Molecular surveillance of influenza A and B in namibia: seasonal patterns and clinical correlates (2021-2023).

BACKGROUND

Influenza viruses cause widespread respiratory illness. Due to limited surveillance, influenza dynamics in Namibia remain poorly understood. This study aimed to conduct molecular surveillance of influenza A and B viruses from 2021 − 2023, characterize circulating strains, and explore symptom correlations to inform public health responses and improve case management.

METHODS

From October 2021 to December 2023, nasopharyngeal or oropharyngeal swabs were collected from patients with influenza-like illness (ILI) in a clinic-based setting. Viral detection, subtyping, and genotyping were conducted using real-time reverse-transcription polymerase chain reaction (RT-PCR). Seasonal trends of influenza and SARS-CoV-2, as well as symptom co-occurrence patterns were examined using statistical and visualization tools in R, Epi Info, and SPSS.

RESULTS

A total of 1186 nasopharyngeal and oropharyngeal samples form ILI patients were collected. Influenza was detected in 25.7% (280/1088) of samples, with influenza A accounting for 20.2% (235/1162) and influenza B for 4.3% (45/1049). Among influenza A cases, A(H1N1)pdm09 was detected in 26.4% (62/235) and A(H3N2) in 67% (157/235). Influenza B (Victoria) accounted for nearly all influenza B cases (96%), while no influenza B(Yamagata) cases were detected. SARS-CoV-2 was detected in 19.2% (227/1182) of samples. Significant associations were observed between influenza infection and cough (OR 2.2, 95% CI 1.2 − 3.9, p = 0.0076) and myalgia (OR 2.3, 95% CI 1.5 − 3.6, p = 0.00044). The strongest correlation was between loss of smell and loss of taste (r = 0.71, p < 0.001).

CONCLUSIONS

Influenza activity followed distinct seasonal patterns, with influenza A more common than B. Cough and myalgia were stronger predictors of infection, while sore throat and loss of smell were less so. These findings highlight the importance of ongoing influenza surveillance and preparedness to manage seasonal outbreaks, while symptom correlations can enhance case management and monitoring.