H1N1 and seasonal influenza vaccine safety in the vaccine safety datalink project uri icon

abstract

  • BACKGROUND: The emergence of pandemic H1N1 influenza virus in early 2009 prompted the rapid licensure and use of H1N1 monovalent inactivated (MIV) and live, attenuated (LAMV) vaccines separate from seasonal trivalent inactivated (TIV) and live, attenuated (LAIV) influenza vaccines. A robust influenza immunization program in the U.S. requires ongoing monitoring of potential adverse events associated with vaccination. PURPOSE: To prospectively conduct safety monitoring of H1N1 and seasonal influenza vaccines during the 2009-2010 season. METHODS: The Vaccine Safety Datalink (VSD) Project monitors approximately 9.2 million members in eight U.S. medical care organizations. Electronic data on vaccines and pre-specified adverse events were updated and analyzed weekly for signal detection from November 2009 to April 2010 using either a self-controlled design or a current versus historical comparison. Statistical signals were further evaluated using alternative approaches to identify temporal clusters and to control for time-varying confounders. RESULTS: As of May 1, 2010, a total of 1,345,663 MIV, 267,715 LAMV, 2,741,150 TIV, and 157,838 LAIV doses were administered in VSD. No significant associations were noted during sequential analyses for Guillain-Barre syndrome, most other neurologic outcomes, and allergic and cardiac events. For MIV, a statistical signal was observed for Bell's palsy for adults aged >/=25 years on March 31, 2010, using the self-controlled approach. Subsequent analyses revealed no significant temporal cluster. Case-centered logistic regression adjusting for seasonality demonstrated an OR for Bell's palsy of 1.26 (95% CI=0.97, 1.63). CONCLUSIONS: No major safety problems following H1N1 or seasonal influenza vaccines were detected in the 2009-2010 season in weekly sequential analyses. Seasonality likely contributed to the Bell's palsy signal following MIV. Prospective safety monitoring followed by rigorous signal refinement is critical to inform decision-making by regulatory and public health agencies.

publication date

  • 2011