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. 2021 Dec 6;73(11):e4244-e4250.
doi: 10.1093/cid/ciaa1884.

Effect of Antigenic Drift on Influenza Vaccine Effectiveness in the United States-2019-2020

Affiliations

Effect of Antigenic Drift on Influenza Vaccine Effectiveness in the United States-2019-2020

Mark W Tenforde et al. Clin Infect Dis. .

Abstract

Background: At the start of the 2019-2020 influenza season, concern arose that circulating B/Victoria viruses of the globally emerging clade V1A.3 were antigenically drifted from the strain included in the vaccine. Intense B/Victoria activity was followed by circulation of genetically diverse A(H1N1)pdm09 viruses that were also antigenically drifted. We measured vaccine effectiveness (VE) in the United States against illness from these emerging viruses.

Methods: We enrolled outpatients aged ≥6 months with acute respiratory illness at 5 sites. Respiratory specimens were tested for influenza by reverse-transcriptase polymerase chain reaction (RT-PCR). Using the test-negative design, we determined influenza VE by virus subtype/lineage and genetic subclades by comparing odds of vaccination in influenza cases versus test-negative controls.

Results: Among 8845 enrollees, 2722 (31%) tested positive for influenza, including 1209 (44%) for B/Victoria and 1405 (51%) for A(H1N1)pdm09. Effectiveness against any influenza illness was 39% (95% confidence interval [CI]: 32-44), 45% (95% CI: 37-52) against B/Victoria and 30% (95% CI: 21-39) against A(H1N1)pdm09-associated illness. Vaccination offered no protection against A(H1N1)pdm09 viruses with antigenically drifted clade 6B.1A 183P-5A+156K HA genes (VE 7%; 95% CI: -14 to 23%) which predominated after January.

Conclusions: Vaccination provided protection against influenza illness, mainly due to infections from B/Victoria viruses. Vaccine protection against illness from A(H1N1)pdm09 was lower than historically observed effectiveness of 40%-60%, due to late-season vaccine mismatch following emergence of antigenically drifted viruses. The effect of drift on vaccine protection is not easy to predict and, even in drifted years, significant protection can be observed.

Keywords: antigenic drift; influenza; test-negative; vaccination; vaccine effectiveness.

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Figures

Figure 1.
Figure 1.
Number of patients enrolled with an acute respiratory illness testing positive for influenza B/Victoria and A(H1N1)pdm09 and percent of enrollees testing positive for influenza by epidemiologic week during the 2019–2020 season. Includes patients with medically attended acute respiratory illness enrolled in the US Influenza Vaccine Effectiveness network between October 29, 2019 through March 26, 2020. Dates on x-axis reflect the reported date of illness onset.
Figure 2.
Figure 2.
Number of sequenced influenza A(H1N1)pdm09 viruses and percentage within genetic subclades by epidemiologic week during the 2019–2020 season. Influenza A(H1N1)pdm09 viruses with cycle threshold values ≤30 from the US Influenza Vaccine Effectiveness network were sent to CDC for whole-genome sequencing. Virus names are abbreviated names for phylogenetic subclades: 5A=A(H1N1)pdm09 183P-5A; 5A+156K=A(H1N1)pdm09 183P-5A+156K; 5A+187A,189E=A(H1N1)pdm09 183P-5A+187A,189E; 5B=A(H1N1)pdm09 183P-5B; 7=A(H1N1)pdm09 183P-7. Dates on the x-axis reflect the reported date of illness onset.
Figure 3.
Figure 3.
Adjusted estimates of influenza vaccine effectiveness, overall and stratified by age group and virus subtype/lineage, for participants enrolled in the US Influenza Vaccine Effectiveness Network for the 2019–2020 season. Vaccine effectiveness was calculated by comparing the odds of current season influenza vaccination in participants who tested positive for influenza and participants who tested negative for influenza, or (1-OR) × 100. Logistic regression models were adjusted for network site, age, presence of ≥1 high-risk conditions, and calendar time in 2-week enrollment intervals.
Figure 4.
Figure 4.
Adjusted estimates of influenza vaccine effectiveness within influenza A(H1N1)pdm09 subclades, overall and stratified by age group, for participants enrolled in the US Influenza Vaccine Effectiveness Network for the 2019–2020 season. Only genetically characterized influenza A(H1N1)pdm09 viruses were included in this analysis. Vaccine effectiveness was calculated by comparing the odds of current season influenza vaccination in participants who tested positive for influenza and participants who tested negative for influenza, or (1-OR) × 100. Logistic regression models were adjusted for network site, age, presence of ≥1 high-risk conditions, and time in 2-week enrollment intervals.

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