Characterization of influenza infection in a high-income urban setting in Nairobi, Kenya.

BACKGROUND

Influenza viruses are an important cause of respiratory infections across all age groups. Information on occurrence and magnitude of influenza virus infections in different populations in Kenya however remains scanty, compromising estimation of influenza disease burden. This study examined influenza infection in an urban high-income setting in Nairobi to establish its prevalence and activity of influenza viruses, and evaluated diagnostic performance of a rapid influenza diagnostic test.

METHODOLOGY: A cross-sectional hospital-based study was conducted in six private health facilities located within high-income residential areas in Nairobi from January 2019 to July 2020. Patients of all ages presenting with influenza-like illness (ILI) were recruited into the study. Detection of influenza virus was conducted using rapid diagnosis and reverse transcription-polymerase chain reaction (RT-PCR). Data were summarized using descriptive statistics and tests of association. Sensitivity, specificity and area under receiver operating characteristics curve was calculated to establish diagnostic accuracy of the rapid diagnosis test.

RESULTS

The study recruited 125 participants with signs and symptoms of ILI, of whom 21 (16.8%) were positive for influenza viruses. Of all the influenza-positive cases, 17 (81.0%) were influenza type A of which 70.6% were pandemic H1N1 (A/H1N1 2009). Highest detection was observed among children aged 5-10 years. Influenza virus mostly circulated during the second half of the year, and fever, general fatigue and muscular and joint pain were significantly observed among participants with influenza virus. Sensitivity and specificity of the diagnostic test was 95% (95% confidence interval 75.1-99.9) and 100% (95% confidence interval 96.5-100.0), respectively.

CONCLUSIONS

Findings of this study shows continuous but variable activity of influenza virus throughout the year in this population, with substantial disease burden. The findings highlight the need for continuous epidemiologic surveillance including genetic surveillance to monitor activity and generate data to inform vaccine introduction or development, and other interventions.