Disentangling post-vaccination symptoms from early COVID-19. (December 2021)
- Record Type:
- Journal Article
- Title:
- Disentangling post-vaccination symptoms from early COVID-19. (December 2021)
- Main Title:
- Disentangling post-vaccination symptoms from early COVID-19
- Authors:
- Canas, Liane S.
Österdahl, Marc F.
Deng, Jie
Hu, Christina
Selvachandran, Somesh
Polidori, Lorenzo
May, Anna
Molteni, Erika
Murray, Benjamin
Chen, Liyuan
Kerfoot, Eric
Klaser, Kerstin
Antonelli, Michela
Hammers, Alexander
Spector, Tim
Ourselin, Sebastien
Steves, Claire
Sudre, Carole H.
Modat, Marc
Duncan, Emma L. - Abstract:
- Abstract: Background: Identifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app. Methods: We conducted a prospective observational study in 1, 072, 313 UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (N=362, 770) (other than local symptoms at injection site) and were tested for SARS-CoV-2 (N=14, 842), aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models considering UK testing criteria. Findings: Differentiating post-vaccination side-effects alone fromAbstract: Background: Identifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app. Methods: We conducted a prospective observational study in 1, 072, 313 UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (N=362, 770) (other than local symptoms at injection site) and were tested for SARS-CoV-2 (N=14, 842), aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models considering UK testing criteria. Findings: Differentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. Most of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue). Interpretation: Post-vaccination symptoms per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2 or quarantining, to prevent community spread. Funding: UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Chronic Disease Research Foundation, Zoe Limited. … (more)
- Is Part Of:
- EClinicalMedicine. Volume 42(2021)
- Journal:
- EClinicalMedicine
- Issue:
- Volume 42(2021)
- Issue Display:
- Volume 42, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 42
- Issue:
- 2021
- Issue Sort Value:
- 2021-0042-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12
- Subjects:
- COVID-19 detection -- Vaccination -- Side-effects -- Self-reported symptoms -- Mobile technology -- Early detection -- severe acute respiratory syndrome‐related coronavirus 2 (SARS-CoV-2)
AUC Area under the curve -- bMEM Bayesian mixed-effect model -- BMI Body mass index -- CI Confidence interval -- COVID-19 Coronavirus disease 2019 -- CSS COVID Symptoms Study -- DI Data invalid -- IQR inter quartile range -- KCL King's College London -- LFAT Lateral flow antigen test -- LR Logistic Regression -- NHS UK National Health Service of the United Kingdom -- O-AZ Oxford-AstraZeneca adenovirus-vectored vaccine -- PB Pfizer-BoiNTech mRNA vaccine -- RF Random forest -- ROC Receiver operating curve -- rtPCR Reverse transcription polymerase chain reaction -- SARS-CoV-2 Severe acute respiratory syndrome-related coronavirus-2 -- UK United Kingdom of Great Britain and Nothern Ireland
Medicine -- Research -- Periodicals
Medical policy -- Periodicals
Clinical Medicine
Health Policy
Public Health
Medical policy
Medicine -- Research
Periodical
Electronic journals
Periodicals
613 - Journal URLs:
- https://www.sciencedirect.com/science/journal/25895370 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.eclinm.2021.101212 ↗
- Languages:
- English
- ISSNs:
- 2589-5370
- Deposit Type:
- Legaldeposit
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