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1.
Stat Methods Med Res ; : 9622802221106720, 2022 Jul 15.
Article in English | MEDLINE | ID: covidwho-1932991

ABSTRACT

We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are applied to data from people admitted to hospital with COVID-19, to estimate the probability of admission to intensive care unit, the probability of death in hospital for patients before and after intensive care unit admission, the lengths of stay in hospital, and how all these vary with age and gender. One modelling framework is based on defining transition-specific hazard functions for competing risks. A less commonly used framework defines partially-latent subpopulations who will experience each subsequent event, and uses a mixture model to estimate the probability that an individual will experience each event, and the distribution of the time to the event given that it occurs. We compare the advantages and disadvantages of these two frameworks, in the context of the COVID-19 example. The issues include the interpretation of the model parameters, the computational efficiency of estimating the quantities of interest, implementation in software and assessing goodness of fit. In the example, we find that some groups appear to be at very low risk of some events, in particular intensive care unit admission, and these are best represented by using 'cure-rate' models to define transition-specific hazards. We provide general-purpose software to implement all the models we describe in the flexsurv R package, which allows arbitrarily flexible distributions to be used to represent the cause-specific hazards or times to events.

2.
BMJ Open ; 12(6): e054336, 2022 06 28.
Article in English | MEDLINE | ID: covidwho-1909750

ABSTRACT

INTRODUCTION: Understanding the effectiveness and durability of protection against SARS-CoV-2 infection conferred by previous infection and COVID-19 is essential to inform ongoing management of the pandemic. This study aims to determine whether prior SARS-CoV-2 infection or COVID-19 vaccination in healthcare workers protects against future infection. METHODS AND ANALYSIS: This is a prospective cohort study design in staff members working in hospitals in the UK. At enrolment, participants are allocated into cohorts, positive or naïve, dependent on their prior SARS-CoV-2 infection status, as measured by standardised SARS-CoV-2 antibody testing on all baseline serum samples and previous SARS-CoV-2 test results. Participants undergo monthly antibody testing and fortnightly viral RNA testing during follow-up and based on these results may move between cohorts. Any results from testing undertaken for other reasons (eg, symptoms, contact tracing) or prior to study entry will also be captured. Individuals complete enrolment and fortnightly questionnaires on exposures, symptoms and vaccination. Follow-up is 12 months from study entry, with an option to extend follow-up to 24 months.The primary outcome of interest is infection with SARS-CoV-2 after previous SARS-CoV-2 infection or COVID-19 vaccination during the study period. Secondary outcomes include incidence and prevalence (both RNA and antibody) of SARS-CoV-2, viral genomics, viral culture, symptom history and antibody/neutralising antibody titres. ETHICS AND DISSEMINATION: The study was approved by the Berkshire Research Ethics Committee, Health Research Authority (IRAS ID 284460, REC reference 20/SC/0230) on 22 May 2020; the vaccine amendment was approved on 12 January 2021. Participants gave informed consent before taking part in the study.Regular reports to national and international expert advisory groups and peer-reviewed publications ensure timely dissemination of findings to inform decision making. TRIAL REGISTRATION NUMBER: ISRCTN11041050.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Health Personnel , Humans , Incidence , Multicenter Studies as Topic , Prospective Studies , RNA, Viral , Reinfection , SARS-CoV-2 , United Kingdom/epidemiology , Vaccination
3.
Lancet Respir Med ; 9(7): 773-785, 2021 07.
Article in English | MEDLINE | ID: covidwho-1337040

ABSTRACT

BACKGROUND: Mortality rates in hospitalised patients with COVID-19 in the UK appeared to decline during the first wave of the pandemic. We aimed to quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital. METHODS: In this multicentre prospective observational cohort study, the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK recruited a prospective cohort of patients with COVID-19 admitted to 247 acute hospitals in England, Scotland, and Wales during the first wave of the pandemic (between March 9 and Aug 2, 2020). We included all patients aged 18 years and older with clinical signs and symptoms of COVID-19 or confirmed COVID-19 (by RT-PCR test) from assumed community-acquired infection. We did a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and in-hospital mortality, adjusting for confounders (demographics, comorbidities, and severity of illness) and quantifying potential mediators (level of respiratory support and steroid treatment). The primary outcome was weekly in-hospital mortality at 28 days, defined as the proportion of patients who had died within 28 days of admission of all patients admitted in the observed week, and it was assessed in all patients with an outcome. This study is registered with the ISRCTN Registry, ISRCTN66726260. FINDINGS: Between March 9, and Aug 2, 2020, we recruited 80 713 patients, of whom 63 972 were eligible and included in the study. Unadjusted weekly in-hospital mortality declined from 32·3% (95% CI 31·8-32·7) in March 9 to April 26, 2020, to 16·4% (15·0-17·8) in June 15 to Aug 2, 2020. Reductions in mortality were observed in all age groups, in all ethnic groups, for both sexes, and in patients with and without comorbidities. After adjustment, there was a 32% reduction in the risk of mortality per 7-week period (odds ratio [OR] 0·68 [95% CI 0·65-0·71]). The higher proportions of patients with severe disease and comorbidities earlier in the first wave (March and April) than in June and July accounted for 10·2% of this reduction. The use of respiratory support changed during the first wave, with gradually increased use of non-invasive ventilation over the first wave. Changes in respiratory support and use of steroids accounted for 22·2%, OR 0·95 (0·94-0·95) of the reduction in in-hospital mortality. INTERPRETATION: The reduction in in-hospital mortality in patients with COVID-19 during the first wave in the UK was partly accounted for by changes in the case-mix and illness severity. A significant reduction in in-hospital mortality was associated with differences in respiratory support and critical care use, which could partly reflect accrual of clinical knowledge. The remaining improvement in in-hospital mortality is not explained by these factors, and could be associated with changes in community behaviour, inoculum dose, and hospital capacity strain. FUNDING: National Institute for Health Research and the Medical Research Council.


Subject(s)
COVID-19/mortality , Hospital Mortality , Aged , Aged, 80 and over , COVID-19/epidemiology , Clinical Protocols , Cohort Studies , Female , Humans , Male , Middle Aged , Prospective Studies , United Kingdom/epidemiology , World Health Organization
4.
Lancet ; 397(10283): 1459-1469, 2021 04 17.
Article in English | MEDLINE | ID: covidwho-1174548

ABSTRACT

BACKGROUND: Increased understanding of whether individuals who have recovered from COVID-19 are protected from future SARS-CoV-2 infection is an urgent requirement. We aimed to investigate whether antibodies against SARS-CoV-2 were associated with a decreased risk of symptomatic and asymptomatic reinfection. METHODS: A large, multicentre, prospective cohort study was done, with participants recruited from publicly funded hospitals in all regions of England. All health-care workers, support staff, and administrative staff working at hospitals who could remain engaged in follow-up for 12 months were eligible to join The SARS-CoV-2 Immunity and Reinfection Evaluation study. Participants were excluded if they had no PCR tests after enrolment, enrolled after Dec 31, 2020, or had insufficient PCR and antibody data for cohort assignment. Participants attended regular SARS-CoV-2 PCR and antibody testing (every 2-4 weeks) and completed questionnaires every 2 weeks on symptoms and exposures. At enrolment, participants were assigned to either the positive cohort (antibody positive, or previous positive PCR or antibody test) or negative cohort (antibody negative, no previous positive PCR or antibody test). The primary outcome was a reinfection in the positive cohort or a primary infection in the negative cohort, determined by PCR tests. Potential reinfections were clinically reviewed and classified according to case definitions (confirmed, probable, or possible) and symptom-status, depending on the hierarchy of evidence. Primary infections in the negative cohort were defined as a first positive PCR test and seroconversions were excluded when not associated with a positive PCR test. A proportional hazards frailty model using a Poisson distribution was used to estimate incidence rate ratios (IRR) to compare infection rates in the two cohorts. FINDINGS: From June 18, 2020, to Dec 31, 2020, 30 625 participants were enrolled into the study. 51 participants withdrew from the study, 4913 were excluded, and 25 661 participants (with linked data on antibody and PCR testing) were included in the analysis. Data were extracted from all sources on Feb 5, 2021, and include data up to and including Jan 11, 2021. 155 infections were detected in the baseline positive cohort of 8278 participants, collectively contributing 2 047 113 person-days of follow-up. This compares with 1704 new PCR positive infections in the negative cohort of 17 383 participants, contributing 2 971 436 person-days of follow-up. The incidence density was 7·6 reinfections per 100 000 person-days in the positive cohort, compared with 57·3 primary infections per 100 000 person-days in the negative cohort, between June, 2020, and January, 2021. The adjusted IRR was 0·159 for all reinfections (95% CI 0·13-0·19) compared with PCR-confirmed primary infections. The median interval between primary infection and reinfection was more than 200 days. INTERPRETATION: A previous history of SARS-CoV-2 infection was associated with an 84% lower risk of infection, with median protective effect observed 7 months following primary infection. This time period is the minimum probable effect because seroconversions were not included. This study shows that previous infection with SARS-CoV-2 induces effective immunity to future infections in most individuals. FUNDING: Department of Health and Social Care of the UK Government, Public Health England, The National Institute for Health Research, with contributions from the Scottish, Welsh and Northern Irish governments.


Subject(s)
Antibodies, Viral/blood , COVID-19/epidemiology , COVID-19/immunology , Health Personnel , Adult , Asymptomatic Infections , COVID-19/diagnosis , COVID-19 Nucleic Acid Testing , England , Female , Follow-Up Studies , Humans , Male , Middle Aged , Pandemics , Prospective Studies , Reinfection , Risk Factors , SARS-CoV-2
5.
J Infect ; 82(5): 151-161, 2021 05.
Article in English | MEDLINE | ID: covidwho-1155535

ABSTRACT

BACKGROUND: Screening for SARS-CoV-2 antibodies is under way in some key worker groups; how this adds to self-reported COVID-19 illness is unclear. In this study, we investigate the association between self-reported belief of COVID-19 illness and seropositivity. METHODS: Cross-sectional study of three key worker streams comprising (A) Police and Fire & Rescue (2 sites) (B) healthcare workers (1 site) and (C) healthcare workers with previously positive PCR result (5 sites). We collected self-reported signs and symptoms of COVID-19 and compared this with serology results from two SARS-CoV-2 immunoassays (Roche Elecsys® and EUROIMMUN). RESULTS: Between 01 and 26 June, we recruited 2847 individuals (Stream A: 1,247, Stream B: 1,546 and Stream C: 154). Amongst those without previous positive PCR tests, 687/2,579 (26%) reported belief they had COVID-19, having experienced compatible symptoms; however, only 208 (30.3%) of these were seropositive on both immunoassays. Both immunoassays had high sensitivities relative to previous PCR positivity (>93%); there was also limited decline in antibody titres up to 110 days post symptom onset. Symptomatic but seronegative individuals had differing symptom profiles and shorter illnesses than seropositive individuals. CONCLUSION: Non-COVID-19 respiratory illness may have been mistaken for COVID-19 during the outbreak; laboratory testing is more specific than self-reported key worker beliefs in ascertaining past COVID-19 disease.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Cross-Sectional Studies , Humans , Self Report , United Kingdom
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