Evidence map›Paper›PMID 35325923›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2022

Effects of Confounding Bias in Coronavirus Disease 2019 (COVID-19) and Influenza Vaccine Effectiveness Test-Negative Designs Due to Correlated Influenza and COVID-19 Vaccination Behaviors.

Margaret K Doll, Stacy M Pettigrew, Julia Ma, Aman Verma

Open access · bronzeAbstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed
10.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

89 citing papers in PubMed, 112 citations in OpenAlex.

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  5. Influenza vaccine effectiveness against outpatient acute respiratory illness with laboratory-confirmed influenza, United States, 2024-25 season.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
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  17. Estimated Vaccine Effectiveness for Respiratory Syncytial Virus-Related Acute Respiratory Illness in Older Adults: Findings From the First Postlicensure Season.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
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29 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Margaret K DollDepartment of Population Health Sciences, Albany College of Pharmacy and Health Sciences, Albany, New York, USA.ORCID 0000-0002-2125-7820
Stacy M PettigrewDepartment of Population Health Sciences, Albany College of Pharmacy and Health Sciences, Albany, New York, USA.
Julia MaPrecision Analytics, Montreal, Quebec, Canada.
Aman VermaPrecision Analytics, Montreal, Quebec, Canada.
Albany College of Pharmacy and Health Sciences · USMD Precision (Canada) · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe test-negative design is commonly used to estimate influenza and coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE). In these studies, correlated COVID-19 and influenza vaccine behaviors may introduce a confounding bias where controls are included with the other vaccine-preventable acute respiratory illness (ARI). We quantified the impact of this bias on VE estimates in studies where this bias is not addressed.

methodsWe simulated study populations under varying vaccination probabilities, COVID-19 VE, influenza VE, and proportions of controls included with the other vaccine-preventable ARI. Mean bias was calculated as the difference between estimated and true VE. Absolute mean bias in VE estimates was classified as low (<10%), moderate (10% to <20%), and high (≥20%).

resultsWhere vaccination probabilities are positively correlated, COVID-19 and influenza VE test-negative studies with influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ARI controls, respectively, underestimate VE. For COVID-19 VE studies, mean bias was low for all scenarios where influenza represented ≤25% of controls. For influenza VE studies, mean bias was low for all scenarios where SARS-CoV-2 represented ≤10% of controls. Although bias was driven by the conditional probability of vaccination, low VE of the vaccine of interest and high VE of the confounding vaccine increase its magnitude.

conclusionsWhere a low percentage of controls is included with the other vaccine-preventable ARI, bias in COVID-19 and influenza VE estimates is low. However, influenza VE estimates are likely more susceptible to bias. Researchers should consider potential bias and its implications in their respective study settings to make informed methodological decisions in test-negative VE studies.

Indexed as

COVID-19Influenza, HumanInfluenza VaccinesCase-Control StudiesCOVID-19 VaccinesHumansSARS-CoV-2VaccinationVaccine EfficacyCOVID-19 VaccinesInfluenza VaccinesCOVID-19influenzanegativeSARS-CoV-2testvaccine effectiveness

Identifiers

PMID35325923
PMCPMC9129127
OpenAlexW4220727497

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.