PropertyValue
?:abstract
  • BACKGROUND: Understanding of the true asymptomatic rate of infection of SARS-CoV-2 is currently limited, as is understanding of the population-based seroprevalence after the first wave of COVID-19 within the UK. The majority of data thus far come from hospitalised patients, with little focus on general population cases, or their symptoms. METHODS: We undertook enzyme linked immunosorbent assay characterisation of IgM and IgG responses against SARS-CoV-2 spike glycoprotein and nucleocapsid protein of 431 unselected general-population participants of the TwinsUK cohort from South-East England, aged 19-86 (median age 48; 85% female). 382 participants completed prospective logging of 14 COVID-19 related symptoms via the COVID Symptom Study App, allowing consideration of serology alongside individual symptoms, and a predictive algorithm for estimated COVID-19 previously modelled on PCR positive individuals from a dataset of over 2 million. FINDINGS: We demonstrated a seroprevalence of 12% (51 participants of 431). Of 48 seropositive individuals with full symptom data, nine (19%) were fully asymptomatic, and 16 (27%) were asymptomatic for core COVID-19 symptoms: fever, cough or anosmia. Specificity of anosmia for seropositivity was 95%, compared to 88% for fever cough and anosmia combined. 34 individuals in the cohort were predicted to be Covid-19 positive using the App algorithm, and of those, 18 (52%) were seropositive. INTERPRETATION: Seroprevalence amongst adults from London and South-East England was 12%, and 19% of seropositive individuals with prospective symptom logging were fully asymptomatic throughout the study. Anosmia demonstrated the highest symptom specificity for SARS-CoV-2 antibody response. FUNDING: NIHR BRC, CDRF, ZOE global LTD, RST-UKRI/MRC.
is ?:annotates of
?:creator
?:journal
  • J_Infect
?:license
  • unk
?:publication_isRelatedTo_Disease
is ?:relation_isRelatedTo_publication of
?:source
  • WHO
?:title
  • Estimates of the rate of infection and asymptomatic COVID-19 disease in a population sample from SE England
?:type
?:who_covidence_id
  • #866901
?:year
  • 2020

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