Bias correction methods for test-negative designs in the presence of misclassification

Endo, Akira; Funk, Sebastian; Kucharski, Adam J.

doi:10.1101/19002691

Cited by 2 publications

(2 citation statements)

References 30 publications

(51 reference statements)

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“…We note that no available assay enables perfect differentiation of COVID-19 from nonetiologic detections of SARS-CoV-2; statistical corrections for imperfect test sensitivity and specificity have been proposed to adjust final VE estimates. 36 Further complicating the selection of assays, available data suggest similar viral loads and nucleic acid abundance among individuals with or without symptoms at similar stages of infection. 37,38 However, onset of COVID-19 upper respiratory tract symptoms typically coincides with peak viral shedding.…”

Section: Choice Of Diagnostic Assaysmentioning

confidence: 99%

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines

et al. 2021

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Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. While traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs.Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, non-specific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources.We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.

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Section: Choice Of Diagnostic Assaysmentioning

confidence: 99%

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines

et al. 2021

View full text Add to dashboard Cite

show abstract

“…We note that no available assay enables perfect differentiation of COVID-19 from non-etiologic detections of SARS-CoV-2; statistical corrections for imperfect test sensitivity and specificity have been proposed to adjust final VE estimates. 28 Further complicating the selection of assays, available data suggest similar viral loads and/or nucleic acid abundance among individuals with or without symptoms at similar stages of infection. 29,30 However, onset of COVID-19 upper respiratory tract symptoms typically coincides with peak viral shedding.…”

Section: Outcome Misclassificationmentioning

confidence: 99%

Theoretical framework for retrospective studies of the effectiveness of SARS-CoV-2 vaccines

Lewnard

Patel

Jewell

et al. 2021

Preprint

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Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. These are now in planning amid the ongoing rollout of SARS-CoV-2 vaccines globally. While traditional case-control (TCC) and test-negative design (TND) studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here we review the theoretical basis for estimation of vaccine direct effects under TCC and TND frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, non-specific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The TCC may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The TND reduces but may not eliminate this confounding, for instance if individuals who receive vaccination seek care or testing for less-severe infection. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.

show abstract

Bias correction methods for test-negative designs in the presence of misclassification

Cited by 2 publications

References 30 publications

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines

Theoretical framework for retrospective studies of the effectiveness of SARS-CoV-2 vaccines

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