The average postvaccination hemagglutination-inhibition antibody titers against influenza A(H1N1)pdm09 remained similar across successive vaccinations, but the rate of waning efficacy was directly proportional to number of vaccinations, according to results published in The Journal of Infectious Diseases.

Antibody waning in the context of longitudinal vaccination history has not been extensively studied; therefore, investigators developed a Bayesian hierarchical model to assess the effects of sequential vaccination on hemagglutination-inhibition antibody boosting and waning in a longitudinal cohort of children and adults from 2011 to 2016.

Measurements from 2057 serum specimens collected longitudinally from 388 individuals were assessed. Investigators found that although average postvaccination antibody titers were similar across successive vaccinations, the rate of antibody waning increased with each inoculation. Estimates predicted a decrease in antibody half-life from 32 (95% credible interval, 22-61) months following first vaccination to 9 (95% credible interval, 7-15) months after a seventh shot.

That the A(H1N1)pdm09 vaccine strain did not change during the study period offered a unique opportunity to study antibody dynamics after repeated exposure to identical antigens. Investigators noted that circulating A(H1N1)pdm09 underwent an antigenic shift during this time, meaning vaccine-specific antibody titer may not be an accurate measure of protection for all individuals. The influenza A(H3N2) viruses also evolve more quickly, leading to its association with larger outbreaks and more severe disease. Therefore, it is also a priority to determine how antibody develops and persists after repeated vaccination and infection. However, investigators acknowledged that modelling the dynamics of influenza A(H3N2) antibody is complicated if attempts to account for additional unique circulating and vaccine strain antigens are made.

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The results represented, according to investigators, “a first step towards the development of models that can be used to develop optimized vaccination schedules that account for long term antibody dynamics.” They also suggested that, “development of these analytic tools that can be paired with longitudinal cohort studies of the development of influenza immunity could inform the development of the next generation of influenza vaccines and the policy decisions regarding their optimal use.”

Reference

Zelner J, Petrie JG, Trangucci R, Martin ET, Monto AS. Effects of sequential influenza A(H1N1)pdm09 vaccination on antibody waning [published online February 4, 2019]. J Infect Dis. doi: 10.1093/infdis/jiz055