Influenza Surveillance Under the Shadow of COVID-19 Pandemic: Phylogenetic Analysis of Influenza A (H1N1)pdm09 Viruses in Türkiye in 2019-20 Season

Creative Commons License

Gorkem E. R. A., Cubuk C., DURUSU TANRIÖVER M., BAĞCI BOSI A. T., Holyavkin C., ÖZIŞIK L., ...Daha Fazla

FLORA INFEKSIYON HASTALIKLARI VE KLINIK MIKROBIYOLOJI DERGISI, cilt.29, sa.4, ss.488-501, 2024 (ESCI) identifier identifier

Özet

Introduction: Influenza is a severe health problem with a massive burden of disease mainly affecting older adults, young children, and people with multimorbidity. Global Influenza Hospital Surveillance Network (GIHSN) is an active hospital surveillance network that generates solid epidemiological and medical evidence to understand influenza severity and related risk factors and support vaccine strain selection. We aimed to analyze the data from the GIHSN Project 2019-20- T & uuml;rkiye to link clinical and viral data to infer potential viral genomic risk factors in hospitalized influenza patients and to get an overview of the genetic characterization of circulating influenza viruses in this cohort. Materials and Methods: This epidemiological active surveillance study followed the GIHSN core protocol and was conducted between the 51st week of 2019 and the 18th week of 2020. Results: Two hundred seventy-three patients were enrolled in the study, and influenza positivity was detected in 84 patients (30.8%). The duration of hospitalization for patients aged five and above was 10.5 +/- 1.9 days, whereas it was 7.2 +/- 0.6 for patients under five (p= 0.047). There was a significant difference in the duration of hospitalization between patients with at least one comorbidity (12.2 +/- 2.4) and those without any comorbidity (5.4 +/- 0.6) (p= 0.013). Genetic characterization could be performed in 25 isolated strains, and 23 of them belonged to the 6B.1A.5A and 6B.1A.5a.1 subclades. The HA1 V537A mutation was associated with older age and longer hospital stays, while the H155L and N16S viral mutations were linked to severe disease. Conclusion: Combining viral genomic data with hospital surveillance is essential for determining the risk factors for severe disease, developing vaccination strategies, understanding viral evolution, and establishing an early warning system to improve pandemic preparedness plans.