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1.
Lancet Healthy Longev ; 3(1): e13-e21, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1586149

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.

2.
Preprint in English | EuropePMC | ID: ppcovidwho-295420

ABSTRACT

Background: This modeling study aims to measure the impact COVID-19-related tuberculosis (TB) service disruptions had on key TB outcomes in Indonesia, Kyrgyzstan, Malawi, Mozambique, and Peru, and the mitigation of that impact through catch-up strategies in each country.<br><br>Methods: Quarterly epidemiological estimates and programmatic TB data capturing disruption levels to each TB service were collected by National TB Programmes (NTPs) in 2019, for a pre-COVID-19 baseline, and throughout 2020. These data, together with the NTP’s COVID-19 response plans, were used within Optima TB models to project TB incidence and deaths over five years.<br><br>Findings: Countries reported disruptions of up to 64% to passive TB case finding. TB treatment experienced lower levels of disruption of up to 21%. We predicted that under the worse-case scenario new latent TB infections, new active TB infections, and TB-related deaths could increase by up to 23%, 11%, and 20%, respectively, by 2024. However, three of the five countries were on track to mitigate these increases to 3% or less by maintaining TB services in 2021 and 2022 and by implementing proposed catch-up strategies thereafter. Indonesia was already experiencing the worse-case scenario, which could lead to 270,000 additional active TB infections and 36,000 additional TB-related deaths by the end of 2024.<br><br>Interpretation: The COVID-19 pandemic is projected to negatively affect progress towards 2035 End TB targets, especially in countries already off-track. Findings highlight the need to proactively maintain TB service availability under a range of scenarios, including potential new waves of COVID-19 caused by more transmissible variants.<br><br>Funding Information: UNAIDS<br><br>Declaration of Interests: None to declare.

3.
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
4.
Lancet Infect Dis ; 21(11): 1529-1538, 2021 11.
Article in English | MEDLINE | ID: covidwho-1281643

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
5.
BMJ Open ; 11(5): e050131, 2021 05 24.
Article in English | MEDLINE | ID: covidwho-1242208

ABSTRACT

OBJECTIVES: To investigate how the COVID-19 pandemic affected the number of people aged 50+ years presenting to primary care with features that could potentially indicate cancer, and to explore how reporting differed by patient characteristics and in face-to-face vs remote consultations. DESIGN, SETTING AND PARTICIPANTS: A retrospective cohort study of general practitioner (GP), nurse and paramedic primary care consultations in 21 practices in South-West England covering 123 947 patients. The models compared potential cancer indicators reported in April-July 2019 with April-July 2020. MAIN OUTCOME MEASURES: Potential indicators of cancer were identified using code lists for symptoms, signs, test results and diagnoses listed in the National Institute for Health and Care Excellence suspected cancer referral guidance (NG12). RESULTS: During April-July 2019, 17% of registered patients aged 50+ years reported a potential cancer indicator in a consultation with a GP or nurse. During April-July 2020, this reduced to 11% (incidence rate ratio (IRR) 0.64, 95% CI 0.62 to 0.67, p<0.001). Reductions in potential cancer indicators were stable across age group, sex, ethnicity, index of multiple deprivation quintile and shielding status, but less marked in patients with mental health conditions than without (IRR 0.75, 95% CI 0.72 to 0.79, interaction p<0.001). Proportions of GP consultations with potential indicators of cancer reduced between 2019 and 2020 for face-to-face consultations (IRR 0.84, 95% CI 0.76 to 0.92, p<0.001) and increased for remote consultations (IRR 1.17, 95% CI 1.07 to 1.29, p=0.001), although it remained lower in remote consulting than face-to-face in April-July 2020. This difference was greater for nurse/paramedic consultations (face-to-face: IRR 0.61, 95% CI 0.44 to 0.83, p=0.002; remote: IRR 1.60, 95% CI 1.10 to 2.333, p=0.014). CONCLUSION: The number of patients consulting with presentations that could potentially indicate cancer reduced during the first wave of the COVID-19 pandemic. Patients should be encouraged to continue contacting primary care for persistent signs and symptoms, and GPs and nurses should be encouraged to probe patients for further information during remote consulting, in the absence of non-verbal cues.


Subject(s)
COVID-19 , Neoplasms , England/epidemiology , Humans , Middle Aged , Neoplasms/epidemiology , Pandemics , Primary Health Care , Retrospective Studies , SARS-CoV-2
6.
Nat Commun ; 11(1): 5749, 2020 11 12.
Article in English | MEDLINE | ID: covidwho-922259

ABSTRACT

Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/pathology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/pathology , Betacoronavirus , Bias , COVID-19 , Humans , Observational Studies as Topic , Pandemics , Risk Factors , SARS-CoV-2 , Treatment Outcome
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