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Wiegand RE, Fireman B, Najdowski M, Tenforde MW, Link-Gelles R, Ferdinands JM. Bias and negative values of COVID-19 vaccine effectiveness estimates from a test-negative design without controlling for prior SARS-CoV-2 infection. Nat Commun 2024; 15:10062. [PMID: 39567531 PMCID: PMC11579392 DOI: 10.1038/s41467-024-54404-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 11/08/2024] [Indexed: 11/22/2024] Open
Abstract
Test-negative designs (TNDs) are used to assess vaccine effectiveness (VE). Protection from infection-induced immunity may confound the association between case and vaccination status, but collecting reliable infection history can be challenging. If vaccinated individuals have less infection-induced protection than unvaccinated individuals, failure to account for infection history could underestimate VE, though the bias is not well understood. We simulated individual-level SARS-CoV-2 infection and COVID-19 vaccination histories and a TND. VE against symptomatic infection and VE against severe disease estimates unadjusted for infection history underestimated VE compared to estimates adjusted for infection history, and unadjusted estimates were more likely to be below 0%, which could lead to an incorrect interpretation that COVID-19 vaccines are harmful. TNDs assessing VE immediately following vaccine rollout introduced the largest bias and potential for negative VE against symptomatic infection. Despite the potential for bias, VE estimates from TNDs without prior infection information are useful because underestimation is rarely more than 8 percentage points.
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Affiliation(s)
- Ryan E Wiegand
- Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Morgan Najdowski
- Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Mark W Tenforde
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ruth Link-Gelles
- Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jill M Ferdinands
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Sukik L, Chemaitelly H, Ayoub HH, Coyle P, Tang P, Yassine HM, Al Thani AA, Hasan MR, Al-Kanaani Z, Al-Kuwari E, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Butt AA, Al-Romaihi HE, Al-Thani MH, Al-Khal A, Bertollini R, Abdel-Rahman ME, Abu-Raddad LJ. Effectiveness of two and three doses of COVID-19 mRNA vaccines against infection, symptoms, and severity in the pre-omicron era: A time-dependent gradient. Vaccine 2024; 42:3307-3320. [PMID: 38616439 DOI: 10.1016/j.vaccine.2024.04.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/01/2024] [Accepted: 04/04/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND Vaccines were developed and deployed to combat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to characterize patterns in the protection provided by the BNT162b2 and mRNA-1273 mRNA vaccines against a spectrum of SARS-CoV-2 infection symptoms and severities. METHODS A national, matched, test-negative, case-control study was conducted in Qatar between January 1 and December 18, 2021, utilizing a sample of 238,896 PCR-positive tests and 6,533,739 PCR-negative tests. Vaccine effectiveness was estimated against asymptomatic, symptomatic, severe coronavirus disease 2019 (COVID-19), critical COVID-19, and fatal COVID-19 infections. Data sources included Qatar's national databases for COVID-19 laboratory testing, vaccination, hospitalization, and death. RESULTS Effectiveness of two-dose BNT162b2 vaccination was 75.6% (95% CI: 73.6-77.5) against asymptomatic infection and 76.5% (95% CI: 75.1-77.9) against symptomatic infection. Effectiveness against each of severe, critical, and fatal COVID-19 infections surpassed 90%. Immediately after the second dose, all categories-namely, asymptomatic, symptomatic, severe, critical, and fatal COVID-19-exhibited similarly high effectiveness. However, from 181 to 270 days post-second dose, effectiveness against asymptomatic and symptomatic infections declined to below 40%, while effectiveness against each of severe, critical, and fatal COVID-19 infections remained consistently high. However, estimates against fatal COVID-19 often had wide 95% confidence intervals. Analogous patterns were observed in three-dose BNT162b2 vaccination and two- and three-dose mRNA-1273 vaccination. Sensitivity analyses confirmed the results. CONCLUSION A gradient in vaccine effectiveness exists and is linked to the symptoms and severity of infection, providing higher protection against more symptomatic and severe cases. This gradient intensifies over time as vaccine immunity wanes after the last vaccine dose. These patterns appear consistent irrespective of the vaccine type or whether the vaccination involves the primary series or a booster.
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Affiliation(s)
- Layan Sukik
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar.
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Houssein H Ayoub
- Mathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar; Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar; Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | - Hadi M Yassine
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Asmaa A Al Thani
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Mohammad R Hasan
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | | | | | | | | | | | | | - Hanan F Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K Nasrallah
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA; Hamad Medical Corporation, Doha, Qatar; Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | | | | | | | | | - Manar E Abdel-Rahman
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA; College of Health and Life Sciences, Hamad bin Khalifa University, Doha, Qatar.
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