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F1000Res. 2017 Nov 29;6:2067. doi: 10.12688/f1000research.13198.1. eCollection 2017.

Prediction of influenza vaccine effectiveness for the influenza season 2017/18 in the US.

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Department of Pathology, Galveston National Laboratory, University of Texas Medical Branch, Galveston, TX, 77555, USA.
Biomed Protection, Galveston, TX, 77550, USA.


Vaccination against seasonal influenza viruses is the most effective way to prevent infection. A key factor in the effectiveness of the seasonal influenza vaccine is its immunological compatibility with the circulating viruses during the season. The high evolutionary rate, antigenic shift and antigenic drift of influenza viruses, represents the main obstacle for correct prediction of the vaccine effectiveness for an upcoming flu season. Conventional structural and phylogenetic approaches for assessment of vaccine effectiveness have had a limited success in prediction of vaccine efficacy in the past. Recently, a novel bioinformatics approach for assessment of effectiveness of seasonal influenza vaccine was proposed. Here, this approach was used for prediction of the vaccine effectiveness for the influenza season 2017/18 in US.


H3N2; influenza virus; phylogenetic analysis; seasonal influenza vaccine effectiveness

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