BACKGROUND: Trivalent inactivated influenza vaccine (TIV) is reformulated annually to contain representative strains of 2 influenza A subtypes (H1N1 and H3N2) and 1 B lineage (Yamagata or Victoria). We describe a sentinel surveillance approach to link influenza variant detection with component-specific vaccine effectiveness (VE) estimation. METHODS: The 2006-2007 TIV included A/NewCaledonia/20/1999(H1N1)-like, A/Wisconsin/67/2005(H3N2)-like, and B/Malaysia/2506/2004(Victoria)-like components. Included participants were individuals >or=9 years of age who presented within 1 week after influenza like illness onset to a sentinel physician between November 2006 and April 2007. Influenza was identified by real-time reverse-transcriptase polymerase chain reaction and/or culture. Isolates were characterized by hemagglutination inhibition assay (HI) and HA1 gene sequence. VE was estimated as 1-[odds ratio for influenza in vaccinated versus nonvaccinated persons]. RESULTS: A total of 841 participants contributed: 69 (8%) were >or=65 years of age; 166 (20%) received the 2006-2007 TIV. Influenza was detected in 337 subjects (40%), distributed as follows: A/H3N2, 242 (72%); A/H1N1, 55 (16%); and B, 36 (11%). All but 1 of the A/H1N1 isolates were well matched, half of A/H3N2 isolates were strain mismatched, and all B isolates were lineage-level mismatched to vaccine. Age-adjusted estimated VE for A/H1N1, A/H3N2, and B components was 92% (95% CI, 40%-91%), 41% (95% CI, 6%-63%), and 19% (95% CI, -112% to 69%), respectively, with an overall VE estimate of 47% (95% CI, 18%-65%). Restriction of the analysis to include only working-age adults resulted in lower VE estimates with wide confidence intervals but similar component-specific trends. CONCLUSIONS: Sentinel surveillance provides a broad platform to link new variant detection and the composite of circulating viruses to annual monitoring of component-specific VE.
BACKGROUND: Trivalent inactivated influenza vaccine (TIV) is reformulated annually to contain representative strains of 2 influenza A subtypes (H1N1 and H3N2) and 1 B lineage (Yamagata or Victoria). We describe a sentinel surveillance approach to link influenza variant detection with component-specific vaccine effectiveness (VE) estimation. METHODS: The 2006-2007 TIV included A/NewCaledonia/20/1999(H1N1)-like, A/Wisconsin/67/2005(H3N2)-like, and B/Malaysia/2506/2004(Victoria)-like components. Included participants were individuals >or=9 years of age who presented within 1 week after influenza like illness onset to a sentinel physician between November 2006 and April 2007. Influenza was identified by real-time reverse-transcriptase polymerase chain reaction and/or culture. Isolates were characterized by hemagglutination inhibition assay (HI) and HA1 gene sequence. VE was estimated as 1-[odds ratio for influenza in vaccinated versus nonvaccinated persons]. RESULTS: A total of 841 participants contributed: 69 (8%) were >or=65 years of age; 166 (20%) received the 2006-2007 TIV. Influenza was detected in 337 subjects (40%), distributed as follows: A/H3N2, 242 (72%); A/H1N1, 55 (16%); and B, 36 (11%). All but 1 of the A/H1N1 isolates were well matched, half of A/H3N2 isolates were strain mismatched, and all B isolates were lineage-level mismatched to vaccine. Age-adjusted estimated VE for A/H1N1, A/H3N2, and B components was 92% (95% CI, 40%-91%), 41% (95% CI, 6%-63%), and 19% (95% CI, -112% to 69%), respectively, with an overall VE estimate of 47% (95% CI, 18%-65%). Restriction of the analysis to include only working-age adults resulted in lower VE estimates with wide confidence intervals but similar component-specific trends. CONCLUSIONS: Sentinel surveillance provides a broad platform to link new variant detection and the composite of circulating viruses to annual monitoring of component-specific VE.
Authors: John J Treanor; H Keipp Talbot; Suzanne E Ohmit; Laura A Coleman; Mark G Thompson; Po-Yung Cheng; Joshua G Petrie; Geraldine Lofthus; Jennifer K Meece; John V Williams; Lashondra Berman; Caroline Breese Hall; Arnold S Monto; Marie R Griffin; Edward Belongia; David K Shay Journal: Clin Infect Dis Date: 2012-07-25 Impact factor: 9.079
Authors: Matthew C Johns; Angelia A Eick; David L Blazes; Seung-eun Lee; Christopher L Perdue; Robert Lipnick; Kelly G Vest; Kevin L Russell; Robert F DeFraites; Jose L Sanchez Journal: PLoS One Date: 2010-05-19 Impact factor: 3.240
Authors: Danuta M Skowronski; Gaston De Serres; Natasha S Crowcroft; Naveed Z Janjua; Nicole Boulianne; Travis S Hottes; Laura C Rosella; James A Dickinson; Rodica Gilca; Pam Sethi; Najwa Ouhoummane; Donald J Willison; Isabelle Rouleau; Martin Petric; Kevin Fonseca; Steven J Drews; Anuradha Rebbapragada; Hugues Charest; Marie-Eve Hamelin; Guy Boivin; Jennifer L Gardy; Yan Li; Trijntje L Kwindt; David M Patrick; Robert C Brunham Journal: PLoS Med Date: 2010-04-06 Impact factor: 11.069