The impact of COVID-19 on adjusted mortality risk in care homes for older adults in Wales, UK: a retrospective population-based cohort study for mortality in 2016-2020

Ethical challenges causing moral distress: nursing home staff's experiences of working during the COVID-19 pandemic

OBJECTIVE

To investigate the experiences of healthcare staff in nursing homes during the COVID-19 pandemic.

DESIGN

Individual interviews. Latent qualitative content analysis.

SETTING

Ten nursing homes in Sweden.

SUBJECTS

Physicians, nurses and nurse assistants working in Swedish nursing homes.

MAIN OUTCOME MEASURES

Participants' experiences of working in nursing homes during the COVID-19 pandemic.

RESULTS

Four manifest categories were found, namely: Balancing restrictions and allocation of scarce resources with care needs; Prioritizing and acting against moral values in advance care planning; Distrust in cooperation and Leadership and staff turnover - a factor for moral distress. The latent theme Experiences of handling ethical challenges caused by the COVID-19 pandemic gave a deeper meaning to the categories.

CONCLUSION

During the pandemic, nursing home staff encountered ethical challenges that caused moral distress. Moral distress stemmed from not being given adequate conditions to perform their work properly, and thus not being able to give the residents adequate care. Another aspect of moral distress originated from feeling forced to act against their moral values when a course of action was considered to cause discomfort or harm to a resident. Alerting employers and policymakers to the harm and inequality experienced by staff and the difficulty in delivering appropriate care is essential. Making proposals for improvements and developing guidelines together with staff to recognize their role and to develop better guidance for good care is vital in order to support and sustain the nursing home workforce.

Understanding health service utilisation patterns for care home residents during the COVID-19 pandemic using routinely collected healthcare data

BACKGROUND

Healthcare in care homes during the COVID-19 pandemic required a balance, providing treatment while minimising exposure risk. Policy for how residents should receive care changed rapidly throughout the pandemic. A lack of accessible data on care home residents over this time meant policy decisions were difficult to make and verify. This study investigates common patterns of healthcare utilisation for care home residents in relation to COVID-19 testing events, and associations between utilisation patterns and resident characteristics.

METHODS

Datasets from County Durham and Darlington NHS Foundation Trust including secondary care, community care and a care home telehealth app are linked by NHS number used to define daily healthcare utilisation sequences for care home residents. We derive four 10-day sets of sequences related to Pillar 1 COVID-19 testing; before [1] and after [2] a resident's first positive test and before [3] and after [4] a resident's first test. These sequences are clustered, grouping residents with similar healthcare patterns in each set. Association of individual characteristics (e.g. health conditions such as diabetes and dementia) with healthcare patterns are investigated.

RESULTS

We demonstrate how routinely collected health data can be used to produce longitudinal descriptions of patient care. Clustered sequences [1,2,3,4] are produced for 3,471 care home residents tested between 01/03/2020-01/09/2021. Clusters characterised by higher levels of utilisation were significantly associated with higher prevalence of diabetes. Dementia is associated with higher levels of care after a testing event and appears to be correlated with a hospital discharge after a first test. Residents discharged from inpatient care within 10 days of their first test had the same mortality rate as those who stayed in hospital.

CONCLUSION

We provide longitudinal, resident-level data on care home resident healthcare during the COVID-19 pandemic. We find that vulnerable residents were associated with higher levels of healthcare usage despite the additional risks. Implications of findings are limited by the challenges of routinely collected data. However, this study demonstrates the potential for further research into healthcare pathways using linked, routinely collected datasets.

Analysis of the impact of COVID-19 on Scotland's care-homes from March 2020 to October 2021: national linked data cohort analysis

BACKGROUND

The impact of the COVID-19 pandemic on long-term care residents remains of wide interest, but most analyses focus on the initial wave of infections.

OBJECTIVE

To examine change over time in: (i) The size, duration, classification and pattern of care-home outbreaks of COVID-19 and associated mortality and (ii) characteristics associated with an outbreak.

DESIGN

Retrospective observational cohort study using routinely-collected data.

SETTING

All adult care-homes in Scotland (1,092 homes, 41,299 places).

METHODS

Analysis was undertaken at care-home level, over three periods. Period (P)1 01/03/2020-31/08/2020; P2 01/09/2020-31/05/2021 and P3 01/06/2021-31/10/2021. Outcomes were the presence and characteristics of outbreaks and mortality within the care-home. Cluster analysis was used to compare the pattern of outbreaks. Logistic regression examined care-home characteristics associated with outbreaks.

RESULTS

In total 296 (27.1%) care-homes had one outbreak, 220 (20.1%) had two, 91 (8.3%) had three, and 68 (6.2%) had four or more. There were 1,313 outbreaks involving residents: 431 outbreaks in P1, 559 in P2 and 323 in P3. The COVID-19 mortality rate per 1,000 beds fell from 45.8 in P1, to 29.3 in P2, and 3.5 in P3. Larger care-homes were much more likely to have an outbreak, but associations between size and outbreaks were weaker in later periods.

CONCLUSIONS

COVID-19 mitigation measures appear to have been beneficial, although the impact on residents remained severe until early 2021. Care-home residents, staff, relatives and providers are critical groups for consideration and involvement in future pandemic planning.

Greatest Risk Factor for Death from COVID-19: Older Age, Chronic Disease Burden, or Place of Residence? Descriptive Analysis of Population-Level Canadian Data

During the first wave of COVID-19, three-quarters of Canadian deaths were among those age 80 and older. We examined whether age, chronic disease load, sex, or place was the strongest predictor of such deaths. A cross-sectional analysis of administrative data from 1 January 2020 to 30 October 2020 for the population of Ontario (n = 15,023,174) was performed. Using logistic regression analysis, we determined whether place of residence (community dwelling, community dwelling with formal home care, or long-term care facility), age group, sex, or chronic disease burden was most strongly associated with the outcome of death within 60 days of a positive SARS-CoV-2 PCR test. Overall, there were 2766 deaths attributed to COVID-19. The age-related odds of dying increased from 6.1 (age 65-74) to 13.4 (age 85 or older) relative to those aged <65 years. This age effect was dwarfed by an odds ratio of 117.1 for those living in long-term care versus independently in the community, adjusted for age, sex, and chronic disease burden. The risk of death from COVID-19 aligned much more with social realities than individual risks. The disproportionate mortality arising specifically from institutional residence demands action to identify sources and ameliorate the harms of living in such facilities.

Individual and contextual risk factors for mortality in nursing home residents during the first wave of COVID-19 in France: a multilevel analysis of a nationwide cohort study

BACKGROUND

Mortality amongst nursing home (NH) residents increased by 43% during the first wave of coronavirus disease 2019 (COVID-19). We estimated the 'contextual effect' on mortality, tried to explain it by NH characteristics and identified resident- and NH-level risk factors for mortality.

METHODS

The contextual effect was measured for two cohorts of NH residents managed by the general scheme in metropolitan France (RESIDESMS data from 03/01/2020 to 05/31/2020 and 03/01/2019 to 05/31/2019) by the intraclass correlation coefficient (ICC) estimated from mixed-effects logistic regression.

RESULTS

Amongst 385,300 residents (5,339 NHs) included in 2020 (median age 89 years, 25% men), 9.1% died, versus 6.7% of 379,926 residents (5,270 NHs) in 2019. In the empty model, the ICC was 9.3% in 2020 and 1.5% in 2019. Only the geographic location partially explained the heterogeneity observed in 2020 (ICC: 6.5% after adjustment). Associations with mortality were stronger in 2020 than in 2019 for male sex and diabetes and weaker for heart disease, chronic respiratory disease and residence <6 months. Mortality was higher in 2020 (15.1%) than 2019 (6.3%) in NHs with at least one death with a mention of COVID-19 and more heterogeneous (ICC: 8.0%) than in the others (mortality: 6.7% in both years; ICC: 1.1%).

CONCLUSION

Our results suggest that the COVID-19 crisis had a heterogeneous impact on mortality in NH residents and that geographic location explain a part of the contextual effect, which appears to have had little influence on mortality in NHs not being affected by the virus.

Usefulness of linked data for infectious disease events: a systematic review

Surveillance is a key public health function to enable early detection of infectious disease events and inform public health action. Data linkage may improve the depth of data for response to infectious disease events. This study aimed to describe the uses of linked data for infectious disease events. A systematic review was conducted using Pubmed, CINAHL and Web of Science. Studies were included if they used data linkage for an acute infectious disease event (e.g. outbreak of disease). We summarised the event, study aims and designs; data sets; linkage methods; outcomes reported; and benefits and limitations. Fifty-four studies were included. Uses of linkage for infectious disease events included assessment of severity of disease and risk factors; improved case finding and contact tracing; and vaccine uptake, safety and effectiveness. The ability to conduct larger scale population level studies was identified as a benefit, in particular for rarer exposures, risk factors or outcomes. Limitations included timeliness, data quality and inability to collect additional variables. This review demonstrated multiple uses of data linkage for infectious disease events. As infectious disease events occur without warning, there is a need to establish pre-approved protocols and the infrastructure for data-linkage to enhance information available during an event.

Towards an understanding of inequalities in accessing residential and nursing home provision: The role of geographical approaches

Suggestions of the existence of so-called 'social care deserts' in England in the years leading up to the COVID-19 pandemic drew attention to the potential impact of geographical inequalities on the availability of residential, nursing and domiciliary care. To date, much of this analysis has been conducted at spatially aggregated scales such as that of local authorities or postcode sector. Hidden within such aggregate-level analysis however are geographical differences in the local provision of care services. In this paper, we draw attention to geographical modelling techniques that can be used to examine local trends in the supply of social care services in relation to potential demand. These spatial models can be used to examine variations in the number of facilities (or choice) within reasonable drive times/distances. Drawing on a national database of residential and nursing care beds in Wales for March 2020, we illustrate the potential of such techniques to provide an insight into current patterns in access to care homes, and to monitor future changes in the fall-out from the effects of the COVID-19 pandemic on the care home sector. The concentration of care home sites in metropolitan areas and in the heavily populated post-industrial valleys in the south-east is identified, but significant demand present in these areas ameliorates scores towards mid-range ratios. We conclude by suggesting that the types of techniques used in this study enable disparities in provision within localised areas to be better explored, thereby helping planners and policy makers to address potential inequalities in provision.

Managing the Impact of COVID-19 in Nursing Homes and Long-Term Care Facilities: An Update

Older adults in nursing homes are at greatest risk of morbidity and mortality from SARS-CoV-2 infection. Nursing home residents constituted one-third to more than half of all deaths during the early waves of the COVID-19 pandemic. Following this, widespread adaptation of infection prevention and control measures and the supply and use of personal protective equipment resulted in a significant decrease in nursing home infections and deaths. For nursing homes, the most important determinant of experiencing a SARS-CoV-2 outbreak in the first instance appears to be community-transmission levels (particularly with variants of concern), although nursing home size and quality, for-profit status, and sociodemographic characteristics are also important. Use of visitation bans, imposed to reduce the impact of COVID-19 on residents, must be delicately balanced against their impact on resident, friend or family, and staff well-being. The successful rollout of primary vaccination has resulted in a sharp decrease in morbidity and mortality from SARS-CoV-2 in nursing homes. However, emerging evidence suggests that vaccine efficacy may wane over time, and the use of a third or additional vaccine "booster" doses in nursing home residents restores protection afforded by primary vaccination. Ongoing monitoring of vaccine efficacy in terms of infection, morbidity, and mortality is crucial in this vulnerable group in informing ongoing SARS-CoV-2 vaccine boosting strategies. Here, we detail the impact of SARS-CoV-2 on nursing home residents and discuss important considerations in the management of nursing home SARS-CoV-2 outbreaks. We additionally examine the use of testing strategies, nonpharmacologic outbreak control measures and vaccination strategies in this cohort. Finally, the impact of SARS-CoV-2 on the sector is reflected on as we emphasize the need for adoption of universal standards of medical care and integration with wider public health infrastructure in nursing homes in order to provide a safe and effective long-term care sector.

Health impact of the first and second wave of COVID-19 and related restrictive measures among nursing home residents: a scoping review

Background and objectives

COVID-19 disproportionally affects older adults living in nursing homes. The purpose of this review was to explore and map the scientific literature on the health impact of COVID-19 and related restrictive measures during the first and second wave among nursing home residents. A specific focus was placed on health data collected among nursing home residents themselves.

Research design and methods

In this study, best practices for scoping reviews were followed. Five databases were systematically searched for peer-reviewed empirical studies published up until December 2020 in which data were collected among nursing home residents. Articles were categorized according to the type of health impact (physical, social and/or psychological) and study focus (impact of COVID-19 virus or related restrictive measures). Findings were presented using a narrative style.

Results

Of 60 included studies, 57 examined the physical impact of COVID-19. All of these focused on the direct impact of the COVID-19 virus. These studies often used an observational design and quantitative data collection methods, such as swab testing or reviewing health records. Only three studies examined the psychological impact of COVID-19 of which one study focused on the impact of COVID-19-related restrictive measures. Findings were contradictory; both decreased and improved psychological wellbeing was found during the pandemic compared with before. No studies were found that examined the impact on social wellbeing and one study examined other health-related outcomes, including preference changes of nursing home residents in Advanced Care planning following the pandemic.

Discussion and implications

Studies into the impact of the first and second wave of the COVID-19 pandemic among nursing home residents predominantly focused on the physical impact. Future studies into the psychological and social impact that collect data among residents themselves will provide more insight into their perspectives, such as lived experiences, wishes, needs and possibilities during later phases of the pandemic. These insights can inform policy makers and healthcare professionals in providing person-centered care during the remaining COVID-19 pandemic and in future crisis periods.

Robust SARS-CoV-2-specific and heterologous immune responses in vaccine-naïve residents of long-term care facilities who survive natural infection

We studied humoral and cellular immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 152 long-term care facility staff and 124 residents over a prospective 4-month period shortly after the first wave of infection in England. We show that residents of long-term care facilities developed high and stable levels of antibodies against spike protein and receptor-binding domain. Nucleocapsid-specific responses were also elevated but waned over time. Antibodies showed stable and equivalent levels of functional inhibition against spike-angiotensin-converting enzyme 2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or other respiratory syncytial viruses. SARS-CoV-2-specific cellular responses were similar across all ages but virus-specific populations showed elevated levels of activation in older donors. Thus, survivors of SARS-CoV-2 infection show a robust and stable immunity against the virus that does not negatively impact responses to other seasonal viruses.

COVID-19 risk factors amongst 14,786 care home residents: an observational longitudinal analysis including daily community positive test rates of COVID-19, hospital stays and vaccination status in Wales (UK) between 1 September 2020 and 1 May 2021

BACKGROUND

COVID-19 vaccinations have been prioritised for high risk individuals.

AIM

Determine individual-level risk factors for care home residents testing positive for SARS-CoV-2.

STUDY DESIGN

Longitudinal observational cohort study using individual-level linked data from the Secure Anonymised Information Linkage (SAIL) databank.

SETTING

Fourteen thousand seven hundred and eighty-six older care home residents (aged 65+) living in Wales between 1 September 2020 and 1 May 2021. Our dataset consisted of 2,613,341 individual-level daily observations within 697 care homes.

METHODS

We estimated odds ratios (ORs [95% confidence interval]) using multilevel logistic regression models. Our outcome of interest was a positive SARS-CoV-2 PCR test. We included time-dependent covariates for the estimated community positive test rate of COVID-19, hospital inpatient status, vaccination status and frailty. Additional covariates were included for age, sex and specialist care home services.

RESULTS

The multivariable regression model indicated an increase in age (OR 1.01 [1.00,1.01] per year), community positive test rate (OR 1.13 [1.12,1.13] per percent increase), hospital inpatients (OR 7.40 [6.54,8.36]), and residents in care homes with non-specialist dementia care (OR 1.42 [1.01,1.99]) had an increased odds of a positive test. Having a positive test prior to the observation period (OR 0.58 [0.49,0.68]) and either one or two doses of a vaccine (0.21 [0.17,0.25] and 0.05 [0.02,0.09], respectively) were associated with a decreased odds.

CONCLUSIONS

Care providers need to remain vigilant despite the vaccination rollout, and extra precautions should be taken when caring for the most vulnerable. Minimising potential COVID-19 infection for care home residents when admitted to hospital should be prioritised.

Mortality of care home residents and community-dwelling controls during the covid-19 pandemic in 2020: matched cohort study

Objective

This study aimed to estimate and compare mortality of care home residents, and matched community-dwelling controls, during the COVID-19 pandemic from primary care electronic health records in England.

Design

Matched cohort study.

Setting and Participants

Family practices in England in the Clinical Practice Research Datalink Aurum database. There were 83,627 care home residents in 2020, with 26,923 deaths; 80,730 (97%) were matched on age, sex, and family practice with 300,445 community-dwelling adults.

Methods

All-cause mortality was evaluated and adjusted rate ratios by negative binomial regression were adjusted for age, sex, number of long-term conditions, frailty category, region, calendar month or week, and clustering by family practice.

Results

Underlying mortality of care home residents was higher than community controls (adjusted rate ratio 5.59, 95% confidence interval 5.23‒5.99, P < .001). During April 2020, there was a net increase in mortality of care home residents over that of controls. The mortality rate of care home residents was 27.2 deaths per 1000 patients per week, compared with 2.31 per 1000 for controls. Excess deaths for care home residents, above that predicted from pre-pandemic years, peaked between April 13 and 19 (men, 27.7, 95% confidence interval 25.1‒30.3; women, 17.4, 15.9‒18.8 per 1000 per week). Compared with care home residents, long-term conditions and frailty were differentially associated with greater mortality in community-dwelling controls.

Conclusions and Implications

Individual-patient data from primary care electronic health records may be used to estimate mortality in care home residents. Mortality is substantially higher than for community-dwelling comparators and showed a disproportionate increase in the first wave of the COVID-19 pandemic. Care home residents require particular protection during periods of high infectious disease transmission.

Incidence, Mortality, and Risk Factors of COVID-19 in Nursing Homes

During the period from March 2020 to January 2021, we performed an analysis of incidence, mortality, and risk factors of COVID-19 in nursing homes (NHs) in two health departments (HDs) of Castellon (Spain) 2021 through epidemiological surveillance and an ecological design. Laboratory-confirmed COVID-19 cases, cumulative incidence rate (CIR), and mortality rate (MR) of 27 NHs were collected. Information of residents, staff, and facilities was obtained by questionnaire. Multilevel Poisson regression models were applied. All NHs in the HDs participated with 2229 residents (median: 83 years old, 67.3% women) and 1666 staff. Among residents, 815 cases (CIR: 34.8 per 100) and 202 deaths (MR: 8.7 per 100, case fatality 21.0%) were reported and, among staff, 296 cases (CIR: 19.2 per 100) without deaths. Residents' CIR and MR increased with staff CIR, age of the building, residents/staff ratios, occupancy rate, and crowding index; CIR increased with private NH ownership, large NH size, large urban area, and the percentage of women residents; and MR was associated with residents' severe disabilities. In conclusion, several risk factors of COVID-19 incidence and mortality can be prevented by improving infection and quality controls, ameliorating residents/staff ratios, improving structural facilities, and increasing NH public ownership to avoid new outbreaks.

Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an observational study of 4.3 million adults over the age of 65

BACKGROUND

Residents in care homes have been severely impacted by COVID-19. We describe trends in the mortality risk among residents of care homes compared to private homes.

METHODS

On behalf of NHS England we used OpenSAFELY-TPP to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to Care and Quality Commission data.

FINDINGS

We included 4,340,648 people aged 65 years or older on the 1st of February 2019, 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to those in private housing in February 2019: comparative mortality figure (CMF) = 10.59 (95%CI = 9.51, 11.81) among women, and 10.87 (9.93, 11.90) among men. By April 2020 these relative differences had increased to more than 17 times with CMFs of 17.57 (16.43, 18.79) among women and 18.17 (17.22, 19.17) among men. CMFs did not increase during the second wave, despite a rise in the absolute age-standardised COVID-19 mortality risks.

INTERPRETATION

COVID-19 has had a disproportionate impact on the mortality of care home residents in England compared to older residents of private homes, but only in the first wave. This may be explained by a degree of acquired immunity, improved protective measures or changes in the underlying frailty of the populations. The care home population should be prioritised for measures aimed at controlling COVID-19.

FUNDING

Medical Research Council MR/V015737/1.

Validating the QCOVID risk prediction algorithm for risk of mortality from COVID-19 in the adult population in Wales, UK

Introduction

COVID-19 risk prediction algorithms can be used to identify at-risk individuals from short-term serious adverse COVID-19 outcomes such as hospitalisation and death. It is important to validate these algorithms in different and diverse populations to help guide risk management decisions and target vaccination and treatment programs to the most vulnerable individuals in society.

Objectives

To validate externally the QCOVID risk prediction algorithm that predicts mortality outcomes from COVID-19 in the adult population of Wales, UK.

Methods

We conducted a retrospective cohort study using routinely collected individual-level data held in the Secure Anonymised Information Linkage (SAIL) Databank. The cohort included individuals aged between 19 and 100 years, living in Wales on 24th January 2020, registered with a SAIL-providing general practice, and followed-up to death or study end (28th July 2020). Demographic, primary and secondary healthcare, and dispensing data were used to derive all the predictor variables used to develop the published QCOVID algorithm. Mortality data were used to define time to confirmed or suspected COVID-19 death. Performance metrics, including R2 values (explained variation), Brier scores, and measures of discrimination and calibration were calculated for two periods (24th January-30th April 2020 and 1st May-28th July 2020) to assess algorithm performance.

Results

1,956,760 individuals were included. 1,192 (0.06%) and 610 (0.03%) COVID-19 deaths occurred in the first and second time periods, respectively. The algorithms fitted the Welsh data and population well, explaining 68.8% (95% CI: 66.9-70.4) of the variation in time to death, Harrell's C statistic: 0.929 (95% CI: 0.921-0.937) and D statistic: 3.036 (95% CI: 2.913-3.159) for males in the first period. Similar results were found for females and in the second time period for both sexes.

Conclusions

The QCOVID algorithm developed in England can be used for public health risk management for the adult Welsh population.

Machine learning for emerging infectious disease field responses

Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised global public health crises in recent decades. Without existing protective immunity, an EID may spread rapidly and cause mass casualties in a very short time. Therefore, it is imperative to identify cases with risk of disease progression for the optimized allocation of medical resources in case medical facilities are overwhelmed with a flood of patients. This study has aimed to cope with this challenge from the aspect of preventive medicine by exploiting machine learning technologies. The study has been based on 83,227 hospital admissions with influenza-like illness and we analysed the risk effects of 19 comorbidities along with age and gender for severe illness or mortality risk. The experimental results revealed that the decision rules derived from the machine learning based prediction models can provide valuable guidelines for the healthcare policy makers to develop an effective vaccination strategy. Furthermore, in case the healthcare facilities are overwhelmed by patients with EID, which frequently occurred in the recent COVID-19 pandemic, the frontline physicians can incorporate the proposed prediction models to triage patients suffering minor symptoms without laboratory tests, which may become scarce during an EID disaster. In conclusion, our study has demonstrated an effective approach to exploit machine learning technologies to cope with the challenges faced during the outbreak of an EID.

Making progress: but a way to go-the age and ageing care-home collection

Care homes enable people with advanced physical and cognitive impairment to live well with 24-h support from staff. They are a feature of care systems in most countries. They have proved pivotal to the coronavirus disease 2019 (COVID-19) response. We searched Age and Ageing for care-home articles published since 2015. From these we collated 42 into the Age and Ageing care-home collection. This collection draws together important papers that show how Age and Ageing is helping to shape and grow care-home research. The  collection outlines the technical issues that researchers face by grouping together important feasibility trials conducted in the sector. It looks at the challenges of measuring quality of life and working with routine data in care homes. It brings together observational studies considering loneliness, functional dependency, stroke outcomes, prescribing and acute deterioration. Health services research in care homes is represented by two studies that demonstrate realist evaluation as a way to make sense of service innovations. Papers are included that consider: non-pharmacological strategies for residents with dementia, end-of-life care, sexuality and intimacy and the care-home workforce. Given the importance of the COVID-19 pandemic in care homes, all of the care home COVID-19 papers published in Age and Ageing to date are included. Finally, a group of papers that present innovative approaches to research in care homes, each of which give voice to residents and/or staff, are collated and presented as a way of moving towards a more resident and care home centred research agenda.

Association between vaccination and preventive routines on COVID-19-related mortality in nursing home facilities: a population-based systematic retrospective chart review

Background:

Older and frail individuals are at high risk of dying from COVID-19, and residents in nursing homes (NHs) are overrepresented in death rates. We explored four different periods during the COVID-19 pandemic to analyze the effects of improved preventive routines and vaccinations, respectively, on mortality in NHs.

Methods:

We undertook a population-based systematic retrospective chart review comprising 136 NH facilities in southeast Sweden. All residents, among these facilities, who died within 30 days after a laboratory-verified COVID-19 diagnosis during four separate 92-day periods representing early pandemic (second quarter 2020), middle of the pandemic (fourth quarter 2020), early post-vaccination phase (first quarter 2021), and the following post-vaccination phase (second quarter 2021). Mortality together with electronic chart data on demographic variables, comorbidity, frailty, and cause of death was collected.

Results:

The number of deaths during the four periods was 104, 120, 34 and 4, respectively, with a significant reduction in the two post-vaccination periods (P < 0.001). COVID-19 was assessed as the dominant cause of death in 20 (19%), 19 (16%), 4 (12%) and 1 (3%) residents in each period (P < 0.01). The respective median age in the four studied periods varied between 87and 89 years, and three or more diagnoses besides COVID-19 were present in 70–90% of the respective periods’ study population. Considerable or severe frailty was found in all residents.

Conclusions:

Vaccination against COVID-19 seems associated with a reduced number of deaths in NHs. We could not demonstrate an effect on mortality merely from the protective routines that were undertaken.

Factors associated with excess all-cause mortality in the first wave of the COVID-19 pandemic in the UK: A time series analysis using the Clinical Practice Research Datalink

BACKGROUND

Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic.

METHODS AND FINDINGS

We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception.

CONCLUSIONS

The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.

Analysing COVID-19 outcomes in the context of the 2019 Global Health Security (GHS) Index

Introduction

The Global Health Security Index benchmarks countries’ capacities to carry out the functions necessary to prevent, detect and respond to biological threats. The COVID-19 pandemic served as an opportunity to evaluate whether the Index contained the correct array of variables that influence countries’ abilities to respond to these threats; assess additional variables that may influence preparedness; and examine how the impact of preparedness components change during public health crises.

Methods

Linear regression models were examined to determine the relationship between excess mortality per capita for the first 500 days of countries’ COVID-19 pandemic and internal Index variables, as well as external variables including social cohesion; island status; perceived corruption; elderly population size; previous epidemic experience; stringency of non-pharmaceutical interventions; and social and political polarisation.

Results

COVID-19 outcomes were significantly associated with sociodemographic, political and governance variables external to the 2019 Index: social cohesion, reduction in social polarisation and reduced perceptions of corruption were consistently correlated with reduced excess mortality throughout the pandemic. The association of other variables assessed by the Index, like epidemiological workforce robustness, changed over time. Fixed country features, including geographic connectedness, larger elderly population and lack of prior coronavirus outbreak experience were detrimental to COVID-19 outcomes. Finally, there was evidence that countries that lacked certain capacities were able to develop these over the course of the pandemic.

Conclusions

Additional sociodemographic, political and governance variables should be included in future indices to improve their ability to characterise preparedness. Fixed characteristics, while not directly addressable, are useful for establishing countries’ inherent risk profile and can motivate those at greater risk to invest in preparedness. Particular components of preparedness vary in their impact on outcomes over the course of the pandemic, which may inform resource direction during ongoing crises. Future research should seek to further characterise time-dependent impacts as additional COVID-19 outcome data become available.

Case-control study to estimate odds of death within 28 days of positive test for SARS-CoV-2 prior to vaccination for residents of long-term care facilities in England, 2020-2021

BACKGROUND

Persons living in long-term care facilities (LTCFs) are presumed to be at higher risk of adverse outcomes from SARS-CoV-2 infection due to increasing age and frailty, but the magnitude of increased risk is not well quantified.

METHODS

After linking demographic and mortality data for cases with confirmed SARS-CoV-2 infection between March 2020 and January 2021 in England, a random sample of 6000 persons who died and 36 000 who did not die within 28 days of a positive test was obtained from the dataset of 3 020 800 patients. Based on an address-matching process, the residence type of each case was categorised into one of private home and residential or nursing LTCF. Univariable and multivariable logistic regression analysis was conducted.

RESULTS

Multivariable analysis showed that an interaction effect between age and residence type determined the outcome. Compared with a 60-year-old person not living in LTCF, the adjusted OR (aOR) for same-aged persons living in residential and nursing LTCFs was 1.77 (95% CI 1.21 to 2.6, p=0.0017) and 3.95 (95% CI 2.77 to 5.64, p<0.0001), respectively. At 90 years of age, aORs were 0.87 (95% CI 0.72 to 1.06, p=0.21) and 0.74 (95% CI 0.61 to 0.9, p=0.001), respectively. The model had an overall accuracy of 94.2% (94.2%) when applied to the full dataset of 2 978 800 patients.

CONCLUSION

This study found that residents of LTCFs in England had higher odds of death up to 80 years of age. Beyond 80 years, there was no difference in the odds of death for LTCF residents compared with those in the wider community.

Editorial: Applications of Cognitive and Behavioral Therapy in Response to COVID-19

The corona virus (COVID-19) continues to have a devastating health, economic, and social impact on our local and international communities. Cognitive and Behavioral Therapies (CBTs), as a family of therapies that posit cognitive, behavioral, emotional, and interpersonal change processes in the understanding and successful treatment of mental health disorders, have risen to the challenge. This special issue represents contributions from CBT experts on the impact on psychopathology, new assessment methods, adaptations of integrated behavioral health, telehealth, psychology training, and discusses a public health framework. The issue includes a series of articles offering guidance for the clinician on interventions for those impacted by trauma, CBT for youth and families, and telehealth for psychotic spectrum disorders and group therapy for social anxiety.

Magnitude, change over time, demographic characteristics and geographic distribution of excess deaths among nursing home residents during the first wave of COVID-19 in France: a nationwide cohort study

BACKGROUND

The objectives were to assess the excess deaths among Nursing Home (NH) residents during the first wave of the COVID-19 pandemic, to determine their part in the total excess deaths and whether there was a mortality displacement.

METHODS

We studied a cohort of 494,753 adults in 6,515 NHs in France exposed to COVID-19 pandemic (from 1 March to 31 May 2020) and compared with the 2014-2019 cohorts using data from the French National Health Data System. The main outcome was death. Excess deaths and standardized mortality ratios (SMRs) were estimated.

RESULT

There were 13,505 excess deaths. Mortality increased by 43% (SMR: 1.43). The mortality excess was higher among males than females (SMR: 1.51 and 1.38) and decreased with increasing age (SMRs in females: 1.61 in the 60-74 age group, 1.58 for 75-84, 1.41 for 85-94 and 1.31 for 95 or over; males: SMRs: 1.59 for 60-74, 1.69 for 75-84, 1.47 for 85-94 and 1.41 for 95 or over). No mortality displacement effect was observed up until 30 August 2020. By extrapolating to all NH residents nationally (N = 570,003), we estimated that they accounted for 51% of the general population excess deaths (N = 15,114 out of 29,563).

CONCLUSION

NH residents accounted for half of the total excess deaths in France during the first wave of the COVID-19 pandemic. The excess death rate was higher among males than females and among younger than older residents.

COVID-19 infection and attributable mortality in UK care homes: cohort study using active surveillance and electronic records (March-June 2020)

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.

Impact of COVID-19 on care-home mortality and life expectancy in Scotland

BACKGROUND

COVID-19 deaths are commoner among care-home residents, but the mortality burden has not been quantified.

METHODS

Care-home residency was identified via a national primary care registration database linked to mortality data. Life expectancy was estimated using Makeham-Gompertz models to (i) describe yearly life expectancy from November 2015 to October 2020 (ii) compare life expectancy (during 2016-18) between care-home residents and the wider population and (iii) apply care-home life expectancy estimates to COVID-19 death counts to estimate years of life lost (YLL).

RESULTS

Among care-home residents, life expectancy in 2015/16 to 2019/20 ranged from 2.7 to 2.3 years for women and 2.3 to 1.8 years for men. Age-sex-specific life expectancy in 2016-18 in care-home residents was lower than in the Scottish population (10 and 2.5 years in those aged 70 and 90, respectively). Applying care home-specific life expectancies to COVID-19 deaths yield mean YLLs for care-home residents of 2.6 and 2.2 for women and men, respectively. In total YLL care-home residents have lost 3,560 years in women and 2,046 years in men. Approximately half of deaths and a quarter of YLL attributed to COVID-19 were accounted for by the 5% of over-70s who were care-home residents.

CONCLUSION

COVID-19 infection has led to the loss of substantial years of life in care-home residents aged 70 years and over in Scotland. Prioritising the 5% of older adults who are care-home residents for vaccination is justified not only in terms of total deaths, but also in terms of YLL.

A retrospective cohort study of risk factors for mortality among nursing homes exposed to COVID-19 in Spain

Long-term care (LTC) facilities have shown remarkably high mortality rates during the coronavirus disease 2019 (COVID-19) outbreak in many countries¹, and different risk factors for mortality have been identified in this setting^2-5. Using facilities as the unit of analysis, we investigated multiple variables covering facility characteristics and socioeconomic characteristics of the geographic location to identify risk factors for excess mortality from a comprehensive perspective. Furthermore, we used a clustering approach to detect patterns in datasets and generate hypotheses regarding potential relationships between types of nursing homes and mortality trends. Our retrospective analysis included 167 nursing homes providing LTC to 8,716 residents during the COVID-19 outbreak in Catalonia (northeast Spain). According to multiple regression analysis, COVID-19-related and overall mortality at the facility level were significantly associated with a higher percentage of patients with complex diseases, lower scores on pandemic preparedness measures and higher population incidence of COVID-19 in the surrounding population. When grouping nursing homes into eight clusters based on common features, we found higher mortality rates in four clusters, mainly characterized by a higher proportion of residents with complex chronic conditions or advanced diseases, lower scores on pandemic preparedness, being located in rural areas and larger capacity, respectively.

Factors Associated With COVID-19 Hospitalizations and Deaths in French Nursing Homes

Objectives

To describe the clinical characteristics and management of residents in French nursing homes with suspected or confirmed coronavirus disease 2019 (COVID-19) and to determine the risk factors for COVID-19–related hospitalization and death in this population.

Design

A retrospective multicenter cohort study.

Setting and Participants

Four hundred eighty nursing home residents with suspected or confirmed COVID-19 between March 1 and May 20, 2020, were enrolled and followed until June 2, 2020, in 15 nursing homes in Marseille’s greater metropolitan area.

Methods

Demographic, clinical, laboratory, treatment type, and clinical outcome data were collected from patients’ medical records. Multivariable analysis was used to determine factors associated with COVID-19–related hospitalization and death. For the former, the competing risk analysis—based on Fine and Gray’s model—took death into account.

Results

A total of 480 residents were included. Median age was 88 years (IQR 80-93), and 330 residents were women. A total of 371 residents were symptomatic (77.3%), the most common symptoms being asthenia (47.9%), fever or hypothermia (48.1%), and dyspnea (35.6%). One hundred twenty-three patients (25.6%) were hospitalized and 96 (20%) died. Male gender [specific hazard ratio (sHR) 1.63, 95% confidence interval (CI) 1.12-2.35], diabetes (sHR 1.69, 95% CI 1.15-2.50), an altered level of consciousness (sHR 2.36, 95% CI 1.40-3.98), and dyspnea (sHR 1.69, 95% CI 1.09-2.62) were all associated with a greater risk of COVID-19–related hospitalization. Male gender [odds ratio (OR) 6.63, 95% CI 1.04-42.39], thermal dysregulation (OR 2.64, 95% CI 1.60-4.38), falls (2.21 95% CI 1.02-4.75), and being aged >85 years (OR 2.36, 95% CI 1.32-4.24) were all associated with increased COVID-19–related mortality risk, whereas polymedication (OR 0.46, 95% CI 0.27-0.77) and preventive anticoagulation (OR 0.46, 95% CI 0.27-0.79) were protective prognostic factors.

Conclusions and Implications

Male gender, being aged >85 years old, diabetes, dyspnea, thermal dysregulation, an altered level of consciousness, and falls must all be considered when identifying and protecting nursing home residents who are at greatest risk of COVID-19–related hospitalization and death.

An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: a national validation cohort study in England

BACKGROUND

Public policy measures and clinical risk assessments relevant to COVID-19 need to be aided by risk prediction models that are rigorously developed and validated. We aimed to externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England.

METHODS

We did a population-based cohort study using the UK Office for National Statistics Public Health Linked Data Asset, a cohort of individuals aged 19-100 years, based on the 2011 census and linked to Hospital Episode Statistics, the General Practice Extraction Service data for pandemic planning and research, and radiotherapy and systemic chemotherapy records. The primary outcome was time to COVID-19 death, defined as confirmed or suspected COVID-19 death as per death certification. Two periods were used: (1) Jan 24 to April 30, 2020, and (2) May 1 to July 28, 2020. We assessed the performance of the QCovid algorithms using measures of discrimination and calibration. Using predicted 90-day risk of COVID-19 death, we calculated r² values, Brier scores, and measures of discrimination and calibration with corresponding 95% CIs over the two time periods.

FINDINGS

We included 34 897 648 adults aged 19-100 years resident in England. 26 985 (0·08%) COVID-19 deaths occurred during the first period and 13 177 (0·04%) during the second. The algorithms had good discrimination and calibration in both periods. In the first period, they explained 77·1% (95% CI 76·9-77·4) of the variation in time to death in men and 76·3% (76·0-76·6) in women. The D statistic was 3·761 (3·732-3·789) for men and 3·671 (3·640-3·702) for women and Harrell's C was 0·935 (0·933-0·937) for men and 0·945 (0·943-0·947) for women. Similar results were obtained for the second time period. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths in the first period was 65·94% for men and 71·67% for women.

INTERPRETATION

The QCovid population-based risk algorithm performed well, showing high levels of discrimination for COVID-19 deaths in men and women for both time periods. QCovid has the potential to be dynamically updated as the pandemic evolves and, therefore, has potential use in guiding national policy.

FUNDING

UK National Institute for Health Research.

An epidemiological investigation of COVID-19 outbreaks in a group of care homes in Wales, UK: a retrospective cohort study

Background

This study describes the epidemiology of COVID-19 outbreaks in four care homes in terms of spread, severity, presentation and interventions.

Methods

Participants were 100 residents and 102 staff from four co-located care homes in Wales. Data were collected from the homes and Public Health Wales, including demographics, presentations, test status and results, hospital admissions and deaths. Genomic sequencing of confirmed case samples was completed, where possible. Epi-curves, crude attack rates, a Kaplan-Meier survival curve and adjusted hazard ratios were calculated using R.

Results

About 14 confirmed and 43 possible resident cases, 23 confirmed and 47 possible staff cases occurred. Crude attack rates of possible and confirmed cases were 57% (residents) and 69% (staff). Genomic sequencing for 10 confirmed case PCR samples identified at least 5 different UK lineages of COVID-19.42 (42%) residents died, 23 (55%) with COVID-19 or suspected COVID-19 recorded on the death certificate. The hazard ratio for death amongst resident possible and confirmed cases compared to null cases, adjusting for age and sex, was 13.26 (95% CI 5.61–31.34).

Conclusions

There were extensive outbreaks of COVID-19 in these homes with high crude attack rates and deaths. Universal testing and early isolation of residents are recommended.

Care-home outbreaks of COVID-19 in Scotland March to May 2020: National linked data cohort analysis

BACKGROUND

understanding care-home outbreaks of COVID-19 is a key public health priority in the ongoing pandemic to help protect vulnerable residents.

OBJECTIVE

to describe all outbreaks of COVID-19 infection in Scottish care-homes for older people between 01/03/2020 and 31/03/2020, with follow-up to 30/06/2020.

DESIGN AND SETTING

National linked data cohort analysis of Scottish care-homes for older people.

METHODS

data linkage was used to identify outbreaks of COVID-19 in care-homes. Care-home characteristics associated with the presence of an outbreak were examined using logistic regression. Size of outbreaks was modelled using negative binomial regression.

RESULTS

334 (41%) Scottish care-homes for older people experienced an outbreak, with heterogeneity in outbreak size (1-63 cases; median = 6) and duration (1-94 days, median = 31.5 days). Four distinct patterns of outbreak were identified: 'typical' (38% of outbreaks, mean 11.2 cases and 48 days duration), severe (11%, mean 29.7 cases and 60 days), contained (37%, mean 3.5 cases and 13 days) and late-onset (14%, mean 5.4 cases and 17 days). Risk of a COVID-19 outbreak increased with increasing care-home size (for ≥90 beds vs <20, adjusted OR = 55.4, 95% CI 15.0-251.7) and rising community prevalence (OR = 1.2 [1.0-1.4] per 100 cases/100,000 population increase). No routinely available care-home characteristic was associated with outbreak size.

CONCLUSIONS

reducing community prevalence of COVID-19 infection is essential to protect those living in care-homes. More systematic national data collection to understand care-home residents and the homes in which they live is a priority in ensuring we can respond more effectively in future.

COVID-19 as the sole cause of death is uncommon in frail home healthcare individuals: a population-based study

Background

During the first pandemic wave, Sweden experienced a high mortality rate. Home healthcare reflects a group of people especially vulnerable to coronavirus disease 2019 (COVID-19). We aimed to evaluate the pattern of comorbidity and frailty in a group of individuals having fatal outcomes in home healthcare during the COVID-19 pandemic March to September 2020, and to assess the contribution of COVID-19 in the fatal outcomes.

Methods

A cohort of adults with confirmed COVID-19 diagnosis that deceased in home healthcare between March and September 2020 were analysed in a retrospective study comprising home healthcare in 136 facilities in one Swedish county. Main outcome measures were comorbidity and frailty.

Results

One hundred fifty-five individuals (88 women, 67 men) aged 57–106 (median 88) years were included in the analysis. Nine had considerable frailty (ability to perform various activities of daily living but confined to bed or chair on occasion) and the remaining 146 had severe frailty (unable to perform activities of daily living and/or confined to bed or chair; dementia necessitating care). Three or more diagnoses besides COVID-19 were present in 142 individuals and another eight had two diagnoses in addition to COVID-19. In 20 (13%) individuals, COVID-19 was assessed as the principal cause of death, in 100 (64.5%) a contributing cause, and for the remaining 35 (22.5%) death was probably caused by another comorbidity. This seemed to change over the course of the COVID − 19 pandemic, with its contributing role decreasing from the middle of the summer.

Conclusions

Death in home healthcare during the first wave of the pandemic mostly affected individuals with severe frailty and comorbidity at very advanced ages. One fifth of the individuals who died in home health care had another cause than Covid-19.

Trial registration

Clinical Trials.gov NCT04642196 date 24/11/2020.

Excess mortality for men and women above age 70 according to level of care during the first wave of COVID-19 pandemic in Sweden: A population-based study

Background

Both age and comorbidity are established risk factors for death among those infected with COVID-19. Because they often co-exist, it is difficult to assess if age is a risk factor on its own.

Methods

We used administrative register data of the total Swedish population from 01/2015 until 07/2020. We stratified the population aged 70+ into three groups according to level of care (in care homes, with home care, and in independent living). Within these groups, we explored the level of excess mortality in 2020 by estimating expected mortality with Poisson regression and compared it to observed levels. We investigated if excess mortality has been of the same magnitude in the three groups, and if age constitutes a risk factor for death during the pandemic regardless of level of care.

Findings

Individuals living in care homes experienced the highest excess mortality (75- >100% in April, 25–50% in May, 0–25% in June, depending on age). Individuals with home care showed the second highest magnitude (30–60% in April, 15–40% in May, 0–25% in June), while individuals in independent living experienced excess primarily at the highest ages (5–50% in April, 5–50% in May, 0–25% in June). Although mortality rates increased, the age-pattern of mortality during the pandemic resembled the age-pattern observed in previous years.

Interpretation

We found stepwise elevated excess mortality by level of care during the first wave of the COVID-19 pandemic in Sweden, suggesting that level of frailty or comorbidities plays a more important role than age for COVID-19 associated deaths. Part of our findings are likely attributable to differences in exposure to the virus between individuals receiving formal care and those living independently, and not only different case fatality between the groups. Although age is a strong predictor for mortality, the relative effect of age on mortality was no different during the pandemic than before. We believe this is an important contribution to the discussion of the pandemic, its consequences, and which groups need the most protection.

Funding

This study was funded by the Swedish Research Council for Health, Working Life and Welfare (FORTE: grant 2016-07115).