Shielding from covid-19 should be stratified by risk

Effective questionnaire-based prediction models for type 2 diabetes across several ethnicities: a model development and validation study

Background

Type 2 diabetes disproportionately affects individuals of non-White ethnicity through a complex interaction of multiple factors. Therefore, early disease detection and prediction are essential and require tools that can be deployed on a large scale. We aimed to tackle this problem by developing questionnaire-based prediction models for type 2 diabetes prevalence and incidence for multiple ethnicities.

Methods

In this proof of principle analysis, logistic regression models to predict type 2 diabetes prevalence and incidence, using questionnaire-only variables reflecting health state and lifestyle, were trained on the White population of the UK Biobank (n = 472,696 total, aged 37-73 years, data collected 2006-2010) and validated in five other ethnicities (n = 29,811 total) and externally in Lifelines (n = 168,205 total, aged 0-93 years, collected between 2006 and 2013). In total, 631,748 individuals were included for prevalence prediction and 67,083 individuals for the eight-year incidence prediction. Type 2 diabetes prevalence in the UK Biobank ranged between 6% in the White population to 23.3% in the South Asian population, while in Lifelines, the prevalence was 1.9%. Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUC), and a detailed sensitivity analysis was conducted to assess potential clinical utility. We compared the questionnaire-only models to models containing physical measurements and biomarkers as well as to clinical non-laboratory type 2 diabetes risk tools and conducted a reclassification analysis.

Findings

Our algorithms accurately predicted type 2 diabetes prevalence (AUC = 0.901) and eight-year incidence (AUC = 0.873) in the White UK Biobank population. Both models replicated well in the Lifelines external validation, with AUCs of 0.917 and 0.817 for prevalence and incidence, respectively. Both models performed consistently well across different ethnicities, with AUCs of 0.855-0.894 for prevalence and 0.819-0.883 for incidence. These models generally outperformed two clinically validated non-laboratory tools and correctly reclassified >3,000 additional cases. Model performance improved with the addition of blood biomarkers but not with the addition of physical measurements.

Interpretation

Our findings suggest that easy-to-implement, questionnaire-based models could be used to predict prevalent and incident type 2 diabetes with high accuracy across several ethnicities, providing a highly scalable solution for population-wide risk stratification. Future work should determine the effectiveness of these models in identifying undiagnosed type 2 diabetes, validated in cohorts of different populations and ethnic representation.

Funding

University Medical Center Groningen.

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting

BACKGROUND

The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting.

METHODS

Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated.

DISCUSSION

Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

A Qualitative Study on the Experiences of Therapists Delivering the Promoting Activity, Independence and Stability in Early Dementia (PrAISED) Intervention During the COVID-19 Pandemic

BACKGROUND

The Promoting Activity, Independence and Stability in Early Dementia (PrAISED) intervention is a programme of physical activity and exercise designed to maintain participation in activities of daily living, mobility, and quality of life for people living with dementia. During the COVID-19 pandemic first national lockdown in England, the PrAISED physiotherapists, occupational therapists, and rehabilitation support workers adapted to delivering the intervention remotely via telephone or video conferencing.

OBJECTIVE

The aim of this study was to explore therapists' experience of delivering the PrAISED intervention during the COVID-19 pandemic and derive implications for clinical practice.

METHODS

Qualitative semi-structured interviews were conducted with 16 therapists using purposive sampling. Thematic analysis was used to analyze the transcripts.

RESULTS

Therapists reported a change in the relationship between themselves, the person with dementia and the caregiver, with an increased reliance on the caregiver and a loss of autonomy for the person living with dementia. There was concern that this would increase the burden on the caregiver. The therapists reported using creativity to adapt to different modes of delivery. They felt their sessions were mostly focused on providing social and emotional support, and that assessing, progressing, and tailoring the intervention was difficult.

CONCLUSION

It is possible to deliver some elements of a physical intervention using remote delivery, but a dual modal approach including remote and face-to-face delivery would optimize treatment efficacy. Educational support would be required to enable people living with dementia and their caregivers to overcome barriers relating to digital literacy.

Pre-pandemic mental and physical health as predictors of COVID-19 vaccine hesitancy: evidence from a UK-wide cohort study

BACKGROUND

Although several predictors of COVID-19 vaccine hesitancy have been identified, the role of physical health and, particularly, mental health, is poorly understood.

METHODS

We used individual-level data from a pandemic-focused investigation (COVID Survey), a prospective cohort study nested within the UK Understanding Society (Main Survey) project. In the week immediately following the announcement of successful testing of the first efficacious inoculation (Oxford University/AstraZeneca, November/December 2020), data on vaccine intentionality were collected in 12,035 individuals aged 16-95 years. Pre-pandemic, study members had responded to enquiries about diagnoses of mental and physical health, including the completion of the 12-item General Health Questionnaire for symptoms of psychological distress (anxiety and depression). Peri-pandemic, individuals indicated whether they or someone in their household was shielding; that is, people judged by the UK National Health Service as being particularly clinically vulnerable who were therefore requested to remain at home. Intention to take up vaccination for COVID-19 was also self-reported.

RESULTS

In an analytical sample of 11,955 people (6741 women), 15.4% indicated that they were vaccine-hesitant. Relative to their disease-free counterparts, shielding was associated with a 24% lower risk of being hesitant (odds ratio; 95% confidence interval: 0.76; 0.59, 0.96), after adjustment for a range of covariates which included age, education, and ethnicity. Corresponding results for cardiometabolic disease were 22% (0.78; 0.64, 0.95), and for respiratory disease were 26% (0.74; 0.59, 0.93). Having a pre-pandemic diagnosis of anxiety or depression, or a high score on the distress symptom scale, were all unrelated to the willingness to vaccine-hesitancy.

CONCLUSIONS

People with a physical condition were more likely to take up the potential offer of a COVID-19 vaccination. These effects were not apparent for indices of mental health.Key messagesIn understanding predictors of COVID-19 vaccine hesitancy, the role of physical and mental health has not been well-examined despite both groups seemingly experiencing an elevated risk of the disease.In a large UK cohort study, people with a pre-pandemic physical condition were more likely to take up the theoretical offer of vaccination.There were no apparent effects for indices of pre-pandemic mental health.

Exploring the impact of shielding advice on the wellbeing of individuals identified as clinically extremely vulnerable amid the COVID-19 pandemic: a mixed-methods evaluation

BACKGROUND

The national shielding programme was introduced by UK Government at the beginning of the COVID-19 pandemic, with individuals identified as clinically extremely vulnerable (CEV) offered advice and support to stay at home and avoid all non-essential contact. This study aimed to explore the impact and responses of "shielding" on the health and wellbeing of CEV individuals in Southwest England during the first COVID-19 lockdown.

METHODS

A two-stage mixed methods study, including a structured survey (7 August-23 October 2020) and semi-structured telephone interviews (26 August-30 September 2020) with a sample of individuals who had been identified as CEV and advised to "shield" by Bristol, North Somerset & South Gloucestershire (BNSSG) Clinical Commissioning Group (CCG).

RESULTS

The survey was completed by 203 people (57% female, 54% > 69 years, 94% White British, 64% retired) in Southwest England identified as CEV by BNSSG CCG. Thirteen survey respondents participated in follow-up interviews (53% female, 40% > 69 years, 100% White British, 61% retired). Receipt of 'official' communication from NHS England or General Practitioner (GP) was considered by participants as the legitimate start of shielding. 80% of survey responders felt they received all relevant advice needed to shield, yet interviewees criticised the timing of advice and often sought supplementary information. Shielding behaviours were nuanced, adapted to suit personal circumstances, and waned over time. Few interviewees received community support, although food boxes and informal social support were obtained by some. Worrying about COVID-19 was common for survey responders (90%). Since shielding had begun, physical and mental health reportedly worsened for 35% and 42% of survey responders respectively. 21% of survey responders scored ≥ 10 on the PHQ-9 questionnaire indicating possible depression and 15% scored ≥ 10 on the GAD-7 questionnaire indicating possible anxiety.

CONCLUSIONS

This research highlights the difficulties in providing generic messaging that is applicable and appropriate given the diversity of individuals identified as CEV and the importance of sharing tailored and timely advice to inform shielding decisions. Providing messages that reinforce self-determined action and assistance from support services could reduce the negative impact of shielding on mental health and feelings of social isolation.

Evaluation of the shielding initiative in Wales (EVITE Immunity): protocol for a quasiexperimental study

INTRODUCTION

Shielding aimed to protect those predicted to be at highest risk from COVID-19 and was uniquely implemented in the UK during the COVID-19 pandemic. Clinically extremely vulnerable people identified through algorithms and screening of routine National Health Service (NHS) data were individually and strongly advised to stay at home and strictly self-isolate even from others in their household. This study will generate a logic model of the intervention and evaluate the effects and costs of shielding to inform policy development and delivery during future pandemics.

METHODS AND ANALYSIS

This is a quasiexperimental study undertaken in Wales where records for people who were identified for shielding were already anonymously linked into integrated data systems for public health decision-making. We will: interview policy-makers to understand rationale for shielding advice to inform analysis and interpretation of results; use anonymised individual-level data to select people identified for shielding advice in March 2020 and a matched cohort, from routine electronic health data sources, to compare outcomes; survey a stratified random sample of each group about activities and quality of life at 12 months; use routine and newly collected blood data to assess immunity; interview people who were identified for shielding and their carers and NHS staff who delivered healthcare during shielding, to explore compliance and experiences; collect healthcare resource use data to calculate implementation costs and cost-consequences. Our team includes people who were shielding, who used their experience to help design and deliver this study.

ETHICS AND DISSEMINATION

The study has received approval from the Newcastle North Tyneside 2 Research Ethics Committee (IRAS 295050). We will disseminate results directly to UK government policy-makers, publish in peer-reviewed journals, present at scientific and policy conferences and share accessible summaries of results online and through public and patient networks.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis

OBJECTIVE

To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19.

DESIGN

Two stage individual participant data meta-analysis.

SETTING

Secondary and tertiary care.

PARTICIPANTS

46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021.

DATA SOURCES

Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ, and through PROSPERO, reference checking, and expert knowledge.

MODEL SELECTION AND ELIGIBILITY CRITERIA

Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor.

METHODS

Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters.

MAIN OUTCOME MEASURES

30 day mortality or in-hospital mortality.

RESULTS

Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28).

CONCLUSION

The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care.

Citation impact and social media visibility of Great Barrington and John Snow signatories for COVID-19 strategy

OBJECTIVE

The Great Barrington Declaration (GBD) and the John Snow Memorandum (JSM), each signed by numerous scientists, have proposed hotly debated strategies for handling the COVID-19 pandemic. The current analysis aimed to examine whether the prevailing narrative that GBD is a minority view among experts is true.

METHODS

The citation impact and social media presence of the key GBD and JSM signatories was assessed. Citation data were obtained from Scopus using a previously validated composite citation indicator that incorporated also coauthorship and author order and ranking was against all authors in the same Science-Metrix scientific field with at least five full papers. Random samples of scientists from the longer lists of signatories were also assessed. The number of Twitter followers for all key signatories was also tracked.

RESULTS

Among the 47 key GBD signatories, 20, 19 and 21, respectively, were top-cited authors for career impact, recent single-year (2019) impact or either. For comparison, among the 34 key JSM signatories, 11, 14 and 15, respectively, were top cited. Key signatories represented 30 different scientific fields (9 represented in both documents, 17 only in GBD and 4 only in JSM). In a random sample of n=30 scientists among the longer lists of signatories, five in GBD and three in JSM were top cited. By April 2021, only 19/47 key GBD signatories had personal Twitter accounts versus 34/34 of key JSM signatories; 3 key GBD signatories versus 10 key JSM signatories had >50 000 Twitter followers and extraordinary Kardashian K-indices (363-2569). By November 2021, four key GBD signatories versus 13 key JSM signatories had >50 000 Twitter followers.

CONCLUSIONS

Both GBD and JSM include many stellar scientists, but JSM has far more powerful social media presence and this may have shaped the impression that it is the dominant narrative.

'We thank you for your sacrifice': Clinical vulnerability, shielding and biosociality in the UK's Covid-19 response

The UK response to Covid-19 has been unusually complex in its ever-shifting classifications of clinical vulnerability. By May 2020, 2.2 million people had been identified as 'clinically extremely vulnerable' (CEV) and were asked to 'shield' at home for over four months. To adhere to this strict guidance, they were enfolded within the patchy infrastructure of the 'shielding programme'. However, membership of the 'shielded list' has changed-often without warning or explanation-through time and across space. Drawing on policy and evidentiary documents, government speeches, reports, press conferences and media analysis of Covid-19 coverage between March 2020 and April 1, 2021, this paper traces the shifting delineations of clinical vulnerability in the UK response across three lockdowns. It argues that the complexities and confusions generated by the transience of the CEV category have fed into forms of biosociality that have been as much about making practical sense of government guidance as a form of mutual support amid crisis. This uncertainty has not eased as restrictions have been relaxed and vaccines rolled out. Instead, tracing individual immune response has become a burgeoning industry as 'the shielded' navigate the uneasy demands of taking 'personal responsibility' rather than being protected by 'the rules'.

Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world

In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave. For this purpose, we took into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. We estimated the growth of the first and second wave across countries by fitting a logistic model to daily-reported case numbers, up to the first and second epidemic peaks. We estimated the basic and effective (second wave) reproduction numbers across countries. Next, we used a random forest algorithm to study the association between the growth rate of the second wave and NPIs as well as pre-existing country-specific characteristics. Lastly, we compared the growth rate of the first and second waves of COVID-19. The top three factors associated with the growth of the second wave were body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times, and restrictions on gatherings of 10 people or less. Artificial intelligence techniques can help scholars as well as decision and policy-makers estimate the effectiveness of public health policies, and implement "smart" interventions, which are as efficacious as stringent ones.

'What is the risk to me from COVID-19?': Public involvement in providing mortality risk information for people with 'high-risk' conditions for COVID-19 (OurRisk.CoV)

Patients and public have sought mortality risk information throughout the pandemic, but their needs may not be served by current risk prediction tools. Our mixed methods study involved: (1) systematic review of published risk tools for prognosis, (2) provision and patient testing of new mortality risk estimates for people with high-risk conditions and (3) iterative patient and public involvement and engagement with qualitative analysis. Only one of 53 (2%) previously published risk tools involved patients or the public, while 11/53 (21%) had publicly accessible portals, but all for use by clinicians and researchers.Among people with a wide range of underlying conditions, there has been sustained interest and engagement in accessible and tailored, pre- and postpandemic mortality information. Informed by patient feedback, we provide such information in 'five clicks' (https://covid19-phenomics.org/OurRiskCoV.html), as context for decision making and discussions with health professionals and family members. Further development requires curation and regular updating of NHS data and wider patient and public engagement.

Changes in Sexual Desire and Behaviors among UK Young Adults During Social Lockdown Due to COVID-19

This study examined self-reported changes in young adults' sexual desire and behaviors during the most significant social restrictions imposed to deal with COVID-19. Drawing on a survey of 565 British adults aged 18-32 collected at the peak of social lockdown restrictions, we document an overall decrease in sexual behaviors consistent with abiding by social restrictions. We found that the levels of sexual desire reported by women (but not men) decreased compared with reports of pre-lockdown levels. Participants in serious relationships reported more increases in sexual activity than people who were single or dating casually, and there were significant differences according to gender and sexual orientation. The perceived impact of subjective wellbeing of people with high sociosexuality scores was disproportionately associated with social lockdown but there was no effect for general health. Thus, the impact on sexuality and general wellbeing should be considered by policymakers when considering future social restrictions related to COVID-19 or other public health emergencies.

Shielding, hospital admission and mortality among 1216 people with total laryngectomy in the UK during the COVID-19 pandemic: A cross-sectional survey from the first national lockdown

BACKGROUND

People with a total laryngectomy (PTL) rely on a permanent opening in their neck (stoma) to breathe. This altered anatomy may increase susceptibility to contracting and transmitting SARS-CoV-2.

AIMS

To report on (1) the frequency and characteristics of PTL who tested positive for COVID-19, (2) the receipt of advice regarding shielding and patient self-reports of shielding, (3) hospital admissions and length of stay, and (4) mortality rates in this group during the first UK national lockdown.

METHODS & PROCEDURES

This is a cross-sectional survey and case note review. National Health Service (NHS) centres providing care to PTL were invited to participate via the Royal College of Speech and Language Therapists' (RCSLT) Head & Neck Clinical Excellence Networks and through social media. PTL were reviewed by their speech and language therapist either in person or via telehealth between 30 March and 30 September 2020. Data were collected within the time frame covered by the Control of Patient Information (COPI) notice issued for COVID-19 and included information on COVID-19 testing, shielding, hospital admissions, length of stay and deaths. Information was submitted to the lead NHS site using a custom designed data-capture worksheet. Analysis was performed using descriptive statistics, including proportions and frequency counts. Pearson's Chi squared tests were used to compare categorical data using a 5% significance level.

OUTCOMES & RESULTS

Data were obtained from 1216 PTL from 26 centres across the UK. A total of 81% were male; mean age was 70 years (28-97 years). Of the total group, 12% received a COVID-19 test. A total of 24 (2% of total sample) tested positive for COVID-19. Almost one-third of PTL (32%) received a government letter or were advised to shield by a healthcare professional. During the data collection time frame, 12% had a hospital admission (n = 151) with a median length of stay of 1 day (1-133 days), interquartile range (IQR) = 17 days. A total of 20 of these admissions (13%) had tested positive for COVID-19 with a median length of stay of 26 days, IQR = 49 days. The overall mortality was 4% (41 patients), with eight deaths occurring within 28 days of testing positive for COVID-19.

CONCLUSIONS & IMPLICATIONS

This study highlighted the lack of routine national data for neck-breathers with which to compare the current findings. Greater testing in the community is necessary to understand the prevalence of COVID-19 in PTL and if this group is indeed more susceptible. The potential for nasopharyngeal and tracheal aspirates to show differing results when testing for COVID-19 in neck-breathers requires further investigation.

WHAT THIS PAPER ADDS

What is already known on the subject? People with total laryngectomy (PTL) have an altered anatomy for breathing and speaking. The presence of a neck stoma poses an additional virus entry point aside from the nose, mouth and conjunctiva. This could increase the susceptibility to COVID-19 for PTL. What this paper adds? This is the first national audit to provide data on shielding, hospital admissions and mortality for patients with total laryngectomy in the UK over the pandemic. The overall mortality in PTL over the first lockdown did not appear to be higher than the "best case" estimates from previous years. However, one in three PTL who acquired COVID-19 and were admitted to hospital, died within 28 days of testing positive. These findings are relevant to the current care and management of PTL over the pandemic but also highlights important knowledge gaps. What are the potential or actual clinical implications of this work? This study highlights gaps in the collection of baseline information on hospital admissions, length of stay and mortality for people with laryngectomy in the UK, restricting comparisons between the current data and historical data. The need for further research on whether neck-breathers should be tested via both nasopharyngeal and tracheal aspirates is important not just currently, but also in case of any future respiratory epidemics.

Japan's voluntary lockdown: further evidence based on age-specific mobile location data

Changes in people's behavior during the COVID-19 pandemic can be regarded as the result of two types of effects: the "intervention effect" (changes resulting from government orders for people to change their behavior) and the "information effect" (voluntary changes in people's behavior based on information about the pandemic). Using age-specific mobile location data, we examine how the intervention and information effects differ across age groups. Our main findings are as follows. First, the age profile of the intervention effect shows that the degree to which people refrained from going out was smaller for older age groups, who are at a higher risk of serious illness and death, than for younger age groups. Second, the age profile of the information effect shows that the degree to which people stayed at home tended to increase with age for weekends and holidays. Thus, while Acemoglu et al. (2020) proposed targeted lockdowns requiring stricter lockdown policies for the oldest group in order to protect those at a high risk of serious illness and death, our findings suggest that Japan's government intervention had a very different effect in that it primarily reduced outings by the young, and what led to the quarantining of older groups at higher risk instead was people's voluntary response to information about the pandemic. Third, the information effect has been on a downward trend since the summer of 2020. It is relatively more pronounced among the young, so that the age profile of the information effect remains upward sloping.

The impact of primary care supported shielding on the risk of mortality in people vulnerable to COVID-19: English sentinel network matched cohort study

Objectives

To mitigate risk of mortality from coronavirus 2019 infection (COVID-19), the UK government recommended ‘shielding’ of vulnerable people through self-isolation for 12 weeks.

Methods

A retrospective cohort study using a nationally representative English primary care database comparing people aged >= 40 years who were recorded as being advised to shield using a fixed ratio of 1:1, matching to people with the same diagnoses not advised to shield (n = 77,360 per group). Time-to-death was compared using Cox regression, reporting the hazard ratio (HR) of mortality between groups. A sensitivity analysis compared exact matched cohorts (n = 24,752 shielded, n = 61,566 exact matches).

Results

We found a time-varying HR of mortality between groups. In the first 21 days, the mortality risk in people shielding was half those not (HR = 0.50, 95%CI:0.41–0.59. p < 0.0001). Over the remaining nine weeks, mortality risk was 54% higher in the shielded group (HR=1.54, 95%CI:1.41–1.70, p < 0.0001). Beyond the shielding period, mortality risk was over two-and-a-half times higher in the shielded group (HR=2.61, 95%CI:2.38–2.87, p < 0.0001).

Conclusions

Shielding halved the risk of mortality for 21 days. Mortality risk became higher across the remainder of the shielding period, rising to two-and-a-half times greater post-shielding. Shielding may be beneficial in the next wave of COVID-19.

Pre-pandemic mental and physical health as predictors of COVID-19 vaccine hesitancy: evidence from a UK-wide cohort study

IMPORTANCE

Although several predictors of COVID-19 vaccine hesitancy have been identified, the role of physical health has not been well-examined, and the association with mental health is unknown.

OBJECTIVE

To examine the association of pre-pandemic mental health, physical health, and shielding with vaccine hesitancy after the announcement of the successful testing of the Oxford University/AstraZeneca vaccine.

DESIGN SETTING AND PARTICIPANTS

We used individual-level data from a pandemic-focused investigation (COVID Survey), a prospective cohort study nested within the UK Understanding Society (Main Survey) project. In the week immediately following the announcement of successful testing of the first efficacious inoculation (November/December 2020), data on vaccine intentionality were collected in 12,035 individuals aged 16-95 years. Pre-pandemic, study members had responded to enquiries about diagnoses of mental and physical health, completed the 12-item General Health Questionnaire for symptoms of psychological distress (anxiety and depression), and indicated whether they or someone in their household was shielding.

MAIN OUTCOME MEASURES

Self-reported intention to take up a vaccination for COVID-19. To summarise our results, we computed odds ratios with accompanying 95% confidence intervals for indices of health and shielding adjusted for selected covariates.

RESULTS

In an analytical sample of 11,955 people (6741 women), 15.4% indicated that they were vaccine hesitant. Relative to their disease-free counterparts, shielding was associated with a 24% lower risk of being hesitant (odds ratio; 95% confidence interval: 0.76; 0.59, 0.96), after adjustment for a range of covariates which included age, education, and ethnicity. Corresponding results for cardiometabolic disease were 22% (0.78; 0.64, 0.95), and for respiratory disease were 26% (0.74; 0.59, 0.93). Having a pre-pandemic diagnosis of anxiety or depression, or a high score on the distress symptom scale, were all unrelated to the willingness to take up a vaccine.

CONCLUSIONS AND RELEVANCE

People who have been prioritised for COVID-19 vaccination owing to a physical condition are more likely to take it up. These effects were not apparent for indices of mental health.

Second versus first wave of COVID-19 deaths: Shifts in age distribution and in nursing home fatalities

OBJECTIVE

To examine whether the age distribution of COVID-19 deaths and the share of deaths in nursing homes changed in the second versus the first pandemic wave.

ELIGIBLE DATA

We considered all countries that had at least 4000 COVID-19 deaths occurring as of January 14, 2021, at least 200 COVID-19 deaths occurring in each of the two epidemic wave periods; and which had sufficiently detailed information available on the age distribution of these deaths. We also considered countries with data available on COVID-19 deaths of nursing home residents for the two waves.

MAIN OUTCOME MEASURES

Change in the second wave versus the first wave in the proportion of COVID-19 deaths occurring in people <50 years ("young deaths") among all COVID-19 deaths and among COVID-19 deaths in people <70 years old; and change in the proportion of COVID-19 deaths in nursing home residents among all COVID-19 deaths.

RESULTS

Data on age distribution were available for 14 eligible countries. Individuals <50 years old had small absolute difference in their share of the total COVID-19 deaths in the two waves across 13 high-income countries (absolute differences 0.0-0.4%). Their proportion was higher in Ukraine, but it decreased markedly in the second wave. The proportion of young deaths was lower in the second versus the first wave (summary prevalence ratio 0.81, 95% CI 0.71-0.92) with large between-country heterogeneity. The proportion of young deaths among deaths <70 years did not differ significantly across the two waves (summary prevalence ratio 0.96, 95% CI 0.86-1.06). Eligible data on nursing home COVID-19 deaths were available for 11 countries. The share of COVID-19 deaths that were accounted by nursing home residents decreased in the second wave significantly and substantially in 8 countries (prevalence ratio estimates: 0.36 to 0.78), remained the same in Denmark and Norway and markedly increased in Australia.

CONCLUSIONS

In the examined countries, age distribution of COVID-19 deaths has been fairly similar in the second versus the first wave, but the contribution of COVID-19 deaths in nursing home residents to total fatalities has decreased in most countries in the second wave.

Assessing relative COVID-19 mortality: a Swiss population-based study

OBJECTIVE

Severity of the COVID-19 has been previously reported in terms of absolute mortality in SARS-CoV-2 positive cohorts. An assessment of mortality relative to mortality in the general population is presented.

DESIGN

Retrospective population-based study.

SETTING

Individual information on symptomatic confirmed SARS-CoV-2 patients and subsequent deaths from any cause were compared with the all-cause mortality in the Swiss population of 2018. Starting 23 February 2020, mortality in COVID-19 patients was monitored for 80 days and compared with the population mortality observed in the same time of year starting 23 February 2018.

PARTICIPANTS

5 102 300 inhabitants of Switzerland aged 35-95 without COVID-19 (general population in spring 2018) and 20 769 persons tested positively for COVID-19 during the first wave in spring 2020.

MEASUREMENTS

Sex-specific and age-specific mortality rates were estimated using Cox proportional hazards models. Absolute probabilities of death were predicted and risk was assessed in terms of relative mortality by taking the ratio between the sex-specific and age-specific absolute mortality in COVID-19 patients and the corresponding mortality in the 2018 general population.

RESULTS

Absolute mortalities increased with age and were higher for males compared with females, both in the general population and in positively tested persons. A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups at least eightfold. The highest relative mortality risks were observed among males and younger patients. Male COVID-19 patients exceeded the population hazard for males (HR 1.21, 95% CI 1.02 to 1.44). An additional year of age increased the population hazard in COVID-19 patients only marginally (HR 1.00, 95% CI 1.00 to 1.01).

CONCLUSIONS

Healthcare professionals, decision-makers and societies are provided with an additional population-adjusted assessment of COVID-19 mortality risk. In combination with absolute measures of risk, the relative risks presented here help to develop a more comprehensive understanding of the actual impact of COVID-19.

Precision shielding for COVID-19: metrics of assessment and feasibility of deployment

The ability to preferentially protect high-risk groups in COVID-19 is hotly debated. Here, the aim is to present simple metrics of such precision shielding of people at high risk of death after infection by SARS-CoV-2; demonstrate how they can estimated; and examine whether precision shielding was successfully achieved in the first COVID-19 wave. The shielding ratio, S, is defined as the ratio of prevalence of infection among people in a high-risk group versus among people in a low-risk group. The contrasted risk groups examined here are according to age (≥70 vs <70 years), and institutionalised (nursing home) setting. For age-related precision shielding, data were used from large seroprevalence studies with separate prevalence data for elderly versus non-elderly and with at least 1000 assessed people≥70 years old. For setting-related precision shielding, data were analysed from 10 countries where information was available on numbers of nursing home residents, proportion of nursing home residents among COVID-19 deaths and overall population infection fatality rate (IFR). Across 17 seroprevalence studies, the shielding ratio S for elderly versus non-elderly varied between 0.4 (substantial shielding) and 1.6 (substantial inverse protection, that is, low-risk people being protected more than high-risk people). Five studies in the USA all yielded S=0.4-0.8, consistent with some shielding being achieved, while two studies in China yielded S=1.5-1.6, consistent with inverse protection. Assuming 25% IFR among nursing home residents, S values for nursing home residents ranged from 0.07 to 3.1. The best shielding was seen in South Korea (S=0.07) and modest shielding was achieved in Israel, Slovenia, Germany and Denmark. No shielding was achieved in Hungary and Sweden. In Belgium (S=1.9), the UK (S=2.2) and Spain (S=3.1), nursing home residents were far more frequently infected than the rest of the population. In conclusion, the experience from the first wave of COVID-19 suggests that different locations and settings varied markedly in the extent to which they protected high-risk groups. Both effective precision shielding and detrimental inverse protection can happen in real-life circumstances. COVID-19 interventions should seek to achieve maximal precision shielding.

Predictions of COVID-19 dynamics in the UK: Short-term forecasting and analysis of potential exit strategies

Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a "stay at home" order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. The model captures a range of age-dependent heterogeneities, reduced transmission from asymptomatic infections and produces a good fit to the key epidemic features over time. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020 on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. We find that significant relaxation of social distancing measures from 7th May onwards can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Our work confirms the effectiveness of stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. It also provides strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units.

COVID-19 zugzwang: Potential public health moves towards population (herd) immunity

COVID-19 is pandemic, and likely to become endemic, possibly returning with greater virulence. Outlining potential public health actions, including hygiene measures, social distancing and face masks, and realistic future advances, this paper focuses on the consequences of taking no public health action; the role of natural changes such as weather; the adverse public health consequences of lockdowns; testing for surveillance and research purposes; testing to identify cases and contacts, including the role of antibody tests; the public health value of treatments; mobilising people who have recovered; population (a synonym for herd) immunity through vaccination and through natural infection; involving the entire population; and the need for public debate. Until there is a vaccine, population immunity is going to occur only from infection. Allowing infection in those at very low risk while making it safer for them and wider society needs consideration but is currently taboo. About 40–50% population immunity is sufficient to suppress an infection with a reproduction number of about 1 or slightly more. Importantly, in children and young people COVID-19 is currently rarely fatal, roughly comparable with influenza. The balance between the damage caused by COVID-19 and that caused by lockdowns needs quantifying. Public debate, including on population immunity, informed by epidemiological data, is now urgent.

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The long-term solution to the COVID-19 pandemic is population immunity through natural infection or vaccination.

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40-50% population immunity is sufficient to suppress and eliminate this pandemic.

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New vaccines may not work well in the older age groups and those with underlying conditions and may not be safer than the infection for children and youth.

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Immunity is currently being acquired by infection and we need safer strategies for managing this.

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Open, honest, factual and sensitively conducted public dialogue is now urgent.

Individual and community-level risk for COVID-19 mortality in the United States

Reducing COVID-19 burden for populations will require equitable and effective risk-based allocations of scarce preventive resources, including vaccinations¹. To aid in this effort, we developed a general population risk calculator for COVID-19 mortality based on various sociodemographic factors and pre-existing conditions for the US population, combining information from the UK-based OpenSAFELY study with mortality rates by age and ethnicity across US states. We tailored the tool to produce absolute risk estimates in future time frames by incorporating information on pandemic dynamics at the community level. We applied the model to data on risk factor distribution from a variety of sources to project risk for the general adult population across 477 US cities and for the Medicare population aged 65 years and older across 3,113 US counties, respectively. Validation analyses using 54,444 deaths from 7 June to 1 October 2020 show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (for example 4.3%) that might experience a disproportionately large number of deaths (for example 48.7%), but there is wide variation in risk across communities. We provide a web-based risk calculator and interactive maps for viewing community-level risks.

Swedish policy analysis for Covid-19

INTRODUCTION

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has challenged health care systems and put societies to the test in the world beyond expectations.

OBJECTIVE

Our aim is to describe and analyze the Swedish approach in combating the pandemic.

METHODS

We present and discuss data collated from various sources - published scientific studies, pre-print material, agency reports, media communication, public surveys, etc. - with specific focus on the approach itself, Covid-19 trends, healthcare system response, policy and measures overview, and implications.

RESULTS

The main intervention to manage the curve has been the general recommendations to adhere to good hand hygiene, beware of physical distance to others, to refrain from large gatherings and restrain from non-essential travel. Persons with suspected Covid-19 infection were recommended to stay at home and avoid social contacts. Additionally, visits to the elderly care homes and meetings with more than 50 people were forbidden. As a result, the healthcare system in the country has so far, never been overwhelmed. However, the relatively high mortality among the elderly, together with the vulnerability of some migrants, points out the drawbacks.

CONCLUSIONS

Many countries have both marvelled and criticized the Swedish strategy that is formed in a close partnership between the government and the society based on a mutual trust giving the responsibility to individuals. It already highlights how much can be achieved with voluntary measures (recommendations) - something that was noticed and proposed as a future model by the World Health Organization.

Incidence of COVID-19 in patients with rheumatic disease: is prior health education more important than shielding advice during the pandemic?

The COVID-19 pandemic has led to major changes in clinical practice on a global scale in order to protect patients. This includes the identification of vulnerable patients who should "shield" in order to reduce the likelihood of contracting SARS-CoV2. We used national specialty guidance and an adapted screening tool to risk stratify patients identified from our prescribing and monitoring databases, and identify those needing to shield (score ≥ 3) using information from departmental letters, online general practice records and recent laboratory investigations. We collated underlying rheumatological conditions and risk factors. Two months into the shielding process, we examined the COVID-19 status of these patients using hospital laboratory records and compared to population level data. Of 887 patients assessed, 248 (28%) scored ≥ 3 and were sent a standard shielding letter. The most common risk factor in the shielding letter group was age ≥ 70 years and/or presence of a listed co-morbidity (199 patients). The most common rheumatology conditions were rheumatoid arthritis (69.4%), polymyalgia rheumatica (8.5%) and giant cell arteritis (8.5%). Coronavirus incidence rates were similar in the shielding letter group (0.403%) and in the UK population (0.397%). However, we found a trend towards lower incidence (0.113%) in our whole cohort (RR 0.28, 95%CI 0.04-2.01 for the whole cohort compared to UK population). The trend towards lower incidence in this cohort could be because of prior education regarding general infection risk and response to public health messages. While risk stratification and shielding could be effective, prior education regarding general infection risk and public health messages to enhance health protection behaviours during a pandemic may have equal or more important roles. Key Points • Patients on treatment for rheumatic disorders showed a trend for lower incidence of COVID-19 transmission irrespective of shielding letter status • This could potentially be because of prior education regarding infection risk received when starting on disease-modifying medication • Health education influencing health protection behaviours may be of equal or more importance than shielding information in reducing transmission of SARS-CoV-2.

Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study

OBJECTIVE

To derive and validate a risk prediction algorithm to estimate hospital admission and mortality outcomes from coronavirus disease 2019 (covid-19) in adults.

DESIGN

Population based cohort study.

SETTING AND PARTICIPANTS

QResearch database, comprising 1205 general practices in England with linkage to covid-19 test results, Hospital Episode Statistics, and death registry data. 6.08 million adults aged 19-100 years were included in the derivation dataset and 2.17 million in the validation dataset. The derivation and first validation cohort period was 24 January 2020 to 30 April 2020. The second temporal validation cohort covered the period 1 May 2020 to 30 June 2020.

MAIN OUTCOME MEASURES

The primary outcome was time to death from covid-19, defined as death due to confirmed or suspected covid-19 as per the death certification or death occurring in a person with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the period 24 January to 30 April 2020. The secondary outcome was time to hospital admission with confirmed SARS-CoV-2 infection. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance, including measures of discrimination and calibration, was evaluated in each validation time period.

RESULTS

4384 deaths from covid-19 occurred in the derivation cohort during follow-up and 1722 in the first validation cohort period and 621 in the second validation cohort period. The final risk algorithms included age, ethnicity, deprivation, body mass index, and a range of comorbidities. The algorithm had good calibration in the first validation cohort. For deaths from covid-19 in men, it explained 73.1% (95% confidence interval 71.9% to 74.3%) of the variation in time to death (R²); the D statistic was 3.37 (95% confidence interval 3.27 to 3.47), and Harrell's C was 0.928 (0.919 to 0.938). Similar results were obtained for women, for both outcomes, and in both time periods. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths within 97 days was 75.7%. People in the top 20% of predicted risk of death accounted for 94% of all deaths from covid-19.

CONCLUSION

The QCOVID population based risk algorithm performed well, showing very high levels of discrimination for deaths and hospital admissions due to covid-19. The absolute risks presented, however, will change over time in line with the prevailing SARS-C0V-2 infection rate and the extent of social distancing measures in place, so they should be interpreted with caution. The model can be recalibrated for different time periods, however, and has the potential to be dynamically updated as the pandemic evolves.

Changes in Emergency General Surgery During Covid-19 in Scotland: A Prospective Cohort Study

Introduction

Covid-19 has had a significant impact on all aspects of health care. We aimed to characterise the trends in emergency general surgery at a district general hospital in Scotland.

Methods

A prospective cohort study was performed from 23/03/20 to 07/05/20. All emergency general surgery patients were included. Demographics, diagnosis and management were recorded along with Covid-19 testing and results. Thirty-day mortality and readmission rates were also noted. Similar data were collected on patients admitted during the same period in 2019 to allow for comparison.

Results

A total of 294 patients were included. There was a 58.3 per cent reduction in admissions when comparing 2020 with 2019 (85 vs 209); however, there was no difference in age (53.2 vs 57.2 years, p = 0.169) or length of stay (4.8 vs 3.7 days, p = 0.133). During 2020, the diagnosis of appendicitis increased (4.3 vs 18.8 per cent, p = < 0.05) as did severity (0 per cent > grade 1 vs 58.3 per cent > grade 1, p = < 0.05). The proportion of patients undergoing surgery increased (19.1 vs 42.3 per cent, p = < 0.05) as did the mean operating time (102.4 vs 145.7 min, p = < 0.05). Surgery was performed in 1 confirmed and 1 suspected Covid-19 patient. The latter died within 30 days. There were no 30-day readmissions with Covid-19 symptoms.

Conclusion

Covid-19 has significantly impacted the number of admissions to emergency general surgery. However, emergency operating continues to be needed at pre-Covid-19 levels and as such provisions need to be made to facilitate this.

Can Air-Conditioning Systems Contribute to the Spread of SARS/MERS/COVID-19 Infection? Insights from a Rapid Review of the Literature

The airborne transmission of SARS-CoV-2 is still debated. The aim of this rapid review is to evaluate the COVID-19 risk associated with the presence of air-conditioning systems. Original studies (both observational and experimental researches) written in English and with no limit on time, on the airborne transmission of SARS-CoV, MERS-CoV, and SARS-CoV-2 coronaviruses that were associated with outbreaks, were included. Searches were made on PubMed/MEDLINE, PubMed Central (PMC), Google Scholar databases, and medRxiv. A snowball strategy was adopted to extend the search. Fourteen studies reporting outbreaks of coronavirus infection associated with the air-conditioning systems were included. All studies were carried out in the Far East. In six out the seven studies on SARS, the role of Heating, Ventilation, and Air Conditioning (HVAC) in the outbreak was indirectly proven by the spatial and temporal pattern of cases, or by airflow-dynamics models. In one report on MERS, the contamination of HVAC by viral particles was demonstrated. In four out of the six studies on SARS-CoV-2, the diffusion of viral particles through HVAC was suspected or supported by computer simulation. In conclusion, there is sufficient evidence of the airborne transmission of coronaviruses in previous Asian outbreaks, and this has been taken into account in the guidelines released by organizations and international agencies for controlling the spread of SARS-CoV-2 in indoor environments. However, the technological differences in HVAC systems prevent the generalization of the results on a worldwide basis. The few COVID-19 investigations available do not provide sufficient evidence that the SARS-CoV-2 virus can be transmitted by HVAC systems.

Risk to health from COVID-19 for anaesthetists and intensivists - a narrative review

Healthcare workers are at an increased risk of infection, harm and death from COVID‐19. Close and prolonged exposure to individuals infectious with SARS‐CoV‐2 leads to infection. A person’s individual characteristics (age, sex, ethnicity and comorbidities) then influence the subsequent risk of COVID‐19 leading to hospitalisation, critical care admission or death. While relative risk is often reported as a measure of individual danger, absolute risk is more important and dynamic, particularly in the healthcare setting. Individual risk interacts with exposure and environmental risk‐factors, and the extent of mitigation to determine overall risk. Hospitals are a unique environment in which there is a significantly increased risk of infection for all healthcare workers. Anaesthetists and intensivists particularly are at high risk of exposure to SARS‐CoV‐2 infected patients due to their working environments and exposure to certain patient groups. However, the available evidence suggests that the risk for this group of individuals is not currently increased. This review examines factors associated with increased risk of infection with SARS‐CoV‐2, increasing severity of COVID‐19 and death. A risk tool is proposed that includes personal, environmental and mitigating factors, and enables an individualised dynamic ‘point‐of‐time’ risk assessment.