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Assessment and mitigation of bias in influenza and COVID-19 vaccine effectiveness analyses - IVY Network, September 1, 2022-March 30, 2023.

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Author information

Affiliations

  • 1. Influenza Division, National Center for Immunization and Respiratory Diseases, CDC, United States.
      Authors
    • Lewis NM 1
    • Harker EJ 1
    • DeCuir J 1
    • Ellington S 1
    (4 authors)
  • 2. University of Michigan, Ann Arbor, MI, United States.
      Authors
    • Leis A 2
    • Lauring AS 2
    • Martin ET 2
    (3 authors)
  • 3. Vanderbilt University Medical Center, Nashville, TN, United States.
      Authors
    • Zhu Y 3
    • Talbot HK 3
    • Grijalva CG 3
    • Halasa N 3
    • Chappell JD 3
    • Johnson CA 3
    • Rice TW 3
    • Casey JD 3
    • Self WH 3
    (9 authors)
  • 4. Baylor Scott & White Health, TX, United States; Baylor College of Medicine, Temple, TX, United States.
      Authors
    • Gaglani M 4
    (1 author)
  • 5. Baylor College of Medicine, Temple, TX, United States.
      Authors
    • Ghamande S 5
    (1 author)
    • Show all (29)

ORCIDs linked to this article

Vaccine, 07 Nov 2024, 43(Pt 2):126492
https://doi.org/10.1016/j.vaccine.2024.126492 PMID: 39515195 

Abstract 

Background

In test-negative studies of vaccine effectiveness (VE), including patients with co-circulating, vaccine-preventable, respiratory pathogens in the control group for the pathogen of interest can introduce a downward bias on VE estimates.

Methods

A multicenter sentinel surveillance network in the US prospectively enrolled adults hospitalized with acute respiratory illness from September 1, 2022-March 31, 2023. We evaluated bias in estimates of VE against influenza-associated and COVID-19-associated hospitalization based on: inclusion vs exclusion of patients with a co-circulating virus among VE controls; observance of VE against the co-circulating virus (rather than the virus of interest), unadjusted and adjusted for vaccination against the virus of interest; and observance of influenza or COVID-19 against a sham outcome of respiratory syncytial virus (RSV).

Results

Overall VE against influenza-associated hospitalizations was 6 percentage points lower when patients with COVID-19 were included in the control group, and overall VE against COVID-19-associated hospitalizations was 2 percentage points lower when patients with influenza were included in the control group. Analyses of VE against the co-circulating virus and against the sham outcome of RSV showed that downward bias was largely attributable the correlation of vaccination status across pathogens, but also potentially attributable to other sources of residual confounding in VE models.

Conclusion

Excluding cases of confounding respiratory pathogens from the control group in VE analysis for a pathogen of interest can reduce downward bias. This real-world analysis demonstrates that such exclusion is a helpful bias mitigation strategy, especially for measuring influenza VE, which included a high proportion of COVID-19 cases among controls.

Full text links 

Read article at publisher's site: https://doi.org/10.1016/j.vaccine.2024.126492

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Funding 

Funders who supported this work.

Centers for Disease Control and Prevention

    National Center for Immunization and Respiratory Diseases (2)