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1.
Lancet Healthy Longev ; 3(7): e470-e480, 2022 07.
Article in English | MEDLINE | ID: covidwho-1915225

ABSTRACT

Background: Residents and staff in long-term care facilities have been prioritised for vaccination against SARS-CoV-2, but data on potential waning of vaccine effectiveness and the effect of booster doses in this vulnerable population are scarce. We aimed to evaluate effectiveness of one, two, and three vaccine doses against infection and severe clinical outcomes in staff and residents of long-term care facilities in England over the first year following vaccine roll-out. Methods: The VIVALDI study is a prospective cohort study done in 331 long-term care facilities in England. Residents aged 65 years or older and staff aged 18 years or older were eligible for participation. Participants had routine PCR testing throughout the study period between Dec 8, 2020, and Dec 11, 2021. We retrieved all PCR results and cycle threshold values for PCR-positive samples from routine testing in long-term care facilities, and positive PCR results from clinical testing in hospitals through the UK's COVID-19 Datastore. PCR results were linked to participants using pseudo-identifiers based on individuals' unique UK National Health Service (NHS) numbers, which were also used to retrieve vaccination records from the National Immunisation Management Service, hospitalisation records from NHS England, and deaths data from the Office for National Statistics through the COVID-19 Datastore. In a Cox proportional hazards regression, we estimated vaccine effectiveness against SARS-CoV-2 infection, COVID-19-related hospitalisation, and COVID-19-related death after one, two, and three vaccine doses, separately by previous SARS-CoV-2 exposure. This study is registered with the ISRCTN Registry, ISRCTN 14447421. Findings: 80 186 residents and staff of long-term care facilities had records available for the study period, of whom 15 518 eligible residents and 19 515 eligible staff were included in the analysis. For residents without evidence of previous SARS-CoV-2 exposure, vaccine effectiveness decreased from 61·7% (95% CI 35·1 to 77·4) to 22·0% (-14·9 to 47·0) against infection; from 89·0% (70·6 to 95·9) to 56·3% (30·1 to 72·6) against hospitalisation; and from 96·4% (84·3 to 99·2) to 64·4% (36·1 to 80·1) against death, when comparing 14-83 days after dose two and 84 days or more after dose two. For staff without evidence of previous exposure, vaccine effectiveness against infection decreased slightly from 57·9% (43·1 to 68·9) at 14-83 days after dose two to 42·1% (29·9 to 52·2) at 84 days or more after dose two. There were no hospitalisations or deaths among unexposed staff at 14-83 days, but seven hospitalisations (vaccine effectiveness 91·0% [95% CI 74·3 to 96·8]) and one death were observed at 84 days or more after dose two. High vaccine effectiveness was restored following a third vaccine dose, with vaccine effectiveness in unexposed residents of 72·7% (55·8 to 83·1) against infection, 90·1% (80·6 to 95·0) against hospitalisation, and 97·5% (88·1 to 99·5) against death; and vaccine effectiveness in unexposed staff of 78·2% (70·0 to 84·1) against infection and 95·8% (49·9 to 99·6) against hospitalisation. There were no COVID-19-related deaths among unexposed staff after the third vaccine dose. Interpretation: Our findings showed substantial waning of SARS-CoV-2 vaccine effectiveness against all outcomes in residents of long-term care facilities from 12 weeks after a primary course of ChAdOx1-S or mRNA vaccines. Boosters restored protection, and maximised immunity across all outcomes. These findings show the importance of boosting and the need for ongoing surveillance in this vulnerable cohort. Funding: UK Government Department of Health and Social Care.


Subject(s)
COVID-19 , COVID-19 Vaccines , Humans , Long-Term Care , Prospective Studies , SARS-CoV-2 , State Medicine , Vaccine Efficacy
2.
Lancet Healthy Longev ; 3(7): e461-e469, 2022 07.
Article in English | MEDLINE | ID: covidwho-1915222

ABSTRACT

Background: Older age and frailty are risk factors for poor clinical outcomes following SARS-CoV-2 infection. As such, COVID-19 vaccination has been prioritised for individuals with these factors, but there is concern that immune responses might be impaired due to age-related immune dysregulation and comorbidity. We aimed to study humoral and cellular responses to COVID-19 vaccines in residents of long-term care facilities (LTCFs). Methods: In this observational cohort study, we assessed antibody and cellular immune responses following COVID-19 vaccination in members of staff and residents at 74 LTCFs across the UK. Staff and residents were eligible for inclusion if it was possible to link them to a pseudo-identifier in the COVID-19 datastore, if they had received two vaccine doses, and if they had given a blood sample 6 days after vaccination at the earliest. There were no comorbidity exclusion criteria. Participants were stratified by age (<65 years or ≥65 years) and infection status (previous SARS-CoV-2 infection [infection-primed group] or SARS-CoV-2 naive [infection-naive group]). Anticoagulated edetic acid (EDTA) blood samples were assessed and humoral and cellular responses were quantified. Findings: Between Dec 11, 2020, and June 27, 2021, blood samples were taken from 220 people younger than 65 years (median age 51 years [IQR 39-61]; 103 [47%] had previously had a SARS-CoV-2 infection) and 268 people aged 65 years or older of LTCFs (median age 87 years [80-92]; 144 [43%] had a previous SARS-CoV-2 infection). Samples were taken a median of 82 days (IQR 72-100) after the second vaccination. Antibody responses following dual vaccination were strong and equivalent between participants younger then 65 years and those aged 65 years and older in the infection-primed group (median 125 285 Au/mL [1128 BAU/mL] for <65 year olds vs 157 979 Au/mL [1423 BAU/mL] for ≥65 year olds; p=0·47). The antibody response was reduced by 2·4-times (467 BAU/mL; p≤0·0001) in infection-naive people younger than 65 years and 8·1-times (174 BAU/mL; p≤0·0001) in infection-naive residents compared with their infection-primed counterparts. Antibody response was 2·6-times lower in infection-naive residents than in infection-naive people younger than 65 years (p=0·0006). Impaired neutralisation of delta (1.617.2) variant spike binding was also apparent in infection-naive people younger than 65 years and in those aged 65 years and older. Spike-specific T-cell responses were also significantly enhanced in the infection-primed group. Infection-naive people aged 65 years and older (203 SFU per million [IQR 89-374]) had a 52% lower T-cell response compared with infection-naive people younger than 65 years (85 SFU per million [30-206]; p≤0·0001). Post-vaccine spike-specific CD4 T-cell responses displayed single or dual production of IFN-γ and IL-2 were similar across infection status groups, whereas the infection-primed group had an extended functional profile with TNFα and CXCL10 production. Interpretation: These data reveal suboptimal post-vaccine immune responses within infection-naive residents of LTCFs, and they suggest the need for optimisation of immune protection through the use of booster vaccination. Funding: UK Government Department of Health and Social Care.


Subject(s)
COVID-19 , Vaccines , Aged, 80 and over , Antibodies, Viral , COVID-19 Vaccines , Humans , Immunity, Cellular , Long-Term Care , Middle Aged , SARS-CoV-2 , Vaccination
3.
J Infect Dis ; 226(11): 1877-1881, 2022 Nov 28.
Article in English | MEDLINE | ID: covidwho-1883018

ABSTRACT

General population studies have shown strong humoral response following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination with subsequent waning of anti-spike antibody levels. Vaccine-induced immune responses are often attenuated in frail and older populations, but published data are scarce. We measured SARS-CoV-2 anti-spike antibody levels in long-term care facility residents and staff following a second vaccination dose with Oxford-AstraZeneca or Pfizer-BioNTech. Vaccination elicited robust antibody responses in older residents, suggesting comparable levels of vaccine-induced immunity to that in the general population. Antibody levels are higher after Pfizer-BioNTech vaccination but fall more rapidly compared to Oxford-AstraZeneca recipients and are enhanced by prior infection in both groups.


Subject(s)
COVID-19 , Vaccines , Humans , Aged , SARS-CoV-2 , ChAdOx1 nCoV-19 , BNT162 Vaccine , Long-Term Care , COVID-19/prevention & control , Antibodies, Viral , England
4.
Lancet Healthy Longev ; 3(5): e347-e355, 2022 05.
Article in English | MEDLINE | ID: covidwho-1821559

ABSTRACT

Background: The SARS-CoV-2 omicron variant (B.1.1.529) is highly transmissible, but disease severity appears to be reduced compared with previous variants such as alpha and delta. We investigated the risk of severe outcomes following infection in residents of long-term care facilities. Methods: We did a prospective cohort study in residents of long-term care facilities in England who were tested regularly for SARS-CoV-2 between Sept 1, 2021, and Feb 1, 2022, and who were participants of the VIVALDI study. Residents were eligible for inclusion if they had a positive PCR or lateral flow device test during the study period, which could be linked to a National Health Service (NHS) number, enabling linkage to hospital admissions and mortality datasets. PCR or lateral flow device test results were linked to national hospital admission and mortality records using the NHS-number-based pseudo-identifier. We compared the risk of hospital admission (within 14 days following a positive SARS-CoV-2 test) or death (within 28 days) in residents who had tested positive for SARS-CoV-2 in the period shortly before omicron emerged (delta-dominant) and in the omicron-dominant period, adjusting for age, sex, primary vaccine course, past infection, and booster vaccination. Variants were confirmed by sequencing or spike-gene status in a subset of samples. Results: 795 233 tests were done in 333 long-term care facilities, of which 159 084 (20·0%) could not be linked to a pseudo-identifier and 138 012 (17·4%) were done in residents. Eight residents had two episodes of infection (>28 days apart) and in these cases the second episode was excluded from the analysis. 2264 residents in 259 long-term care facilities (median age 84·5 years, IQR 77·9-90·0) were diagnosed with SARS-CoV-2, of whom 253 (11·2%) had a previous infection and 1468 (64·8%) had received a booster vaccination. About a third of participants were male. Risk of hospital admissions was markedly lower in the 1864 residents infected in the omicron-period (4·51%, 95% CI 3·65-5·55) than in the 400 residents infected in the pre-omicron period (10·50%, 7·87-13·94), as was risk of death (5·48% [4·52-6·64] vs 10·75% [8·09-14·22]). Adjusted hazard ratios (aHR) also indicated a reduction in hospital admissions (0·64, 95% CI 0·41-1·00; p=0·051) and mortality (aHR 0·68, 0·44-1·04; p=0·076) in the omicron versus the pre-omicron period. Findings were similar in residents with a confirmed variant. Interpretation: Observed reduced severity of the omicron variant compared with previous variants suggests that the wave of omicron infections is unlikely to lead to a major surge in severe disease in long-term care facility populations with high levels of vaccine coverage or natural immunity. Continued surveillance in this vulnerable population is important to protect residents from infection and monitor the public health effect of emerging variants. Funding: UK Department of Health and Social Care.


Subject(s)
COVID-19 , SARS-CoV-2 , Aged, 80 and over , Cohort Studies , Female , Humans , Long-Term Care , Male , Prospective Studies , State Medicine
5.
Eur J Epidemiol ; 37(3): 227-234, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1782861

ABSTRACT

This essay considers the factors that have contributed to very high COVID-19 mortality in longer-term care facilities (LTCFs). We compare the demographic characteristics of LTCF residents with those of community-dwelling older adults, and then we review the evidence regarding prevalence and infection fatality rates (IFRs), including links to frailty and some comorbidities. Finally, we discuss policy measures that could foster the physical and mental health and well-being of LTCF residents in the present context and in potential future pandemics.


Subject(s)
COVID-19 , Aged , Humans , Long-Term Care , Pandemics , Prevalence , SARS-CoV-2
6.
Lancet Healthy Longev ; 3(1): e13-e21, 2022 01.
Article in English | MEDLINE | ID: covidwho-1665611

ABSTRACT

BACKGROUND: Long-term care facilities (LTCFs) have reported high SARS-CoV-2 infection rates and related mortality, but the proportion of infected people among those who have survived, and duration of the antibody response to natural infection, is unknown. We determined the prevalence and stability of nucleocapsid antibodies (the standard assay for detection of previous infection) in staff and residents in LTCFs in England. METHODS: This was a prospective cohort study of residents 65 years or older and of staff 65 years or younger in 201 LTCFs in England between March 1, 2020, and May 7, 2021. Participants were linked to a unique pseudo-identifier based on their UK National Health Service identification number. Serial blood samples were tested for IgG antibodies against SARS-CoV-2 nucleocapsid protein using the Abbott ARCHITECT i-system (Abbott, Maidenhead, UK) immunoassay. Primary endpoints were prevalence and cumulative incidence of antibody positivity, which were weighted to the LTCF population. Incidence rate of loss of antibodies (seroreversion) was estimated from Kaplan-Meier curves. FINDINGS: 9488 samples were included, 8636 (91·0%) of which could be individually linked to 1434 residents and 3288 staff members. The cumulative incidence of nucleocapsid seropositivity was 34·6% (29·6-40·0) in residents and 26·1% (23·0-29·5) in staff over 11 months. 239 (38·6%) residents and 503 women (81·3%) were included in the antibody-waning analysis, and median follow-up was 149 days (IQR 107-169). The incidence rate of seroreversion was 2·1 per 1000 person-days at risk, and median time to reversion was 242·5 days. INTERPRETATION: At least a quarter of staff and a third of surviving residents were infected with SAR-CoV-2 during the first two waves of the pandemic in England. Nucleocapsid-specific antibodies often become undetectable within the first year following infection, which is likely to lead to marked underestimation of the true proportion of people with previous infection. Given that natural infection might act to boost vaccine responses, better assays to identify natural infection should be developed. FUNDING: UK Government Department of Health and Social Care.


Subject(s)
COVID-19 , Pandemics , Antibodies, Viral , Female , Humans , Long-Term Care , Nucleocapsid , Prevalence , Prospective Studies , SARS-CoV-2 , State Medicine
7.
Lancet Infect Dis ; 21(11): 1529-1538, 2021 11.
Article in English | MEDLINE | ID: covidwho-1637724

ABSTRACT

BACKGROUND: The effectiveness of SARS-CoV-2 vaccines in older adults living in long-term care facilities is uncertain. We investigated the protective effect of the first dose of the Oxford-AstraZeneca non-replicating viral-vectored vaccine (ChAdOx1 nCoV-19; AZD1222) and the Pfizer-BioNTech mRNA-based vaccine (BNT162b2) in residents of long-term care facilities in terms of PCR-confirmed SARS-CoV-2 infection over time since vaccination. METHODS: The VIVALDI study is a prospective cohort study that commenced recruitment on June 11, 2020, to investigate SARS-CoV-2 transmission, infection outcomes, and immunity in residents and staff in long-term care facilities in England that provide residential or nursing care for adults aged 65 years and older. In this cohort study, we included long-term care facility residents undergoing routine asymptomatic SARS-CoV-2 testing between Dec 8, 2020 (the date the vaccine was first deployed in a long-term care facility), and March 15, 2021, using national testing data linked within the COVID-19 Datastore. Using Cox proportional hazards regression, we estimated the relative hazard of PCR-positive infection at 0-6 days, 7-13 days, 14-20 days, 21-27 days, 28-34 days, 35-48 days, and 49 days and beyond after vaccination, comparing unvaccinated and vaccinated person-time from the same cohort of residents, adjusting for age, sex, previous infection, local SARS-CoV-2 incidence, long-term care facility bed capacity, and clustering by long-term care facility. We also compared mean PCR cycle threshold (Ct) values for positive swabs obtained before and after vaccination. The study is registered with ISRCTN, number 14447421. FINDINGS: 10 412 care home residents aged 65 years and older from 310 LTCFs were included in this analysis. The median participant age was 86 years (IQR 80-91), 7247 (69·6%) of 10 412 residents were female, and 1155 residents (11·1%) had evidence of previous SARS-CoV-2 infection. 9160 (88·0%) residents received at least one vaccine dose, of whom 6138 (67·0%) received ChAdOx1 and 3022 (33·0%) received BNT162b2. Between Dec 8, 2020, and March 15, 2021, there were 36 352 PCR results in 670 628 person-days, and 1335 PCR-positive infections (713 in unvaccinated residents and 612 in vaccinated residents) were included. Adjusted hazard ratios (HRs) for PCR-positive infection relative to unvaccinated residents declined from 28 days after the first vaccine dose to 0·44 (95% CI 0·24-0·81) at 28-34 days and 0·38 (0·19-0·77) at 35-48 days. Similar effect sizes were seen for ChAdOx1 (adjusted HR 0·32, 95% CI 0·15-0·66) and BNT162b2 (0·35, 0·17-0·71) vaccines at 35-48 days. Mean PCR Ct values were higher for infections that occurred at least 28 days after vaccination than for those occurring before vaccination (31·3 [SD 8·7] in 107 PCR-positive tests vs 26·6 [6·6] in 552 PCR-positive tests; p<0·0001). INTERPRETATION: Single-dose vaccination with BNT162b2 and ChAdOx1 vaccines provides substantial protection against infection in older adults from 4-7 weeks after vaccination and might reduce SARS-CoV-2 transmission. However, the risk of infection is not eliminated, highlighting the ongoing need for non-pharmaceutical interventions to prevent transmission in long-term care facilities. FUNDING: UK Government Department of Health and Social Care.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/prevention & control , Immunogenicity, Vaccine , Nursing Homes/statistics & numerical data , Age Factors , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/virology , COVID-19 Nucleic Acid Testing/statistics & numerical data , COVID-19 Vaccines/administration & dosage , England/epidemiology , Female , Humans , Immunization Schedule , Incidence , Male , Mass Vaccination/methods , Mass Vaccination/statistics & numerical data , Prospective Studies , SARS-CoV-2/genetics , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Treatment Outcome
8.
Euro Surveill ; 26(46)2021 11.
Article in English | MEDLINE | ID: covidwho-1526748

ABSTRACT

We describe the impact of changing epidemiology and vaccine introduction on characteristics of COVID-19 outbreaks in 330 long-term care facilities (LTCF) in England between November 2020 and June 2021. As vaccine coverage in LTCF increased and national incidence declined, the total number of outbreaks and outbreak severity decreased across the LTCF. The number of infected cases per outbreak decreased by 80.6%, while the proportion of outbreaks affecting staff only increased. Our study supports findings of vaccine effectiveness in LTCF.


Subject(s)
COVID-19 , Vaccines , Disease Outbreaks/prevention & control , Humans , Long-Term Care , SARS-CoV-2
9.
Lancet Microbe ; 3(2): e151-e158, 2022 02.
Article in English | MEDLINE | ID: covidwho-1440435

ABSTRACT

We reviewed all genomic epidemiology studies on COVID-19 in long-term care facilities (LTCFs) that had been published to date. We found that staff and residents were usually infected with identical, or near identical, SARS-CoV-2 genomes. Outbreaks usually involved one predominant cluster, and the same lineages persisted in LTCFs despite infection control measures. Outbreaks were most commonly due to single or few introductions followed by a spread rather than a series of seeding events from the community into LTCFs. The sequencing of samples taken consecutively from the same individuals at the same facilities showed the persistence of the same genome sequence, indicating that the sequencing technique was robust over time. When combined with local epidemiology, genomics allowed probable transmission sources to be better characterised. The transmission between LTCFs was detected in multiple studies. The mortality rate among residents was high in all facilities, regardless of the lineage. Bioinformatics methods were inadequate in a third of the studies reviewed, and reproducing the analyses was difficult because sequencing data were not available in many facilities.


Subject(s)
COVID-19 , COVID-19/epidemiology , Disease Outbreaks , Genomics , Humans , Long-Term Care , SARS-CoV-2/genetics
10.
Lancet Healthy Longev ; 2(9): e544-e553, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1433991

ABSTRACT

BACKGROUND: Residents of long-term care facilities (LTCFs) have been prioritised for COVID-19 vaccination because of the high COVID-19 mortality in this population. Several countries have implemented an extended interval of up to 12 weeks between the first and second vaccine doses to increase population coverage of single-dose vaccination. We aimed to assess the magnitude and quality of adaptive immune responses following a single dose of COVID-19 vaccine in LTCF residents and staff. METHODS: From the LTCFs participating in the ongoing VIVALDI study (ISRCTN14447421), staff and residents who had received a first dose of COVID-19 vaccine (BNT162b2 [tozinameran] or ChAdOx1 nCoV-19), had pre-vaccination and post-vaccination blood samples (collected between Dec 11, 2020, and Feb 16, 2021), and could be linked to a pseudoidentifier in the COVID-19 Data Store were included in our cohort. Past infection with SARS-CoV-2 was defined on the basis of nucleocapsid-specific IgG antibodies being detected through a semiquantitative immunoassay, and participants who tested positive on this assay after but not before vaccination were excluded from the study. Processed blood samples were assessed for spike-specific immune responses, including spike-specific IgG antibody titres, T-cell responses to spike protein peptide mixes, and inhibition of ACE2 binding by spike protein from four variants of SARS-CoV-2 (the original strain as well as the B.1.1.7, B.1.351, and P.1 variants). Responses before and after vaccination were compared on the basis of age, previous infection status, role (staff or resident), and time since vaccination. FINDINGS: Our cohort comprised 124 participants from 14 LTCFs: 89 (72%) staff (median age 48 years [IQR 35·5-56]) and 35 (28%) residents (87 years [77-90]). Blood samples were collected a median 40 days (IQR 25-47; range 6-52) after vaccination. 30 (24%) participants (18 [20%] staff and 12 [34%] residents) had serological evidence of previous SARS-CoV-2 infection. All participants with previous infection had high antibody titres following vaccination that were independent of age (r s=0·076, p=0·70). In participants without evidence of previous infection, titres were negatively correlated with age (r s=-0·434, p<0·0001) and were 8·2-times lower in residents than in staff. This effect appeared to result from a kinetic delay antibody generation in older infection-naive participants, with the negative age correlation disappearing only in samples taken more than 42 days post-vaccination (r s=-0·207, p=0·20; n=40), in contrast to samples taken after 0-21 days (r s=-0·774, p=0·0043; n=12) or 22-42 days (r s=-0·437, p=0·0034; n=43). Spike-specific cellular responses were similar between older and younger participants. In infection-naive participants, antibody inhibition of ACE2 binding by spike protein from the original SARS-CoV-2 strain was negatively correlated with age (r s=-0·439, p<0·0001), and was significantly lower against spike protein from the B.1.351 variant (median inhibition 31% [14-100], p=0·010) and the P.1 variant (23% [14-97], p<0·0001) than against the original strain (58% [27-100]). By contrast, a single dose of vaccine resulted in around 100% inhibition of the spike-ACE2 interaction against all variants in people with a history of infection. INTERPRETATION: History of SARS-CoV-2 infection impacts the magnitude and quality of antibody response after a single dose of COVID-19 vaccine in LTCF residents. Residents who are infection-naive have delayed antibody responses to the first dose of vaccine and should be considered for an early second dose where possible. FUNDING: UK Government Department of Health and Social Care.

11.
Lancet Microbe ; 2(11): e594-e603, 2021 11.
Article in English | MEDLINE | ID: covidwho-1356520

ABSTRACT

BACKGROUND: Emergency admissions for infection often lack initial diagnostic certainty. COVID-19 has highlighted a need for novel diagnostic approaches to indicate likelihood of viral infection in a pandemic setting. We aimed to derive and validate a blood transcriptional signature to detect viral infections, including COVID-19, among adults with suspected infection who presented to the emergency department. METHODS: Individuals (aged ≥18 years) presenting with suspected infection to an emergency department at a major teaching hospital in the UK were prospectively recruited as part of the Bioresource in Adult Infectious Diseases (BioAID) discovery cohort. Whole-blood RNA sequencing was done on samples from participants with subsequently confirmed viral, bacterial, or no infection diagnoses. Differentially expressed host genes that met additional filtering criteria were subjected to feature selection to derive the most parsimonious discriminating signature. We validated the signature via RT-qPCR in a prospective validation cohort of participants who presented to an emergency department with undifferentiated fever, and a second case-control validation cohort of emergency department participants with PCR-positive COVID-19 or bacterial infection. We assessed signature performance by calculating the area under receiver operating characteristic curves (AUROCs), sensitivities, and specificities. FINDINGS: A three-gene transcript signature, comprising HERC6, IGF1R, and NAGK, was derived from the discovery cohort of 56 participants with bacterial infections and 27 with viral infections. In the validation cohort of 200 participants, the signature differentiated bacterial from viral infections with an AUROC of 0·976 (95% CI 0·919-1·000), sensitivity of 97·3% (85·8-99·9), and specificity of 100% (63·1-100). The AUROC for C-reactive protein (CRP) was 0·833 (0·694-0·944) and for leukocyte count was 0·938 (0·840-0·986). The signature achieved higher net benefit in decision curve analysis than either CRP or leukocyte count for discriminating viral infections from all other infections. In the second validation analysis, which included SARS-CoV-2-positive participants, the signature discriminated 35 bacterial infections from 34 SARS-CoV-2-positive COVID-19 infections with AUROC of 0·953 (0·893-0·992), sensitivity 88·6%, and specificity of 94·1%. INTERPRETATION: This novel three-gene signature discriminates viral infections, including COVID-19, from other emergency infection presentations in adults, outperforming both leukocyte count and CRP, thus potentially providing substantial clinical utility in managing acute presentations with infection. FUNDING: National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7.


Subject(s)
Bacterial Infections , COVID-19 , Communicable Diseases , Virus Diseases , Adolescent , Adult , Bacteria , Bacterial Infections/diagnosis , C-Reactive Protein/analysis , COVID-19/diagnosis , Case-Control Studies , Cohort Studies , Humans , SARS-CoV-2/genetics , Virus Diseases/diagnosis
12.
Lancet Healthy Longev ; 2(3): e129-e142, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1284651

ABSTRACT

BACKGROUND: Outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have occurred in long-term care facilities (LTCFs) worldwide, but the reasons why some facilities are particularly vulnerable to outbreaks are poorly understood. We aimed to identify factors associated with SARS-CoV-2 infection and outbreaks among staff and residents in LTCFs. METHODS: We did a national cross-sectional survey of all LTCFs providing dementia care or care to adults aged 65 years or older in England between May 26 and June 19, 2020. The survey collected data from managers of eligible LTCFs on LTCF characteristics, staffing factors, the use of disease control measures, and the number of confirmed cases of infection among staff and residents in each LTCF. Survey responses were linked to individual-level SARS-CoV-2 RT-PCR test results obtained through the national testing programme in England between April 30 and June 13, 2020. The primary outcome was the weighted period prevalence of confirmed SARS-CoV-2 infections in residents and staff reported via the survey. Multivariable logistic regression models were fitted to identify factors associated with infection in staff and residents, an outbreak (defined as at least one case of SARS-CoV-2 infection in a resident or staff member), and a large outbreak (defined as LTCFs with more than a third of the total number of residents and staff combined testing positive, or with >20 residents and staff combined testing positive) using data from the survey and from the linked survey-test dataset. FINDINGS: 9081 eligible wLTCFs were identified, of which 5126 (56·4%) participated in the survey, providing data on 160 033 residents and 248 594 staff members. The weighted period prevalence of infection was 10·5% (95% CI 9·9-11·1) in residents and 3·8% (3·4-4·2) in staff members. 2724 (53·1%) LTCFs reported outbreaks, and 469 (9·1%) LTCFs reported large outbreaks. The odds of SARS-CoV-2 infection in residents (adjusted odds ratio [aOR] 0·80 [95% CI 0·75-0·86], p<0·0001) and staff (0·70 [0·65-0·77], p<0·0001), and of large outbreaks (0·59 [0·38-0·93], p=0·024) were significantly lower in LTCFs that paid staff statutory sick pay compared with those that did not. Each one unit increase in the staff-to-bed ratio was associated with a reduced odds of infection in residents (0·82 [0·78-0·87], p<0·0001) and staff (0·63 [0·59-0·68], p<0·0001. The odds of infection in residents (1·30 [1·23-1·37], p<0·0001) and staff (1·20 [1·13-1·29], p<0·0001), and of outbreaks (2·56 [1·94-3·49], p<0·0001) were significantly higher in LTCFs in which staff often or always cared for both infected or uninfected residents compared with those that cohorted staff with either infected or uninfected residents. Significantly increased odds of infection in residents (1·01 [1·01-1·01], p<0·0001) and staff (1·00 [1·00-1·01], p=0·0005), and of outbreaks (1·08 [1·05-1·10], p<0·0001) were associated with each one unit increase in the number of new admissions to the LTCF relative to baseline (March 1, 2020). The odds of infection in residents (1·19 [1·12-1·26], p<0·0001) and staff (1·19 [1·10-1·29], p<0·0001), and of large outbreaks (1·65 [1·07-2·54], p=0·024) were significantly higher in LTCFs that were for profit versus those that were not for profit. Frequent employment of agency nurses or carers was associated with a significantly increased odds of infection in residents (aOR 1·65 [1·56-1·74], p<0·0001) and staff (1·85 [1·72-1·98], p<0·0001), and of outbreaks (2·33 [1·72-3·16], p<0·0001) and large outbreaks (2·42 [1·67-3·51], p<0·0001) compared with no employment of agency nurses or carers. Compared with LTCFs that did not report difficulties in isolating residents, those that did had significantly higher odds of infection in residents (1·33 [1·28-1·38], p<0·0001) and staff (1·48 [1·41-1·56], p<0·0001), and of outbreaks (1·84 [1·48-2·30], p<0·0001) and large outbreaks (1·62 [1·24-2·11], p=0·0004). INTERPRETATION: Half of LTCFs had no cases of SARS-CoV-2 infection in the first wave of the pandemic. Reduced transmission from staff is associated with adequate sick pay, minimal use of agency staff, an increased staff-to-bed ratio, and staff cohorting with either infected or uninfected residents. Increased transmission from residents is associated with an increased number of new admissions to the facility and poor compliance with isolation procedures. FUNDING: UK Government Department of Health and Social Care.

14.
Age Ageing ; 50(4): 1019-1028, 2021 06 28.
Article in English | MEDLINE | ID: covidwho-1132418

ABSTRACT

BACKGROUND: epidemiological data on COVID-19 infection in care homes are scarce. We analysed data from a large provider of long-term care for older people to investigate infection and mortality during the first wave of the pandemic. METHODS: cohort study of 179 UK care homes with 9,339 residents and 11,604 staff. We used manager-reported daily tallies to estimate the incidence of suspected and confirmed infection and mortality in staff and residents. Individual-level electronic health records from 8,713 residents were used to model risk factors for confirmed infection, mortality and estimate attributable mortality. RESULTS: 2,075/9,339 residents developed COVID-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory-confirmed infections. The incidence of confirmed infection was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days in residents and staff, respectively. Sixty-eight percent (121/179) of care homes had at least one COVID-19 infection or COVID-19-related death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection.Out of 607 residents with confirmed infection, 217 died (case fatality rate: 35.7% [31.9%; 39.7%]). Mortality in residents with no direct evidence of infection was twofold higher in care homes with outbreaks versus those without (adjusted hazard ratio: 2.2 [1.8; 2.6]). CONCLUSIONS: findings suggest many deaths occurred in people who were infected with COVID-19, but not tested. Higher occupancy and lower staffing levels were independently associated with risks of infection. Protecting staff and residents from infection requires regular testing for COVID-19 and fundamental changes to staffing and care home occupancy.


Subject(s)
COVID-19 , Aged , COVID-19 Testing , Cohort Studies , Electronics , Humans , Nursing Homes , SARS-CoV-2 , United Kingdom/epidemiology , Watchful Waiting
15.
Wellcome Open Res ; 5: 225, 2020.
Article in English | MEDLINE | ID: covidwho-1106516

ABSTRACT

Background: Diagnostic testing forms a major part of the UK's response to the current coronavirus disease 2019 (COVID-19) pandemic with tests offered to anyone with a continuous cough, high temperature or anosmia. Testing capacity must be sufficient during the winter respiratory season when levels of cough and fever are high due to non-COVID-19 causes. This study aims to make predictions about the contribution of baseline cough or fever to future testing demand in the UK. Methods: In this analysis of the Bug Watch prospective community cohort study, we estimated the incidence of cough or fever in England in 2018-2019. We then estimated the COVID-19 diagnostic testing rates required in the UK for baseline cough or fever cases for the period July 2020-June 2021. This was explored for different rates of the population requesting tests and four COVID-19 second wave scenarios. Estimates were then compared to current national capacity. Results: The baseline incidence of cough or fever in the UK is expected to rise rapidly from 154,554 (95%CI 103,083 - 231,725) cases per day in August 2020 to 250,708 (95%CI 181,095 - 347,080) in September, peaking at 444,660 (95%CI 353,084 - 559,988) in December. If 80% of baseline cough or fever cases request tests, average daily UK testing demand would exceed current capacity for five consecutive months (October 2020 to February 2021), with a peak demand of 147,240 (95%CI 73,978 - 239,502) tests per day above capacity in December 2020. Conclusions: Our results show that current national COVID-19 testing capacity is likely to be exceeded by demand due to baseline cough and fever alone. This study highlights that the UK's response to the COVID-19 pandemic must ensure that a high proportion of people with symptoms request tests, and that testing capacity is immediately scaled up to meet this high predicted demand.

16.
Wellcome Open Research ; 2020.
Article in English | ProQuest Central | ID: covidwho-916554

ABSTRACT

Background: Cross-sectional studies indicate that up to 80% of active SARS-CoV-2 infections may be asymptomatic. However, accurate estimates of the asymptomatic proportion require systematic detection and follow-up to differentiate between truly asymptomatic and pre-symptomatic cases. We conducted a rapid review and meta-analysis of the asymptomatic proportion of PCR-confirmed SARS-CoV-2 infections based on methodologically appropriate studies in community settings. Methods: We searched Medline and EMBASE for peer-reviewed articles, and BioRxiv and MedRxiv for pre-prints published before 25/08/2020. We included studies based in community settings that involved systematic PCR testing on participants and follow-up symptom monitoring regardless of symptom status. We extracted data on study characteristics, frequencies of PCR-confirmed infections by symptom status, and (if available) cycle threshold/genome copy number values and/or duration of viral shedding by symptom status, and age of asymptomatic versus (pre)symptomatic cases. We computed estimates of the asymptomatic proportion and 95% confidence intervals for each study and overall using random effect meta-analysis. Results: We screened 1138 studies and included 21. The pooled asymptomatic proportion of SARS-CoV-2 infections was 23% (95% CI 16%-30%). When stratified by testing context, the asymptomatic proportion ranged from 6% (95% CI 0-17%) for household contacts to 47% (95% CI 21-75%) for non-outbreak point prevalence surveys with follow-up symptom monitoring. Estimates of viral load and duration of viral shedding appeared to be similar for asymptomatic and symptomatic cases based on available data, though detailed reporting of viral load and natural history of viral shedding by symptom status were limited. Evidence into the relationship between age and symptom status was inconclusive. Conclusion: Asymptomatic viral shedding comprises a substantial minority of SARS-CoV-2 infections when estimated using methodologically appropriate studies. Further investigation into variation in the asymptomatic proportion by testing context, the degree and duration of infectiousness for asymptomatic infections, and demographic predictors of symptom status are warranted.

17.
Lancet ; 395(10238): 1715-1725, 2020 05 30.
Article in English | MEDLINE | ID: covidwho-245277

ABSTRACT

BACKGROUND: The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. METHODS: In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. FINDINGS: We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41-4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. INTERPRETATION: We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. FUNDING: National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.


Subject(s)
Coronavirus Infections/epidemiology , Mortality/trends , Pneumonia, Viral/epidemiology , Adult , Aged , Aged, 80 and over , COVID-19 , Cohort Studies , Coronavirus Infections/complications , Female , Humans , Male , Middle Aged , Models, Statistical , Multimorbidity , Pandemics , Pneumonia, Viral/complications , Risk Factors , United Kingdom/epidemiology
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