend and associated demographic factors for influenza cases in Tanzania from 2016 to 2019. Methodology: The cross-section study design was conducted using secondary data obtained from laboratory information system from 2016 to 2019. Logistic regression model was used to check the significant predictors for influenza. Results: A total of 7260 samples were collected between 2016 to 2019 from clients with median age of 4 years [IQR=25; 26-1], most samples were from patients aged under five years. Most samples (19%) collected from Mwananyamala hospital. Overall sample collection was lower in 2016, but increased from 2017 to 2019. Trend shows strong evidence of correlation between SARI and ILI case definition on influenza positivity (r=0.78[0.60-0.799]). Laboratory confirmed cases was 17% with higher prevalence of influenza A [12% (881/7260)] as compared to influenza B [5% (373/7260)]. We observed the seasonality of influenza where higher number of cases occurred in rainy and cold seasons (January to June) than the rest of other months. When bivariate and multivariate logistic regression was done, the factors of age, case definition type and sentinel site were significantly associated with influenza positivity (p Conclusion and recommendations Having known the seasonality of the disease apprise the proper allocation of resources for the surveillance activities. Since Influenza viruses may have pandemic potential, surveillance and data review activities are inevitable to create epidemiological awareness for prompt public health action.

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.