Keywords: influenza, influenza vaccine, vaccine effectiveness, biostatistics, computational, vaccines
Influenza is a highly contagious and deadly virus. Influenza vaccine effectiveness fluctuates, and a higher vaccine effectiveness typically results in fewer influenza cases. In the influenza virus there are hemagglutinin and neuraminidase glycoproteins, each with a unique immunogenic function. Currently, only the amount of the hemagglutinin glycoprotein is standardized in the vaccine; therefore, the amount of neuraminidase is unquantified and variable. The influence of the glycoprotein ratio on the influenza vaccine effectiveness was studied. The glycoprotein ratios studied were: hemagglutinin accuracy greater than neuraminidase accuracy, hemagglutinin accuracy equal to neuraminidase accuracy, and hemagglutinin accuracy lower than neuraminidase accuracy.
The accuracy ratios for each influenza season were determined using BLASTp. An ANOVA test resulted in a statistically significant p-value of .026. The glycoprotein ratio where the hemagglutinin glycoprotein’s accuracy was equal to the neuraminidase glycoprotein’s accuracy was most advantageous, with the highest mean vaccine effectiveness and lowest standard deviation. A vaccine effectiveness equation was created to calculate the vaccine effectiveness for an influenza season using the glycoproteins’ accuracies that could be applied to countries without quality influenza surveillance.
The importance of this research is twofold. First, this novel data-analysis experiment supports neuraminidase standardization, as an equal glycoprotein ratio was most beneficial. Second, the percentage of A H3N2 influenza strains subtyped, which the vaccine offers the least protection against, decreases with an equal glycoprotein ratio. Thus, the results suggest that the neuraminidase standardization would increase the influenza vaccine effectiveness and result in fewer influenza cases worldwide.