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1.
Lancet Respir Med ; 9(4): 397-406, 2021 04.
Article in English | MEDLINE | ID: covidwho-1180129

ABSTRACT

BACKGROUND: Analysis of the effect of COVID-19 on the complete hospital population in England has been lacking. Our aim was to provide a comprehensive account of all hospitalised patients with COVID-19 in England during the early phase of the pandemic and to identify the factors that influenced mortality as the pandemic evolved. METHODS: This was a retrospective exploratory analysis using the Hospital Episode Statistics administrative dataset. All patients aged 18 years or older in England who completed a hospital stay (were discharged alive or died) between March 1 and May 31, 2020, and had a diagnosis of COVID-19 on admission or during their stay were included. In-hospital death was the primary outcome of interest. Multilevel logistic regression was used to model the relationship between death and several covariates: age, sex, deprivation (Index of Multiple Deprivation), ethnicity, frailty (Hospital Frailty Risk Score), presence of comorbidities (Charlson Comorbidity Index items), and date of discharge (whether alive or deceased). FINDINGS: 91 541 adult patients with COVID-19 were discharged during the study period, among which 28 200 (30·8%) in-hospital deaths occurred. The final multilevel logistic regression model accounted for age, deprivation score, and date of discharge as continuous variables, and sex, ethnicity, and Charlson Comorbidity Index items as categorical variables. In this model, significant predictors of in-hospital death included older age (modelled using restricted cubic splines), male sex (1·457 [1·408-1·509]), greater deprivation (1·002 [1·001-1·003]), Asian (1·211 [1·128-1·299]) or mixed ethnicity (1·317 [1·080-1·605]; vs White ethnicity), and most of the assessed comorbidities, including moderate or severe liver disease (5·433 [4·618-6·392]). Later date of discharge was associated with a lower odds of death (0·977 [0·976-0·978]); adjusted in-hospital mortality improved significantly in a broadly linear fashion, from 52·2% in the first week of March to 16·8% in the last week of May. INTERPRETATION: Reductions in the adjusted probability of in-hospital mortality for COVID-19 patients over time might reflect the impact of changes in hospital strategy and clinical processes. The reasons for the observed improvements in mortality should be thoroughly investigated to inform the response to future outbreaks. The higher mortality rate reported for certain ethnic minority groups in community-based studies compared with our hospital-based analysis might partly reflect differential infection rates in those at greatest risk, propensity to become severely ill once infected, and health-seeking behaviours. FUNDING: None.


Subject(s)
/mortality , Hospital Mortality/trends , Minority Groups/statistics & numerical data , Pandemics/statistics & numerical data , Patient Acceptance of Health Care/statistics & numerical data , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Comorbidity , Datasets as Topic , Electronic Health Records/statistics & numerical data , England/epidemiology , Female , Humans , Length of Stay/statistics & numerical data , Male , Middle Aged , Retrospective Studies , Risk Factors , Severity of Illness Index , Sex Factors , Young Adult
2.
Rev Infirm ; 70(270): 47-48, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1174483

ABSTRACT

Catherine is an advanced nurse practitioner working in a large general practice in the North of England. Today she is running a travel clinic. Because of the immense changes brought about by COVID-19 the world is struggling to regain a degree of normality and the possibility of travel to distant places is liberating to many. More than ever medical advice about safety precautions are necessary. Marc and Emma are consulting Catherine about a projected holiday abroad.


Subject(s)
Practice Patterns, Nurses' , Travel Medicine , Advanced Practice Nursing , /nursing , England/epidemiology , General Practice , Humans
3.
Vet Rec ; 188(7): 242-243, 2021 04.
Article in English | MEDLINE | ID: covidwho-1173864
4.
BMJ Open ; 11(4): e045286, 2021 04 07.
Article in English | MEDLINE | ID: covidwho-1172759

ABSTRACT

INTRODUCTION: Recent evidence suggests that ethnic minority groups are disproportionately at increased risk of hospitalisation and death from SARS-CoV-2 infection. Population-based evidence on potential explanatory factors across minority groups and within subgroups is lacking. This study aims to quantify the association between ethnicity and the risk of hospitalisation and mortality due to COVID-19. METHODS AND ANALYSIS: This is a retrospective cohort study of adults registered across a representative and anonymised national primary care database (QResearch) that includes data on 10 million people in England. Sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared across ethnic subgroups (categorised as per 2011 census). Cox models will be used to calculate HR for hospitalisation and COVID-19 mortality associated with ethnic group. Potential confounding and explanatory factors (such as demographic, socioeconomic and clinical) will be adjusted for within regression models. The percentage contribution of distinct risk factor classes to the excess risks seen in ethnic groups/subgroups will be calculated. ETHICS AND DISSEMINATION: The study has undergone ethics review in accordance with the QResearch agreement (reference OX102). Findings will be disseminated through peer-reviewed manuscripts, presentations at scientific meetings and conferences with national and international stakeholders.


Subject(s)
/ethnology , Ethnic Groups , Adult , England/epidemiology , Humans , Minority Groups , Retrospective Studies
5.
BMJ ; 372: n693, 2021 03 31.
Article in English | MEDLINE | ID: covidwho-1166413

ABSTRACT

OBJECTIVE: To quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population. DESIGN: Retrospective cohort study. SETTING: NHS hospitals in England. PARTICIPANTS: 47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records. MAIN OUTCOME MEASURES: Rates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity. RESULTS: Over a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (P<0.001), diabetes (P<0.001), and cardiovascular disease (P<0.001) were also significantly raised in patients with covid-19, with 770 (95% confidence interval 758 to 783), 127 (122 to 132), and 126 (121 to 131) diagnoses per 1000 person years, respectively. Rate ratios were greater for individuals aged less than 70 than for those aged 70 or older, and in ethnic minority groups compared with the white population, with the largest differences seen for respiratory disease (10.5 (95% confidence interval 9.7 to 11.4) for age less than 70 years v 4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-white v 5.2 (5.0 to 5.5) for white individuals). CONCLUSIONS: Individuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.


Subject(s)
/complications , Hospitalization/statistics & numerical data , Multiple Organ Failure/epidemiology , Patient Readmission/statistics & numerical data , Adult , Aged , /mortality , Cardiovascular Diseases/epidemiology , Case-Control Studies , Diabetes Mellitus/epidemiology , England/epidemiology , Ethnic Groups , Female , Humans , Male , Middle Aged , Patient Discharge/statistics & numerical data , Respiratory Tract Diseases/epidemiology , Retrospective Studies , Risk Factors , /isolation & purification
6.
Sci Rep ; 11(1): 7106, 2021 03 29.
Article in English | MEDLINE | ID: covidwho-1157914

ABSTRACT

The National Health Service (NHS) Pathways triage system collates data on enquiries to 111 and 999 services in England. Since the 18th of March 2020, these data have been made publically available for potential COVID-19 symptoms self-reported by members of the public. Trends in such reports over time are likely to reflect behaviour of the ongoing epidemic within the wider community, potentially capturing valuable information across a broader severity profile of cases than hospital admission data. We present a fully reproducible analysis of temporal trends in NHS Pathways reports until 14th May 2020, nationally and regionally, and demonstrate that rates of growth/decline and effective reproduction number estimated from these data may be useful in monitoring transmission. This is a particularly pressing issue as lockdown restrictions begin to be lifted and evidence of disease resurgence must be constantly reassessed. We further assess the correlation between NHS Pathways reports and a publicly available NHS dataset of COVID-19-associated deaths in England, finding that enquiries to 111/999 were strongly associated with daily deaths reported 16 days later. Our results highlight the potential of NHS Pathways as the basis of an early warning system. However, this dataset relies on self-reported symptoms, which are at risk of being severely biased. Further detailed work is therefore necessary to investigate potential behavioural issues which might otherwise explain our conclusions.


Subject(s)
/epidemiology , /virology , England/epidemiology , Humans , State Medicine
7.
Nat Commun ; 12(1): 1942, 2021 03 29.
Article in English | MEDLINE | ID: covidwho-1157906

ABSTRACT

In early 2020 many countries closed schools to mitigate the spread of SARS-CoV-2. Since then, governments have sought to relax the closures, engendering a need to understand associated risks. Using address records, we construct a network of schools in England connected through pupils who share households. We evaluate the risk of transmission between schools under different reopening scenarios. We show that whilst reopening select year-groups causes low risk of large-scale transmission, reopening secondary schools could result in outbreaks affecting up to 2.5 million households if unmitigated, highlighting the importance of careful monitoring and within-school infection control to avoid further school closures or other restrictions.


Subject(s)
/transmission , Family Characteristics , Schools/organization & administration , Adolescent , /virology , Child , Child, Preschool , Disease Transmission, Infectious/prevention & control , England/epidemiology , Humans , Pandemics , Risk Assessment , Risk Factors , Schools/statistics & numerical data
8.
BMJ Open ; 11(3): e050223, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1146137

ABSTRACT

The COVID-19 pandemic has brought unprecedented challenges to the medical workforce. This has put them at increased risk of burnout at a time when levels are already worryingly high in the profession, with recent studies consistently showing that around half of doctors meet the validated criteria for burnout. OBJECTIVES: To understand the wider factors influencing and impacting upon hospital doctors' well-being during the COVID-19 pandemic in England. DESIGN: Cross-sectional survey and mixed quantitative-qualitative analysis. SETTING: Acute National Health Service (NHS) Foundation Trust in England. PARTICIPANTS: An online survey was circulated in early June 2020 to all 449 doctors employed by the Trust. 242 doctors completed the survey (54% response rate). PRIMARY OUTCOME MEASURES: Questions assessed occupational details, self-reported changes in physical and mental health, satisfaction with working hours and patterns, availability of personal protective equipment (PPE), medication and facilities, communication and sought to identify areas seen as having a significant effect on doctors' well-being. RESULTS: 96% of respondents requiring PPE were able to access it. Nearly half of the respondents felt that their mental health had deteriorated since the start of the pandemic. Over a third stated that their physical health had also declined. Issues identified as having a negative impact on doctors included increased workload, redeployment, loss of autonomy, personal issues affecting family members, anxiety around recovery plans, inadequate access to changing and storage facilities and to rest areas that allow for social distancing. Doctors appreciated access to 'calm rooms' that were made available for staff, access to clinical psychology support, free drinks and free car parking on site. CONCLUSION: The emerging themes are suggestive of increased burnout risk among doctors during the COVID-19 pandemic and encompass factors well beyond shortage of PPE. Small organisational initiatives and the implementation of changes suggested by survey respondents can have a positive impact on doctors' well-being.


Subject(s)
Mental Health , Pandemics , Personal Protective Equipment , Physicians/psychology , Cross-Sectional Studies , England/epidemiology , Humans , State Medicine
9.
Epidemiol Infect ; 149: e73, 2021 03 08.
Article in English | MEDLINE | ID: covidwho-1145031

ABSTRACT

The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first 6 months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on 23 March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.In terms of controlling transmission, the most important practical application of our results is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.


Subject(s)
/diagnosis , Time Factors , /classification , England/epidemiology , Humans , Population Surveillance/methods , Risk Evaluation and Mitigation , Risk Factors , Spatio-Temporal Analysis , Urban Population/statistics & numerical data
10.
Euro Surveill ; 26(11)2021 03.
Article in English | MEDLINE | ID: covidwho-1143384

ABSTRACT

The SARS-CoV-2 B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (hazard ratio: 1.67; 95% confidence interval: 1.34-2.09; p < 0.0001). Absolute risk of death by 28 days increased with age and comorbidities. This VOC has potential to spread faster with higher mortality than the pandemic to date.


Subject(s)
/mortality , /pathogenicity , Age Factors , Comorbidity , England/epidemiology , Humans
11.
BMJ ; 372: n628, 2021 03 18.
Article in English | MEDLINE | ID: covidwho-1143026

ABSTRACT

OBJECTIVE: To investigate whether risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and outcomes of coronavirus disease 2019 (covid-19) differed between adults living with and without children during the first two waves of the UK pandemic. DESIGN: Population based cohort study, on behalf of NHS England. SETTING: Primary care data and pseudonymously linked hospital and intensive care admissions and death records from England, during wave 1 (1 February to 31 August 2020) and wave 2 (1 September to 18 December 2020). PARTICIPANTS: Two cohorts of adults (18 years and over) registered at a general practice on 1 February 2020 and 1 September 2020. MAIN OUTCOME MEASURES: Adjusted hazard ratios for SARS-CoV-2 infection, covid-19 related admission to hospital or intensive care, or death from covid-19, by presence of children in the household. RESULTS: Among 9 334 392adults aged 65 years and under, during wave 1, living with children was not associated with materially increased risks of recorded SARS-CoV-2 infection, covid-19 related hospital or intensive care admission, or death from covid-19. In wave 2, among adults aged 65 years and under, living with children of any age was associated with an increased risk of recorded SARS-CoV-2 infection (hazard ratio 1.06 (95% confidence interval 1.05 to 1.08) for living with children aged 0-11 years; 1.22 (1.20 to 1.24) for living with children aged 12-18 years) and covid-19 related hospital admission (1.18 (1.06 to 1.31) for living with children aged 0-11; 1.26 (1.12 to 1.40) for living with children aged 12-18). Living with children aged 0-11 was associated with reduced risk of death from both covid-19 and non-covid-19 causes in both waves; living with children of any age was also associated with lower risk of dying from non-covid-19 causes. For adults 65 years and under during wave 2, living with children aged 0-11 years was associated with an increased absolute risk of having SARS-CoV-2 infection recorded of 40-60 per 10 000 people, from 810 to between 850 and 870, and an increase in the number of hospital admissions of 1-5 per 10 000 people, from 160 to between 161 and 165. Living with children aged 12-18 years was associated with an increase of 160-190 per 10 000 in the number of SARS-CoV-2 infections and an increase of 2-6 per 10 000 in the number of hospital admissions. CONCLUSIONS: In contrast to wave 1, evidence existed of increased risk of reported SARS-CoV-2 infection and covid-19 outcomes among adults living with children during wave 2. However, this did not translate into a materially increased risk of covid-19 mortality, and absolute increases in risk were small.


Subject(s)
/epidemiology , Family Characteristics , Hospitalization/statistics & numerical data , Intensive Care Units/statistics & numerical data , Adolescent , Adult , Aged , /physiopathology , Child , Child, Preschool , Cohort Studies , England/epidemiology , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Proportional Hazards Models , Residence Characteristics , Severity of Illness Index , Young Adult
12.
BMJ Open ; 11(3): e045384, 2021 03 16.
Article in English | MEDLINE | ID: covidwho-1138355

ABSTRACT

OBJECTIVES: Since its emergence in late 2019, SARS-CoV-2 has caused a global pandemic that has significantly challenged healthcare systems. Healthcare workers have previously been shown to have experienced higher rates of infection than the general population. We aimed to assess the extent of infection in staff working in our healthcare setting. DESIGN: A retrospective analysis of antibody results, compared with staff demographic data, and exposure to patients with COVID-19 infection. SETTING: A large teaching hospital in the North West of England. PARTICIPANTS: 4474 staff in diverse clinical and non-patient facing roles who volunteered for SARS-CoV-2 antibody testing by the Roche Elecsys assay between 29 May and 4 July 2020. RESULTS: Seroprevalence was 17.4%. Higher rates were seen in Asian/Asian British (OR 1.61, 95% CI 1.27 to 2.04) and Black/Black British (OR 2.08, 95% CI 1.25 to 3.45) staff. Staff working in any clinical location were more likely to be seropositive (OR 2.68, 95% 2.27 to 3.15). Staff were at an increased risk of seropositivity as the 'per 100 COVID-19 bed-days change' increased in the clinical area in which they worked (OR 1.12, 95% 1.10 to 1.14). Staff working in critical care were no more likely to have detectable antibodies than staff working in non-clinical areas. Symptoms compatible with COVID-19 were reported in 41.8% and antibodies were detected in 30.7% of these individuals. In staff who reported no symptoms, antibodies were detected in 7.7%. In all staff who had detectable antibodies, 25.2% reported no symptoms. CONCLUSIONS: Staff working in clinical areas where patients with COVID-19 were nursed were more likely to have detectable antibodies. The relationship between seropositivity in healthcare workers and the increase in 'per 100 COVID-19 bed-days' of the area in which they worked, although statistically significant, was weak, suggesting other contributing factors to the risk profile. Of staff with detectable antibodies and therefore evidence of prior infection, a quarter self-reported that they had experienced no compatible symptoms. This has implications for potential unrecorded transmission in both staff and patients.


Subject(s)
/diagnosis , Health Personnel/statistics & numerical data , Seroepidemiologic Studies , /blood , England/epidemiology , Hospitals, Teaching , Humans , Prevalence , Retrospective Studies
13.
J Transl Med ; 19(1): 109, 2021 03 16.
Article in English | MEDLINE | ID: covidwho-1136231

ABSTRACT

BACKGROUND: No versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. The http://covid-webapp.numerusinc.com/ web app presented here fills this gap. METHODS: Our web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. RESULTS: We illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world's fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. CONCLUSION: Our web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration.


Subject(s)
/epidemiology , Infection Control , Internet , Mobile Applications , /etiology , Computer Simulation , Effect Modifier, Epidemiologic , England/epidemiology , Epidemics , Forecasting/methods , Humans , Infection Control/methods , Infection Control/organization & administration , Infection Control/standards , Israel/epidemiology , Markov Chains , Population Surveillance/methods , Risk Factors , South Africa/epidemiology
14.
Lancet Psychiatry ; 8(2): 141-149, 2021 02.
Article in English | MEDLINE | ID: covidwho-1127095

ABSTRACT

BACKGROUND: There is major concern about the impact of the global COVID-19 outbreak on mental health. Several studies suggest that mental health deteriorated in many countries before and during enforced isolation (ie, lockdown), but it remains unknown how mental health has changed week by week over the course of the COVID-19 pandemic. This study aimed to explore the trajectories of anxiety and depression over the 20 weeks after lockdown was announced in England, and compare the growth trajectories by individual characteristics. METHODS: In this prospective longitudinal observational study, we analysed data from the UCL COVID-19 Social Study, a panel study weighted to population proportions, which collects information on anxiety (using the Generalised Anxiety Disorder assessment) and depressive symptoms (using the Patient Health Questionnaire) weekly in the UK since March 21, 2020. We included data from adults living in England who had at least three repeated measures between March 23 and Aug 9, 2020. Analyses were done using latent growth models, which were fitted to account for sociodemographic and health covariates. FINDINGS: Between March 23, and Aug 9, data from over 70 000 adults were collected in the UCL COVID-19 Social Study. When including participants living in England with three follow-up measures and no missing values, our analytic sample consisted of 36 520 participants. The average depression score was 6·6 (SD=6·0, range 0-27) and the average anxiety score 5·7 (SD=5·6, range 0-21) in week 1. Anxiety and depression levels both declined across the first 20 weeks following the introduction of lockdown in England (b=-1·93, SE=0·26, p<0·0001 for anxiety; b=-2·52, SE=0·28, p<0·0001 for depressive symptoms). The fastest decreases were seen across the strict lockdown period (between weeks 2 and 5), with symptoms plateauing as further lockdown easing measures were introduced (between weeks 16 and 20). Being a woman or younger, having lower educational attainment, lower income, or pre-existing mental health conditions, and living alone or with children were all risk factors for higher levels of anxiety and depression at the start of lockdown. Many of these inequalities in experiences were reduced as lockdown continued, but differences were still evident 20 weeks after the start of lockdown. INTERPRETATION: These data suggest that the highest levels of depression and anxiety occurred in the early stages of lockdown but declined fairly rapidly, possibly because individuals adapted to circumstances. Our findings emphasise the importance of supporting individuals in the lead-up to future lockdowns to try to reduce distress, and highlight that groups already at risk for poor mental health before the pandemic have remained at risk throughout lockdown and its aftermath. FUNDING: Nuffield Foundation, UK Research and Innovation, Wellcome Trust.


Subject(s)
Adaptation, Psychological , Anxiety Disorders/epidemiology , Anxiety/epidemiology , Depression/epidemiology , Depressive Disorder/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , England/epidemiology , Female , Humans , Longitudinal Studies , Male , Middle Aged , Psychological Distress , Risk , Time Factors , Young Adult
15.
Sci Rep ; 11(1): 5378, 2021 03 08.
Article in English | MEDLINE | ID: covidwho-1123141

ABSTRACT

COVID-19 caseloads in England have passed through a first peak, and at the time of this analysis appeared to be gradually increasing, potentially signalling the emergence of a second wave. To ensure continued response to the epidemic is most effective, it is imperative to better understand both retrospectively and prospectively the geographical evolution of COVID-19 caseloads and deaths at small-area resolution, identify localised areas in space-time at significantly higher risk, quantify the impact of changes in localised population mobility (or movement) on caseloads, identify localised risk factors for increased mortality and project the likely course of the epidemic at high spatial resolution in coming weeks. We applied a Bayesian hierarchical space-time SEIR model to assess the spatiotemporal variability of COVID-19 caseloads (transmission) and deaths at small-area scale in England [Middle Layer Super Output Area (MSOA), 6791 units] and by week (using observed data from week 5 to 34 of 2020), including key determinants, the modelled transmission dynamics and spatial-temporal random effects. We also estimate the number of cases and deaths at small-area resolution with uncertainty projected forward in time by MSOA (up to week 51 of 2020), the impact mobility reductions (and subsequent easing) have had on COVID-19 caseloads and quantify the impact of key socio-demographic risk factors on COVID-19 related mortality risk by MSOA. Reductions in population mobility during the course of the first lockdown had a significant impact on the reduction of COVID-19 caseloads across England, however local authorities have had a varied rate of reduction in population movement which our model suggest has substantially impacted the geographic heterogeneity in caseloads at small-area scale. The steady gain in population mobility, observed from late April, appears to have contributed to a slowdown in caseload reductions towards late June and subsequent start of the second wave. MSOA with higher proportions of elderly (70+ years of age) and elderly living in deprivation, both with very distinct geographic distributions, have a significantly elevated COVID-19 mortality rates. While non-pharmaceutical interventions (that is, reductions in population mobility and social distancing) had a profound impact on the trajectory of the first wave of the COVID-19 outbreak in England, increased population mobility appears to have significantly contributed to the second wave. A number of contiguous small-areas appear to be at a significant elevated risk of high COVID-19 transmission, many of which are also at increased risk for higher mortality rates. A geographically staggered re-introduction of intensified social distancing measures is advised and limited cross MSOA movement if the magnitude and geographic extent of the second wave is to be reduced.


Subject(s)
/epidemiology , Models, Biological , Spatio-Temporal Analysis , Bayes Theorem , Disease Susceptibility , England/epidemiology , Geography , Humans , Multivariate Analysis , Risk Factors , Time Factors
16.
Int J Prison Health ; ahead-of-print(ahead-of-print)2021 03 10.
Article in English | MEDLINE | ID: covidwho-1122376

ABSTRACT

PURPOSE: The outbreak of the severe acute respiratory syndrome coronavirus 2 virus and subsequent COVID-19 illness has had a major impact on all levels of society internationally. The extent of the impact of COVID-19 on prison staff and prisoners in England and Wales is unknown. Testing for COVID-19 both asymptomatic and symptomatic, as well as for antibodies, to date, has been minimal. The purpose of this paper is to explore the widespread testing of COVID-19 in prisons poses philosophical and ethical questions around trust, efficacy and ethicacy. DESIGN/METHODOLOGY/APPROACH: This paper is both descriptive, providing an overview of the widespread testing of COVID-19 in prisoners in England and Wales, and conceptual in that it discusses and argues the issues associated with large-scale testing. This paper provides a discussion, using comparative studies, of the issues associated with large-scale testing of prisoners across the prison estate in England and Wales (120 prisons). The issues identified in this paper are contextualised through the lens of COVID-19, but they are equally transferrable to epidemiological studies of any pandemic. Given the prevalence of COVID-19 globally and the lack of information about its spread in prisons, at the time of writing this paper, there is a programme of asymptomatic testing of prisoners. However, there remains a paucity of data on the spread of COVID-19 in prisons because of the progress with the ongoing testing programme. FINDINGS: The authors argue that the widespread testing of prisoners requires careful consideration of the details regarding who is included in testing, how consent is gained and how tests are administered. This paper outlines and argues the importance of considering the complex nuance of power relationships within the prison system, among prisoner officers, medical staff and prisoners and the detrimental consequences. PRACTICAL IMPLICATIONS: The widespread testing of COVID-19 presents ethical and practical challenges. Careful planning is required when considering the ethics of who should be included in COVID-19 testing, how consent will be gained, who and how tests will be administered and very practical challenges around the recording and assigning of COVID-19 test kits inside the prison. The current system for the general population requires scanning of barcodes and registration using a mobile number; these facilities are not permitted inside a prison. ORIGINALITY/VALUE: This paper looks at the issues associated with mass testing of prisoners for COVID-19. According to the authors' knowledge, there has not been any research that looks at the issues of testing either in the UK or internationally. The literature available details countries' responses to the pandemic rather and scientific papers on the development of vaccines. Therefore, this paper is an original review of some of the practicalities that need to be addressed to ensure that testing can be as successful as possible.


Subject(s)
/diagnosis , Prisoners , Adult , /ethics , England/epidemiology , Female , Humans , Male , Prevalence , Trust , Wales/epidemiology
17.
BMC Med ; 19(1): 71, 2021 03 05.
Article in English | MEDLINE | ID: covidwho-1119426

ABSTRACT

BACKGROUND: To estimate excess mortality for care home residents during the COVID-19 pandemic in England, exploring associations with care home characteristics. METHODS: Daily number of deaths in all residential and nursing homes in England notified to the Care Quality Commission (CQC) from 1 January 2017 to 7 August 2020. Care home-level data linked with CQC care home register to identify home characteristics: client type (over 65s/children and adults), ownership status (for-profit/not-for-profit; branded/independent) and size (small/medium/large). Excess deaths computed as the difference between observed and predicted deaths using local authority fixed-effect Poisson regressions on pre-pandemic data. Fixed-effect logistic regressions were used to model odds of experiencing COVID-19 suspected/confirmed deaths. RESULTS: Up to 7 August 2020, there were 29,542 (95% CI 25,176 to 33,908) excess deaths in all care homes. Excess deaths represented 6.5% (95% CI 5.5 to 7.4%) of all care home beds, higher in nursing (8.4%) than residential (4.6%) homes. 64.7% (95% CI 56.4 to 76.0%) of the excess deaths were confirmed/suspected COVID-19. Almost all excess deaths were recorded in the quarter (27.4%) of homes with any COVID-19 fatalities. The odds of experiencing COVID-19 attributable deaths were higher in homes providing nursing services (OR 1.8, 95% CI 1.6 to 2.0), to older people and/or with dementia (OR 5.5, 95% CI 4.4 to 6.8), amongst larger (vs. small) homes (OR 13.3, 95% CI 11.5 to 15.4) and belonging to a large provider/brand (OR 1.2, 95% CI 1.1 to 1.3). There was no significant association with for-profit status of providers. CONCLUSIONS: To limit excess mortality, policy should be targeted at care homes to minimise the risk of ingress of disease and limit subsequent transmission. Our findings provide specific characteristic targets for further research on mechanisms and policy priority.


Subject(s)
Health Services for the Aged , Homes for the Aged/statistics & numerical data , Nursing Homes/statistics & numerical data , Quality of Health Care , Residential Facilities/statistics & numerical data , Aged , Aged, 80 and over , /prevention & control , Cohort Studies , England/epidemiology , Female , Health Services Needs and Demand , Health Services for the Aged/organization & administration , Health Services for the Aged/standards , Humans , Male , Mortality
18.
Am J Respir Crit Care Med ; 203(5): 532-534, 2021 03 01.
Article in English | MEDLINE | ID: covidwho-1119354
19.
Int J Qual Health Care ; 33(1)2021 Mar 16.
Article in English | MEDLINE | ID: covidwho-1119021

ABSTRACT

BACKGROUND: COVID-19 pandemic has had a major impact globally, with older people living in aged care homes suffering high death rates. OBJECTIVES: We aimed to compare the impact of initial government policies on this vulnerable older population between the UK and Australia during the first wave of attack. METHODS: We searched websites of governments in the UK and Australia and media outlets. We examined the key policies including the national lockdown dates and the distribution of some important resources (personal protective equipment and testing) and the effects of these initial policies on the mortality rates in the aged care homes during the first wave of attack of COVID-19. RESULTS: We found that both countries had prioritized resources to hospitals over aged care homes during the first wave of attack. Both countries had lower priority for aged care residents in hospitals (e.g. discharging without testing for COVID-19 or discouraging admissions). However, deaths in aged care homes were 270 times higher in the UK than in Australia as on 7 May 2020 (despite UK having a population only 2.5 times larger than Australia). The lower fatality rate in Australia may have been due to the earlier lockdown strategy when the total daily cases were low in Australia (118) compared to the UK (over 1000), as well as the better community viral testing regime in Australia. CONCLUSION: In conclusion, the public health policy in Australia aimed towards earlier intervention with earlier national lockdown and more viral testing to prevent new cases. This primary prevention could have resulted in more lives being saved. In contrast, the initial policy in the UK focussed mainly on protecting resources for hospitals, and there was a delay in national lockdown intervention and lower viral testing rate, resulting in more lives lost in the aged care sector.


Subject(s)
/prevention & control , Health Policy , Homes for the Aged/organization & administration , Australia/epidemiology , England/epidemiology , Hospitalization/statistics & numerical data , Humans , Resource Allocation/methods , Resource Allocation/organization & administration , United Kingdom/epidemiology
20.
Elife ; 102021 03 02.
Article in English | MEDLINE | ID: covidwho-1112865

ABSTRACT

COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1167 residents from 337 care homes were identified from a dataset of 6600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns - outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population.


Subject(s)
/epidemiology , Nursing Homes , /genetics , Aged, 80 and over , Disease Outbreaks , England/epidemiology , Female , Humans , Infectious Disease Transmission, Patient-to-Professional , Infectious Disease Transmission, Professional-to-Patient , Male , Polymorphism, Single Nucleotide , Sequence Analysis , Time Factors
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