ABSTRACT
Historically SARS-CoV-2 secondary attack rates (SAR) have been based on PCR positivity on screening symptomatic contacts, this misses transmission events and identifies only symptomatic contacts who are PCR positive at the time of sampling. We used serology to detect the relative transmissibility of Alpha Variant of Concern (VOC) to non-VOC SARS-CoV-2 to calculate household secondary attack rates. We identified index patients diagnosed with Alpha and non-VOC SARS-CoV-2 across two London Hospitals between November 2020 and January 2021 during a prolonged and well adhered national lockdown. We completed a household seroprevalence survey and found that 61.8% of non-VOC exposed household contacts were seropositive compared to 82.1% of Alpha exposed household contacts. The odds of infection doubled with exposure to an index diagnosed with Alpha. There was evidence of transmission events in almost all households. Our data strongly support that estimates of SAR should include serological data to improve accuracy and understanding.
ABSTRACT
Patients with haematological malignancies are at increased risk of severe disease and death from COVID-19 and are less likely to mount humoral immune responses to COVID-19 vaccination, with the B cell malignancies a particularly high-risk group. Our COV-VACC study is evaluating the immune response to COVID-19 vaccination in patients with B cell malignancies. Eligible patients were either receiving active treatment or had received treatment within the last 24 months. Patients were vaccinated with either the BNT162b2 (Pfizer-BioNTech) (n=41) or ChAdOx1 nCoV-19 (Oxford-AstraZeneca) (n=14) vaccines. The median age of participants was 60 years (range: 27-82) and 50% were receiving systemic anti-cancer therapy (SACT) at the time of vaccination. This interim analysis from the first 55 participants describes anti-S seropositivity rates, neutralising antibody activity and association with peripheral lymphocyte subsets. After the first vaccine dose, 36% overall had detectable anti-S antibodies rising to 42% after the second dose. Sera from seropositive patients was assessed for neutralisation activity in vitro. Of the seropositive patients after first dose (n=17), only 41% were able to neutralise SARS-CoV-2 pseudotyped virus with a 50% inhibitory dilution factor (ID50) of >1:50. After two doses (n=21) 57% of the seropositive patients had detectable neutralisation activity (median ID50 of 1:469, range 1:70 - 1:3056). Total blood lymphocyte, CD19, CD4 and CD56 counts were significantly associated with seropositivity. Patients vaccinated more than 6 months after completing therapy were significantly more likely to develop antibodies than those within 6 months of treatment or on active treatment; OR: 5.93 (1.29 - 27.28). Our data has important implications for patients with B cell malignancies as we demonstrate a disconnect between anti-S seropositivity and virus neutralisation in vitro following vaccination against COVID-19. Urgent consideration should be given to revaccinating patients with B-cell malignancies after completion of anti-cancer treatment as large numbers currently remain at high risk of infection with the increasing transmission of SARS-CoV-2 in many countries.
Subject(s)
COVID-19ABSTRACT
Summary: Lipid nanoparticle (LNP) encapsulated self-amplifying RNA (saRNA) is a novel technology formulated as a low dose vaccine against COVID-19.Methods: A phase I first-in-human dose-ranging trial of a saRNA COVID-19 vaccine candidate LNP-nCoVsaRNA, was conducted at Imperial Clinical Research Facility, and participating centres in London, UK. Participants received two intramuscular (IM) injections of LNP-nCoVsaRNA at six different dose levels, 0·1-10·0mg, given four weeks apart. An open-label dose escalation was followed by a dose evaluation. Solicited adverse events (AEs) were collected for one week from enrolment, with follow-up at regular intervals (1-8 weeks). The binding and neutralisation capacity of anti-SARS-CoV-2 antibody raised in participant sera was measured by means of an anti-Spike (S) IgG ELISA, immunoblot, SARS-CoV-2 pseudoneutralisation and wild type neutralisation assays.Findings: 192 healthy individuals with no history or serological evidence of COVID-19, aged 18-45 years were enrolled. The vaccine was well tolerated with no serious adverse events related to vaccination. Seroconversion at week six whether measured by ELISA or immunoblot was related to dose (both p<0·001), ranging from 8% to 61% in ELISA and 46% to 87% in the immunoblot assay.Concurrent anti-S IgG ranged from GM concentration (95% CI) 74 (45-119) at 0·1mg to 1023 (468-2236) ng/ml at 5·0mg (p<0·001) and was not higher at 10·0mg. Neutralisation of SARS-CoV-2 by participant sera was measurable in 15-48% depending on dose level received.Interpretation: Encapsulated saRNA is safe for clinical development and is immunogenic at low dose levels. Modifications to optimise humoral responses are required to realise its potential as an effective vaccine against SARS-CoV-2.Trial Registration: (ISRCTN17072692, EudraCT 2020-001646-20)Funding Statement: Medical Research Council UKRI (MC_PC_19076 and MC_UU_12023/23), National Institute for Health Research, Partners of Citadel and Citadel Securities, Sir Joseph Hotung Charitable Settlement, Jon Moulton Charity Trust.Declaration of Interests: P.F.M. and R.J.S. are co-inventors on a patent application covering this SARS-CoV-2 saRNA vaccine. All other authors have nothing to declare. Ethics Approval Statement: This study was approved in the UK by the Medicines and Healthcare products Regulatory Agency and the North East - York Research Ethics Committee (reference 20/SC/0145).
Subject(s)
COVID-19 , Pyruvate Carboxylase Deficiency Disease , Hemoglobin SC DiseaseABSTRACT
BackgroundThe number of proposed prognostic models for COVID-19, which aim to predict disease outcomes, is growing rapidly. It is not known whether any are suitable for widespread clinical implementation. We addressed this question by independent and systematic evaluation of their performance among hospitalised COVID-19 cases. MethodsWe conducted an observational cohort study to assess candidate prognostic models, identified through a living systematic review. We included consecutive adults admitted to a secondary care hospital with PCR-confirmed or clinically diagnosed community-acquired COVID-19 (1st February to 30th April 2020). We reconstructed candidate models as per their original descriptions and evaluated performance for their original intended outcomes (clinical deterioration or mortality) and time horizons. We assessed discrimination using the area under the receiver operating characteristic curve (AUROC), and calibration using calibration plots, slopes and calibration-in-the-large. We calculated net benefit compared to the default strategies of treating all and no patients, and against the most discriminating predictor in univariable analyses, based on a limited subset of a priori candidates. ResultsWe tested 22 candidate prognostic models among a cohort of 411 participants, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. The highest AUROCs were achieved by the NEWS2 score for prediction of deterioration over 24 hours (0.78; 95% CI 0.73-0.83), and a novel model for prediction of deterioration <14 days from admission (0.78; 0.74-0.82). Calibration appeared generally poor for models that used probability outcomes. In univariable analyses, admission oxygen saturation on room air was the strongest predictor of in-hospital deterioration (AUROC 0.76; 0.71-0.81), while age was the strongest predictor of in-hospital mortality (AUROC 0.76; 0.71-0.81). No prognostic model demonstrated consistently higher net benefit than using the most discriminating univariable predictors to stratify treatment, across a range of threshold probabilities. ConclusionsOxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated offer incremental value for patient stratification to these univariable predictors.