Department of Twin Research, King's College London, St Thomas' Hospital, London SE1 7EH, UK.
Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK.
J Infect. 2020 Dec;81(6):931-936. doi: 10.1016/j.jinf.2020.10.011. Epub 2020 Oct 15.
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.
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.
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.
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.
NIHR BRC, CDRF, ZOE global LTD, RST-UKRI/MRC.
目前对于 SARS-CoV-2 感染的真实无症状率的了解有限，对于英国第一波 COVID-19 后基于人群的血清流行率的了解也有限。迄今为止，大多数数据来自住院患者，对一般人群病例或其症状关注甚少。
我们对来自英格兰东南部 TwinsUK 队列的 431 名未选择的普通人群参与者的血清进行了酶联免疫吸附试验分析，这些参与者的年龄为 19-86 岁（中位年龄 48 岁；85%为女性），以针对 SARS-CoV-2 刺突糖蛋白和核衣壳蛋白的 IgM 和 IgG 反应进行了特征描述。382 名参与者通过 COVID Symptom Study App 完成了 14 种 COVID-19 相关症状的前瞻性记录，这使得可以结合个体症状考虑血清学，并在先前基于超过 200 万个体的 PCR 阳性个体建立的预测算法的基础上对 COVID-19 进行估计。
我们证明了 12%（431 名中的 51 名）的血清流行率。在有完整症状数据的 48 名血清阳性个体中，有 9 名（19%）为完全无症状，有 16 名（27%）为核心 COVID-19 症状（发热、咳嗽或嗅觉丧失）无症状。嗅觉丧失对血清阳性的特异性为 95%，而发热、咳嗽和嗅觉丧失组合的特异性为 88%。应用 App 算法，队列中有 34 名个体被预测为新冠病毒阳性，其中 18 名（52%）为血清阳性。
伦敦和英格兰东南部成年人的血清流行率为 12%，在有前瞻性症状记录的血清阳性个体中，有 19%在整个研究期间完全无症状。嗅觉丧失对 SARS-CoV-2 抗体反应显示出最高的症状特异性。
NIHR BRC、CDRF、ZOE 全球 LTD、RST-UKRI/MRC。
