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<0.05). Patients who presented with SARI were more likely to have influenza as compared to those who had ILI symptoms (aOR 0.75, 95% CI [0.64-0.89], P=0.001). Those who presented with ILI symptoms were more likely to be detected for influenza B as compared to those with SARI.
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.