2022
DOI: 10.1016/s1473-3099(21)00460-6
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Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study

Abstract: Background COVID-19 vaccines show excellent efficacy in clinical trials and effectiveness in real-world data, but some people still become infected with SARS-CoV-2 after vaccination. This study aimed to identify risk factors for post-vaccination SARS-CoV-2 infection and describe the characteristics of post-vaccination illness. Methods This prospective, community-based, nested, case-control study used self-reported data (eg, on demographics, geographical location, health… Show more

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Cited by 692 publications
(723 citation statements)
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References 35 publications
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“…25 Data is also emerging that fully vaccinated patients who develop a "breakthrough" COVID-19 infection are substantially less likely to develop PASC compared with an unvaccinated individual. 26 Taken together, these data support vaccination efforts not only to primarily prevent COVID-19 and PASC but also to improve symptoms in patients who already have PASC.…”
Section: ■ Vaccinationsupporting
confidence: 52%
“…25 Data is also emerging that fully vaccinated patients who develop a "breakthrough" COVID-19 infection are substantially less likely to develop PASC compared with an unvaccinated individual. 26 Taken together, these data support vaccination efforts not only to primarily prevent COVID-19 and PASC but also to improve symptoms in patients who already have PASC.…”
Section: ■ Vaccinationsupporting
confidence: 52%
“…We can hypothesize that this can come from the 11 participants out of 27 positive to COVID-19 (40.7%) who were already vaccinated at the time of outcome assessment. Indeed, the vaccinated participants are apparently more often completely asymptomatic, even if they are 65 years or older, as indicated by the study of Antonelli et al [ 67 ]. Third, the physical activity level was self-reported.…”
Section: Discussionmentioning
confidence: 99%
“…These include the use of large datasets of self-reported symptoms and PCR test results, collected via mobile phone applications, and an array of modelling methods including logistic regression [ 4 , 5 ] and a hierarchical Gaussian process model [ 6 ] and machine learning models [ 7 , 8 ]. Self-reported symptoms have also been used to identify changes in the symptomatology and disease profiles associated with vaccination [ 9 ] and the introduction of new variants of concern [ 10 ]. Accurately characterizing the relationship between specific symptoms or clusters of symptoms and the presence or absence of a positive test for COVID-19 may contribute to the formulation and enhancement of case definitions for both acute and ‘long’ COVID-19, and to criteria for prioritising access to testing [ 11 ].…”
Section: Introductionmentioning
confidence: 99%