Nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination.

BackgroundMost studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. MethodsPlasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FindingsStrong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months. Nasal and plasma anti-S IgG remained elevated for at least 12 months with high plasma neutralising titres against all variants. Of 180 with complete data, 160 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal. Samples 12 months after admission showed no association between nasal IgA and plasma IgG responses, indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. InterpretationThe decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. Research in contextO_ST_ABSEvidence before the studyC_ST_ABSWhile systemic immunity to SARS-CoV-2 is important in preventing severe disease, mucosal immunity prevents viral replication at the point of entry and reduces onward transmission. We searched PubMed with search terms "mucosal", "nasal", "antibody", "IgA", "COVID-19", "SARS-CoV-2", "convalescent" and "vaccination" for studies published in English before 20th July 2022, identifying three previous studies examining the durability of nasal responses that generally show nasal antibody to persist for 3 to 9 months. However, these studies were small or included individuals with mild COVID-19. One study of 107 care-home residents demonstrated increased salivary IgG (but not IgA) after two doses of mRNA vaccine, and another examined nasal antibody responses after infection and subsequent vaccination in 20 cases, demonstrating rises in both nasal IgA and IgG 7 to 10 days after vaccination. Added value of this studyStudying 446 people hospitalised for COVID-19, we show durable nasal and plasma IgG responses to ancestral (B.1 lineage) SARS-CoV-2, Delta and Omicron (BA.1) variants up to 12 months after infection. Nasal antibody induced by infection with pre-Omicron variants, bind Omicron virus in vitro better than plasma antibody. Although nasal and plasma IgG responses were enhanced by vaccination, Omicron binding responses did not reach levels equivalent to responses for ancestral SARS-CoV-2. Using paired plasma and nasal samples collected approximately 12 months after infection, we show that nasal IgA declines and shows a minimal response to vaccination whilst plasma antibody responses to S antigen are well maintained and boosted by vaccination. Implications of all the available evidenceAfter COVID-19 and subsequent vaccination, Omicron binding plasma and nasal antibody responses are only moderately enhanced, supporting the need for booster vaccinations to maintain immunity against SARS-CoV-2 variants. Notably, there is distinct compartmentalisation between nasal IgA and plasma IgA and IgG responses after vaccination. These findings highlight the need for vaccines that induce robust and durable mucosal immunity.

Omicron B.1.1.529 variant infections associated with severe disease are uncommon in a COVID-19 under-vaccinated, high SARS-CoV-2 seroprevalence population in Malawi

BackgroundThe B.1.1.529 (Omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the fourth COVID-19 pandemic wave across the southern African region, including Malawi. The seroprevalence of SARS-CoV-2 antibodies and their association with epidemiological trends of hospitalisations and deaths are needed to aid locally relevant public health policy decisions. MethodsWe conducted a population-based serosurvey from December 27, 2021 to January 17, 2022, in 7 districts across Malawi to determine the seroprevalence of SARS-CoV-2 antibodies. Primary sampling units (PSU) were selected using probability proportionate to the number of households based on the 2018 national census, followed by second-stage sampling units that were selected from listed households. A random systematic sample of households was selected from each PSU within the 7 districts. Serum samples were tested for antibodies against SARS-CoV-2 receptor binding domain using WANTAI SARS-CoV-2 Receptor Binding Domain total antibody commercial enzyme-linked immunosorbent assay (ELISA). We also evaluated COVID-19 epidemiologic trends in Malawi, including cases, hospitalizations and deaths from April 1, 2021 through April 30, 2022, collected using the routine national COVID-19 reporting system. ResultsSerum samples were analysed from 4619 participants (57% female; 65% aged 14 to 50 years), of whom 1018 (22%) had received a COVID-19 vaccine. The overall assay-adjusted seroprevalence was 86.3% (95% confidence interval (CI), 85.1% to 87.5%). Seroprevalence was lowest among children <13 years of age (66%) and highest among adults 18 to 50 years of age (82%). Seroprevalence was higher among vaccinated compared to unvaccinated participants (96% vs. 77%; risk ratio, 6.65; 95% CI, 4.16 to 11.40). Urban residents were more likely to test seropositive than those living in rural settings (91% vs. 78%; risk ratio, 2.81; 95% CI, 2.20 to 3.62). National COVID-19 data showed that at least a two-fold reduction in the proportion of hospitalisations and deaths among the reported cases in the fourth wave compared to the third wave (hospitalization, 10.7% (95% CI, 10.2 to 11.3) vs 4.86% (95% CI, 4.52 to 5.23), p<0.0001; deaths, 3.48% (95% CI, 3.18 to 3.81) vs 1.15% (95% CI, 1.00 to 1.34), p<0.0001). ConclusionWe report reduction in proportion of hospitalisations and deaths from SARS-CoV-2 infections during the Omicron variant dominated wave in Malawi, in the context of high SARS-CoV-2 seroprevalence but low COVID-19 vaccination coverage. These findings suggest that COVID-19 vaccination policy in high seroprevalence settings may need to be amended from mass campaigns to targeted vaccination of at-risk populations.

Outcome of COVID-19 in hospitalised immunocompromised patients: an analysis of the WHO ISARIC CCP-UK prospective cohort study.

BackgroundImmunocompromised patients may be at higher risk of mortality if hospitalised with COVID-19 compared with immunocompetent patients. However, previous studies have been contradictory. We aimed to determine whether immunocompromised patients were at greater risk of in-hospital death, and how this risk changed over the pandemic. MethodsWe included patients >=19yrs with symptomatic community-acquired COVID-19 recruited to the ISARIC WHO Clinical Characterisation Protocol UK. We defined immunocompromise as: immunosuppressant medication preadmission, cancer treatment, organ transplant, HIV, or congenital immunodeficiency. We used logistic regression to compare the risk of death in both groups, adjusting for age, sex, deprivation, ethnicity, vaccination and co-morbidities. We used Bayesian logistic regression to explore mortality over time. FindingsBetween 17/01/2020 and 28/02/2022 we recruited 156,552 eligible patients, of whom 21,954 (14%) were immunocompromised. 29% (n=6,499) of immunocompromised and 21% (n=28,608) of immunocompetent patients died in hospital. The odds of in-hospital mortality were elevated for immunocompromised patients (adjOR 1.44, 95% CI 1.39-1.50, p<0.001). As the pandemic progressed, in-hospital mortality reduced more slowly for immunocompromised patients than for immunocompetent patients. This was particularly evident with increasing age: the probability of the reduction in hospital mortality being less for immunocompromised patients aged 50-69yrs was 88% for men and 83% for women, and for those >80yrs was 99% for men, and 98% for women. ConclusionsImmunocompromised patients remain at elevated risk of death from COVID-19. Targeted measures such as additional vaccine doses and monoclonal antibodies should be considered for this group. FundingNational Institute for Health Research; Medical Research Council; Chief Scientist Office, Scotland.

Evaluation of the Implementation of the 4C Mortality Score in United Kingdom hospitals during the second pandemic wave

The 4C Mortality Score (4C Score) was designed to risk stratify hospitalised patients with COVID-19. We assessed inclusion of 4C Score in COVID-19 management guidance and its documentation in patients case notes in January 2021 in UK hospitals. 4C Score was included within guidance by 50% of sites, though score documentation in case notes was highly variable. Higher documentation of 4C Score was associated with score integration within admissions proformas, inclusion of 4C Score variables or link to online calculator, and management decisions. Integration of 4C Score within clinical pathways may encourage more widespread use.

Anxiety and Depression among Medical Doctors in Catalonia, Italy, and the UK during the COVID-19 Pandemic

Healthcare workers have had the longest and most direct exposure to COVID-19 and consequently may suffer from poor mental health. We conducted one of the first repeated multi-country analysis of the mental wellbeing of medical doctors (n=5,275) at two timepoints during the COVID-19 pandemic (June 2020 and November/December 2020) to understand the prevalence of anxiety and depression, as well as associated risk factors. Rates of anxiety and depression were highest in Italy (24.6% and 20.1%, June 2020), second highest in Catalonia (24.6% and 17.4%, June 2020), and lowest in the UK (11.7% and 13.7%, June 2020). Across all countries, higher risk of anxiety and depression symptoms are found among women, individuals below 60 years old, those feeling vulnerable/exposed at work, and those in poor health. We did not find systematic differences in mental health measures between the two rounds of data collection, hence we cannot discard that the mental health repercussions of the pandemic are persistent.

A Prenylated dsRNA Sensor Protects Against Severe COVID-19 and is Absent in Horseshoe Bats

Cell autonomous antiviral defenses can inhibit the replication of viruses and reduce transmission and disease severity. To better understand the antiviral response to SARS-CoV-2, we used interferon-stimulated gene (ISG) expression screening to reveal that OAS1, through RNase L, potently inhibits SARS-CoV-2. We show that while some people can express a prenylated OAS1 variant, that is membrane-associated and blocks SARS-CoV-2 infection, other people express a cytosolic, nonprenylated OAS1 variant which does not detect SARS-CoV-2 (determined by the splice-acceptor SNP Rs10774671). Alleles encoding nonprenylated OAS1 predominate except in people of African descent. Importantly, in hospitalized patients, expression of prenylated OAS1 was associated with protection from severe COVID-19, suggesting this antiviral defense is a major component of a protective antiviral response. Remarkably, approximately 55 million years ago, retrotransposition ablated the OAS1 prenylation signal in horseshoe bats (the presumed source of SARS-CoV-2). Thus, SARS-CoV-2 never had to adapt to evade this defense. As prenylated OAS1 is widespread in animals, the billions of people that lack a prenylated OAS1 could make humans particularly vulnerable to the spillover of coronaviruses from horseshoe bats.

Genetic epidemiology of SARS-CoV-2 transmission in renal dialysis units - a high risk community-hospital interface

ObjectivesPatients requiring haemodialysis are at increased risk of serious illness with SARS-CoV-2 infection. To improve the understanding of transmission risks in six Scottish renal dialysis units, we utilised the rapid whole-genome sequencing data generated by the COG-UK consortium. MethodsWe combined geographical, temporal and genomic sequence data from the community and hospital to estimate the probability of infection originating from within the dialysis unit, the hospital or the community using Bayesian statistical modelling and compared these results to the details of epidemiological investigations. ResultsOf 671 patients, 60 (8.9%) became infected with SARS-CoV-2, of whom 16 (27%) died. Within-unit and community transmission were both evident and an instance of transmission from the wider hospital setting was also demonstrated. ConclusionsNear-real-time SARS-CoV-2 sequencing data can facilitate tailored infection prevention and control measures, which can be targeted at reducing risk in these settings.

Long Covid in adults discharged from UK hospitals after Covid-19: A prospective, multicentre cohort study using the ISARIC WHO Clinical Characterisation Protocol.

Structured AbstractO_ST_ABSObjectivesC_ST_ABSThe long-term consequences of severe Covid-19 requiring hospital admission are not well characterised. The objective of this study was to establish the long-term effects of Covid-19 following hospitalisation and the impact these may have on patient reported outcome measures. DesignA multicentre, prospective cohort study with at least 3 months follow-up of participants admitted to hospital between 5th February 2020 and 5th October 2020. Setting31 hospitals in the United Kingdom. Participants327 hospitalised participants discharged alive from hospital with confirmed/high likelihood SARS-CoV-2 infection. Main outcome measures and comparisonsThe primary outcome was self-reported recovery at least ninety days after initial Covid-19 symptom onset. Secondary outcomes included new symptoms, new or increased disability (Washington group short scale), breathlessness (MRC Dyspnoea scale) and quality of life (EQ5D-5L). We compared these outcome measures across age, comorbidity status and in-hospital Covid-19 severity to identify groups at highest risk of developing long-term difficulties. Multilevel logistic and linear regression models were built to adjust for the effects of patient and centre level risk factors on these outcomes. ResultsIn total 53.7% (443/824) contacted participants responded, yielding 73.8% (327/443) responses with follow-up of 90 days or more from symptom onset. The median time between symptom onset of initial illness and completing the participant questionnaire was 222 days (Interquartile range (IQR) 189 to 269 days). In total, 54.7% (179/327) of participants reported they did not feel fully recovered. Persistent symptoms were reported by 93.3% (305/325) of participants, with fatigue the most common (82.8%, 255/308), followed by breathlessness (53.5%, 175/327). 46.8% (153/327) reported an increase in MRC dyspnoea scale of at least one grade. New or worse disability was reported by 24.2% (79/327) of participants. Overall (EQ5D-5L) summary index was significantly worse at the time of follow-up (median difference 0.1 points on a scale of 0 to 1, IQR: -0.2 to 0.0). Females under the age of 50 years were five times less likely to report feeling recovered (adjusted OR 5.09, 95% CI 1.64 to 15.74), were more likely to have greater disability (adjusted OR 4.22, 95% CI 1.12 to 15.94), twice as likely to report worse fatigue (adjusted OR 2.06, 95% CI 0.81 to 3.31) and seven times more likely to become more breathless (adjusted OR 7.15, 95% CI 2.24 to 22.83) than men of the same age. ConclusionsSurvivors of Covid-19 experienced long-term symptoms, new disability, increased breathlessness, and reduced quality of life. These findings were present even in young, previously healthy working age adults, and were most common in younger females. Policymakers should fund further research to identify effective treatments for long-Covid and ensure healthcare, social care and welfare support is available for individuals with long-Covid. Section 1: What is already known on this topicO_LILong-term symptoms after hospitalisation for Covid-19 have been reported, but it is not clear what impact this has on quality of life. C_LIO_LIIt is not known which patient groups are most likely to have long-term persistent symptoms following hospitalisation for Covid-19, or if this differs by disease severity. C_LI Section 2: What this study addsO_LIMore than half of patients reported not being fully recovered 7 months after onset of Covid-19 symptoms. C_LIO_LIPreviously healthy participants and those under the age of 50 had higher odds of worse long-term outcomes compared to older participants and those with comorbidities. C_LIO_LIYounger women and those with more severe acute disease in-hospital had the worst long-term outcomes. C_LIO_LIPolicy makers need to ensure there is long-term support for people experiencing long-Covid and should plan for lasting long-term population morbidity. Funding for research to understand mechanisms underlying long-Covid and identify potential interventions for testing in randomised trials is urgently required. C_LI

Changes in UK hospital mortality in the first wave of COVID-19: the ISARIC WHO Clinical Characterisation Protocol prospective multicentre observational cohort study

BackgroundMortality rates of UK patients hospitalised with COVID-19 appeared to fall during the first wave. We quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital. MethodsThe International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK recruited a prospective cohort admitted to 247 acute UK hospitals with COVID-19 in the first wave (March to August 2020). Outcome was hospital mortality within 28 days of admission. We performed a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and hospital mortality adjusting for confounders (demographics, comorbidity, illness severity) and quantifying potential mediators (respiratory support and steroids). FindingsUnadjusted hospital mortality fell from 32.3% (95%CI 31.8, 32.7) in March/April to 16.4% (95%CI 15.0, 17.8) in June/July 2020. Reductions were seen in all ages, ethnicities, both sexes, and in comorbid and non-comorbid patients. After adjustment, there was a 19% reduction in the odds of mortality per 4 week period (OR 0.81, 95%CI 0.79, 0.83). 15.2% of this reduction was explained by greater disease severity and comorbidity earlier in the epidemic. The use of respiratory support changed with greater use of non-invasive ventilation (NIV). 22.2% (OR 0.94, 95%CI 0.94, 0.96) of the reduction in mortality was mediated by changes in respiratory support. InterpretationThe fall in hospital mortality in COVID-19 patients during the first wave in the UK was partly accounted for by changes in case mix and illness severity. A significant reduction was associated with differences in respiratory support and critical care use, which may partly reflect improved clinical decision making. The remaining improvement in mortality is not explained by these factors, and may relate to community behaviour on inoculum dose and hospital capacity strain. FundingNIHR & MRC Key points / Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSRisk factors for mortality in patients hospitalised with COVID-19 have been established. However there is little literature regarding how mortality is changing over time, and potential explanations for why this might be. Understanding changes in mortality rates over time will help policy makers identify evolving risk, strategies to manage this and broader decisions about public health interventions. Added value of this studyMortality in hospitalised patients at the beginning of the first wave was extremely high. Patients who were admitted to hospital in March and early April were significantly more unwell at presentation than patients who were admitted in later months. Mortality fell in all ages, ethnic groups, both sexes and in patients with and without comorbidity, over and above contributions from falling illness severity. After adjustment for these variables, a fifth of the fall in mortality was explained by changes in the use of respiratory support and steroid treatment, along with associated changes in clinical decision-making relating to supportive interventions. However, mortality was persistently high in patients who required invasive mechanical ventilation, and in those patients who received non-invasive ventilation outside of critical care. Implications of all the available evidenceThe observed reduction in hospital mortality was greater than expected based on the changes seen in both case mix and illness severity. Some of this fall can be explained by changes in respiratory care, including clinical learning. In addition, introduction of community policies including wearing of masks, social distancing, shielding of vulnerable patients and the UK lockdown potentially resulted in people being exposed to less virus. The decrease in mortality varied depending on the level of respiratory support received. Patients receiving invasive mechanical ventilation have persistently high mortality rates, albeit with a changing case-mix, and further research should target this group. Severe COVID-19 disease has primarily affected older people in the UK. Many of these people, but not all have significant frailty. It is essential to ensure that patients and their families remain at the centre of decision-making, and we continue with an individualised approach to their treatment and care.

The circulating SARS-CoV-2 spike variant N439K maintains fitness while evading antibody-mediated immunity

SARS-CoV-2 can mutate to evade immunity, with consequences for the efficacy of emerging vaccines and antibody therapeutics. Herein we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is the most divergent region of S, and provide epidemiological, clinical, and molecular characterization of a prevalent RBM variant, N439K. We demonstrate that N439K S protein has enhanced binding affinity to the hACE2 receptor, and that N439K virus has similar clinical outcomes and in vitro replication fitness as compared to wild- type. We observed that the N439K mutation resulted in immune escape from a panel of neutralizing monoclonal antibodies, including one in clinical trials, as well as from polyclonal sera from a sizeable fraction of persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.

Development and validation of the 4C Deterioration model for adults hospitalised with COVID-19

Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.

Genetic mechanisms of critical illness in Covid-19

The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3 GenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland. We identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 10-8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 x 10-30). We identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.

What is the recovery rate and risk of long-term consequences following a diagnosis of COVID-19? - A harmonised, global longitudinal observational study

IntroductionVery little is known about possible clinical sequelae that may persist after resolution of the acute Coronavirus Disease 2019 (COVID-19). A recent longitudinal cohort from Italy including 143 patients recovered after hospitalisation with COVID-19 reported that 87% had at least one ongoing symptom at 60 day follow-up. Early indications suggest that patients with COVID-19 may need even more psychological support than typical ICU patients. The assessment of risk factors for longer term consequences requires a longitudinal study linked to data on pre-existing conditions and care received during the acute phase of illness. Methods and analysisThis is an international open-access prospective, observational multi-site study. It will enrol patients following a diagnosis of COVID-19. Tier 1 is developed for following up patients day 28 post-discharge, additionally at 3 to 6 months intervals. This module can be used to identify sub-sets of patients experiencing specific symptomatology or syndromes for further follow up. A Tier 2 module will be developed for in-clinic, in-depth follow up. The primary aim is to characterise physical consequences in patients post-COVID-19. Secondary aim includes estimating the frequency of and risk factors for post-COVID-19 medical sequalae, psychosocial consequences and post-COVID-19 mortality. A subset of patients will have sampling to characterize longer term antibody, innate and cell-mediated immune responses to SARS-CoV-2. Ethics and disseminationThis collaborative, open-access study aims to characterize the frequency of and risk factors for long-term consequences and characterise the immune response over time in patients following a diagnosis of COVID-19 and facilitate standardized and longitudinal data collection globally. The outcomes of this study will inform strategies to prevent long term consequences; inform clinical management, direct rehabilitation, and inform public health management to reduce overall morbidity and improve outcomes of COVID-19. Article summaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIAs an international prospective, observational study we provide open-access standardised tools that can be adapted by any site interested in following up patients with COVID-19, for independent or combined analysis, to forward knowledge into short and long term consequences of COVID-19. C_LIO_LIThis study aims to inform strategies to prevent longer term sequalae; inform clinical management, rehabilitation, and public health management strategies to reduce morbidity and improve outcomes. C_LIO_LIThe protocol will be used for a sub-set of patients, already included in the existing cohort of more than 85,973 individuals hospitalized with confirmed COVID-19 infection across 42 countries (as of 20 July 2020), using the ISARIC/WHO standardized Core- or RAPID Case Report Forms (CRFs). C_LIO_LIThe data will be linked with data on pre-existing comorbidities, presentation, clinical care and treatments documented in the existing cohort already documented using the ISARIC/WHO standardized Core- or RAPID CRFs. C_LIO_LIThe data collection tool is developed to facilitate wide dissemination and uptake, by enabling patient self-assessment, however, follow up of patients requires consent and resources, which might limit the uptake and bias the data towards countries /sites with capacity to follow up patients over time. C_LI

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score

ObjectivesTo develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. DesignProspective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. Setting260 hospitals across England, Scotland, and Wales. ParticipantsAdult patients ([≥]18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. Main outcome measuresIn-hospital mortality. ResultsThere were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 - 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score [≥]15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score [≤]3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). ConclusionsWe have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. Study registrationISRCTN66726260

SARS-CoV-2 viral load dynamics, duration of viral shedding and infectiousness: a living systematic review and meta-analysis

BackgroundViral load kinetics and the duration of viral shedding are important determinants for disease transmission. We aim i) to characterize viral load dynamics, duration of viral RNA, and viable virus shedding of SARS-CoV-2 in various body fluids and ii) to compare SARS-CoV-2 viral dynamics with SARS-CoV-1 and MERS-CoV. MethodsMedline, EMBASE, Europe PMC, preprint servers and grey literature were searched to retrieve all articles reporting viral dynamics and duration of SARS-CoV-2, SARS-CoV-1 and MERS-CoV shedding. We excluded case reports and case series with < 5 patients, or studies that did not report shedding duration from symptom onset. PROSPERO registration: CRD42020181914. FindingsSeventy-nine studies on SARS-CoV-2, 8 on SARS-CoV-1, and 11 on MERS-CoV were included. Mean SARS-CoV-2 RNA shedding duration in upper respiratory tract, lower respiratory tract, stool and serum were 17.0, 14.6, 17.2 and 16.6 days, respectively. Maximum duration of SARS-CoV-2 RNA shedding reported in URT, LRT, stool and serum were 83, 59, 35 and 60 days, respectively. Pooled mean duration of SARS-CoV-2 RNA shedding was positively associated with age (p=0.002), but not gender (p = 0.277). No study to date has cultured live virus beyond day nine of illness despite persistently high viral loads. SARS-CoV-2 viral load in the upper respiratory tract appears to peak in the first week of illness, while SARS-CoV-1 and MERS-CoV peak later. ConclusionAlthough SARS-CoV-2 RNA shedding in respiratory and stool can be prolonged, duration of viable virus is relatively short-lived. Thus, detection of viral RNA cannot be used to infer infectiousness. High SARS-CoV-2 titers are detectable in the first week of illness with an early peak observed at symptom onset to day 5 of illness. This review underscores the importance of early case finding and isolation, as well as public education on the spectrum of illness. However, given potential delays in the isolation of patients, effective containment of SARS-CoV-2 may be challenging even with an early detection and isolation strategy. FundingNo funding was received.

Genomic epidemiology of SARS-CoV-2 spread in Scotland highlights the role of European travel in COVID-19 emergence

SARS-CoV-2, the causative agent of COVID-19, emerged in Wuhan, China in December 2019 and spread rapidly throughout the world. Understanding the introductions of this new coronavirus in different settings may assist control efforts and the establishment of frameworks to support rapid response in future infectious disease outbreaks. We investigated the first four weeks of emergence of the SARS-CoV-2 virus in Scotland after the first case reported on the 1st March 2020. We obtained full genome sequences from 452 individuals with a laboratory-confirmed diagnosis of COVID-19, representing 20% of all cases until 1st April 2020 (n=2310). This permitted a genomic epidemiology approach to study the introductions and spread of the SARS-2 virus in Scotland. From combined phylogenetic and epidemiological analysis, we estimated at least 113 introductions of SARS-CoV-2 into Scotland during this period. Clusters containing multiple sequences suggestive of onward transmission occurred in 48/86 (56%). 42/86 (51%) clusters had no known international travel history indicating undetected introductions. The majority of viral sequences were most closely related to those circulating in other European countries, including Italy, Austria and Spain. Travel-associated introductions of SARS-CoV-2 into Scotland predated travel restrictions in the UK and other European countries. The first local transmission occurred three days after the first case. A shift from travel-associated to sustained community transmission was apparent after only 11 days. Undetected introductions occurred prior to the first known case of COVID-19. Earlier travel restrictions and quarantine measures might have resulted in fewer introductions into Scotland, thereby reducing the number of cases and the subsequent burden on health services. The high number of introductions and transmission rates were likely to have impacted on national contact tracing efforts. Our results also demonstrate that local real-time genomic epidemiology can be used to monitor transmission clusters and facilitate control efforts to restrict the spread of COVID-19. FundingMRC (MC UU 1201412), UKRI/Wellcome (COG-UK), Wellcome Trust Collaborator Award (206298/Z/17/Z - ARTIC Network; TCW Wellcome Trust Award 204802/Z/16/Z Research in contextO_ST_ABSEvidence before this studyC_ST_ABSCoronavirus disease-2019 (COVID-19) was first diagnosed in Scotland on the 1st of March 2020 following the emergence of the causative severe acute respiratory system coronavirus 2 (SARS-CoV-2) virus in China in December 2019. During the first month of the outbreak in Scotland, 2310 positive cases of COVID-19 were detected, associated with 1832 hospital admissions, 207 intensive care admissions and 126 deaths. The number of introductions into Scotland and the source of those introductions was not known prior to this study. Added value of this studyUsing a combined phylogenetic and epidemiological approach following real-time next generation sequencing of 452 SARS-CoV-2 samples, it was estimated that the virus was introduced to Scotland on at least 113 occasions, mostly from other European countries, including Italy, Austria and Spain. Localised outbreaks occurred in the community across multiple Scottish health boards, within healthcare facilities and an international conference and community transmission was established rapidly, before local and international lockdown measures were introduced.

Epidemiology of seasonal coronaviruses: Establishing the context for COVID-19 emergence

Public health preparedness for coronavirus disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal human coronaviruses (sCoVs) and other cocirculating viruses in the West of Scotland, UK. We analyzed routine diagnostic data for >70,000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43 and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity.

Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions

Since first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. using a transmission model, we estimate a basic reproductive number of 3.11 (95%CI, 2.39-4.13); 58-76% of transmissions must be prevented to stop increasing; Wuhan case ascertainment of 5.0% (3.6-7.4); 21022 (11090-33490) total infections in Wuhan 1 to 22 January. Changes to previous versionO_LIcase data updated to include 22 Jan 2020; we did not use cases reported after this period as cases were reported at the province level hereafter, and large-scale control interventions were initiated on 23 Jan 2020; C_LIO_LIimproved likelihood function, better accounting for first 41 confirmed cases, and now using all infections (rather than just cases detected) in Wuhan for prediction of infection in international travellers; C_LIO_LIimproved characterization of uncertainty in parameters, and calculation of epidemic trajectory confidence intervals using a more statistically rigorous method; C_LIO_LIextended range of latent period in sensitivity analysis to reflect reports of up to 6 day incubation period in household clusters; C_LIO_LIremoved travel restriction analysis, as different modelling approaches (e.g. stochastic transmission, rather than deterministic transmission) are more appropriate to such analyses. C_LI