ABSTRACT
BackgroundCoronavirus disease 2019 (COVID-19) is associated with significant mortality and morbidity in care homes. Novel or repurposed antiviral drugs may reduce infection and disease severity through reducing viral replication and inflammation. ObjectiveTo compare the safety and efficacy of antiviral agents (ciclesonide, niclosamide) for preventing SARS-CoV-2 infection and COVID-19 severity in care home residents. DesignCluster-randomised open-label blinded endpoint platform clinical trial testing antiviral agents in a post-exposure prophylaxis paradigm. SettingCare homes across all four United Kingdom member countries. ParticipantsCare home residents 65 years of age or older. InterventionsCare homes were to be allocated at random by computer to 42 days of antiviral agent plus standard care versus standard of care and followed for 60 days after randomisation. Main outcome measuresThe primary four-level ordered categorical outcome with participants classified according to the most serious of all-cause mortality, all-cause hospitalisation, SARS-CoV-2 infection and no infection. Analysis using ordinal logistic regression was by intention to treat. Other outcomes included the components of the primary outcome and transmission. ResultsDelays in contracting between NIHR and the manufacturers of potential antiviral agents significantly delayed any potential start date. Having set up the trial (protocol, approvals, insurance, website, database, routine data algorithms, training materials), the trial was stopped in September 2021 prior to contracting of care homes and general practitioners in view of the success of vaccination in care homes with significantly reduced infections, hospitalisations and deaths. As a result, the sample size target (based on COVID-19 rates and deaths occurring in February-June 2020) became unfeasible. LimitationsCare home residents were not approached about the trial and so were not consented and did not receive treatment. Hence, the feasibility of screening, consent, treatment and data acquisition, and potential benefit of post exposure prophylaxis were never tested. Further, contracting between the University of Nottingham and the PIs, GPs and care homes was not completed, so the feasibility of contracting with all the different groups at the scale needed was not tested. ConclusionsThe role of post exposure prophylaxis of COVID-19 in care home residents was not tested because of changes in COVID-19 incidence, prevalence and virulence as a consequence of the vaccination programme that rendered the study unfeasible. Significant progress was made in describing and developing the infrastructure necessary for a large scale Clinical Trial of Investigational Medicinal Products in care homes in all four UK nations. Future workThe role of post-exposure prophylaxis of COVID-19 in care home residents remains to be defined. Significant logistical barriers to conducting research in care homes during a pandemic need to be removed before such studies are possible in the required short timescale.
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IntroductionCOVID-19 deaths are commoner among care-home residents, but the mortality burden has not been quantified. MethodsCare-home residency was identified via a national primary care registration database linked to national mortality data. Life expectancy was estimated using Makeham-Gompertz models, to (i) describe yearly life expectancy from Nov 2015 to Oct 2020 (ii) compare life expectancy (during 2016-2018) between care-home residents and the wider Scottish population and (iii) apply care-home life expectancy estimates to COVID-19 death counts to estimate years of life lost (YLL). ResultsAmong 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. Life expectancy was lowest in 2019/20. Age-sex specific life expectancy in 2016-2018 in care-home residents was lower than in the Scottish population (10 and 2.5 years in those aged 70 and 90 respectively). Rather than using national life tables, applying care-home specific life expectancies to COVID-19 deaths yields, mean YLLs for care-home residents were 2.6 and 2.2 for women and men respectively, with total care-home resident YLLs of 3,560 years in women and 2,046 years in men. In people aged over-70, 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. ConclusionPrioritising care-home residents for vaccination is justified not only in terms of total deaths, but also in terms of years of life lost. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed to 1st December 2020, with the terms ("nursing home" OR "care-home" OR "long-term care" OR "residential care") AND ("mortality" OR "life expectancy" OR "length of stay"). We also searched for studies specific to the impact of the COVID-19 pandemic on those living in care-homes. We restricted our search to publications in English. Usual care-home life expectancy, in a UK context, has not previously been defined. One systematic review of length of stay was identified, which found significant heterogeneity in factors and associations. The impact of COVID-19 on excess mortality among care-home residents was noted, but the impact on life expectancy was not reported. Studies evaluating life expectancy among older people in the COVID-19 pandemic have not taken account of residency in their estimates. Added value of this studyUsing Scottish national representative linked data we describe the usual life expectancy of older adults (aged [≥]70 years) living in care-homes, compared to older people living elsewhere. Deaths among care-home residents account for a considerable proportion of all mortality in older adults, around 19% for men and 30% for women. Life expectancy in care-home residents during the pandemic fell by almost 6 months, from 2.7 to 2.3 years in men and 2.1 to 1.8 years in women. In total, over 5,600 Years of Life were Lost (YLL) by care-home residents in Scotland who died with COVID-19. Around half of COVID-19 deaths and a quarter of YLL in those aged 70 years and over occurred among care-home residents. During the COVID-19 pandemic a smaller proportion of deaths among care-home residents occurred in hospitals. Implications of all the available evidencePrioritising the 5% of older adults who are care-home residents for vaccination against COVID-19 is justified both in terms of total deaths and total years of life lost. Individual and societal planning for care needs in older age relies on understanding usual care-home life expectancy and patterns of mortality. Understanding life expectancy may help clinicians, residents and their families make decisions about their health care, facilitating more informed discussions around their priorities and wishes. Population-wide estimates of YLL and burden of disease should take account of residency status, given the significant differences between life expectancy of those living in care-homes from their peers in other settings.
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BackgroundSevere disease directly associated with SARS-CoV-2 infection in children is rare. However, the indirect consequences of the COVID-19 pandemic on paediatric health have not been fully quantified. We examined paediatric health-care utilisation, incidence of severe disease, and mortality during the lockdown period in Scotland. MethodsThis national retrospective cohort study examined national data for emergency childhood primary and secondary care utilisation following national lockdown on March 23, 2020. To determine whether social distancing measures and caregiver behavioural changes were associated with delayed care-seeking and increased disease severity on presentation, unplanned, emergency admissions requiring invasive mechanical ventilation for the two national Paediatric Intensive Care Units (PICUs) were analysed. PICU admissions were grouped by diagnostic category, and disease severity on presentation calculated. National statutory death records were consulted to establish childhood mortality rates and causes of death. For all observations, the lockdown period was compared to equivalent dates in 2016-2019. FindingsWe identified 273,455 unscheduled primary care attendances; 462,437 emergency department attendances; 54,076 emergency hospital admissions; 413 PICU emergency admissions; and 415 deaths during the lockdown study period and equivalent dates in previous years. The rates of emergency presentations to primary and secondary care fell during lockdown in comparison to previous years. Emergency PICU admissions for children requiring invasive mechanical ventilation also fell, with an odds ratio of 0{middle dot}52 for chance of admission during lockdown (95% CI 0{middle dot}37-0{middle dot}73, p < 0{middle dot}001). Clinical severity scores did not suggest children were presenting with more advanced disease. The greatest reduction in PICU admissions was for diseases of the respiratory system; those for injury, poisoning or other external causes were equivalent to previous years. Mortality during lockdown did not change significantly compared to 2016-2019. InterpretationNational lockdown led a reduction in paediatric emergency care utilisation, without associated evidence of severe harm. FundingNone Research in contextO_ST_ABSEvidence before this studyC_ST_ABSData on the indirect effects of the COVID-19 pandemic on children at a population level are limited. We searched PubMed and medRxiv on October 13, 2020, for studies published from Jan 1, 2020 examining the indirect effects of non-pharmaceutical interventions (NPIs), and associated changes in caregiver health-care seeking behaviour, on the risk of severe paediatric disease and death. We used the search terms COVID-19, SARS-CoV-2, non-pharmaceutical interventions, indirect, and children, as well as manually searching references in other relevant papers. Terms were searched individually and in combination as necessary, with no language restrictions. We identified one study that modelled the indirect effects of the COVID-19 pandemic on child deaths in low- and middle-income countries. Other studies analysed in isolation the effects of NPIs and other behavioural changes on emergency department attendances, hospital admission rates, paediatric intensive care unit (PICU) admission rates, or the incidence of specific presentations, such as asthma exacerbations. Some case series described delayed care-seeking for children with non-SARS-CoV-2 disease. We did not identify any national studies examining the indirect effects of the COVID-19 pandemic on the incidence of severe paediatric disease and mortality. Added value of this studyThis national study quantified the changes following national lockdown in Scotland on March 23, 2020. We examined data for unscheduled primary care and emergency department attendances, emergency hospital admissions, emergency paediatric intensive care unit (PICU) admissions requiring invasive mechanical ventilation, and paediatric mortality. Rates were compared with previous years. We found a reduction in paediatric emergency care utilisation rates associated with national lockdown. This reduction is likely to be due to a combination of changes in health care seeking behavior, and a fall in overall burden of paediatric infectious disease. These measures did not appear to have been associated with evidence of severe harm to children in Scotland, as evidenced by severity scores on presentation to PICU or mortality. Implications of all the available evidenceThis is the first comprehensive population-based assessment at a national level of the indirect effects of the COVID-19 pandemic on severe paediatric morbidity and mortality. Despite a significant reduction in health-care utilisation rates, we did not find associated evidence of severe harm. This study will assist policy makers, health-care providers and the public in evaluating the effects of lockdown on the risk of severe paediatric disease at a population level.
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ObjectivesTo investigate the relation of severe COVID-19 to prior drug prescribing. DesignMatched case-control study (REACT-SCOT) based on record linkage to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. SettingScottish population. Main outcome measureSevere COVID-19, defined by entry to critical care or fatal outcome. ParticipantsAll 4272 cases of severe COVID-19 in Scotland since the start of the epidemic, with 36948 controls matched for age, sex and primary care practice. ResultsSevere COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in care homes, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.7, 13.2), and was not accounted for by treatment of conditions designated as conferring increased risk. Of 17 drug classes postulated at the start of the epidemic to be "medications compromising COVID", all were associated with increased risk of severe COVID-19. The largest effect was for antipsychotic agents: rate ratio 4.14 (3.39, 5.07). Other drug classes with large effects included proton pump inhibitors (rate rato 2.19 (1.70, 2.80) for >= 2 defined daily doses/day), opioids (3.62 (2.65, 4.94) for >= 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates, and were stronger with recent than with non-recent exposure. ConclusionsSevere COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression or dyskinesia, have anticholinergic effects or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Although the evidence for causality is not conclusive, these results support existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy as a potential means of reducing COVID-19 risk. RegistrationENCEPP number EUPAS35558 What is already known on this topicTwo previous studies have examined the relationship of severe COVID-19 to drugs for the cardiovascular system. This is the first systematic study of the relationship of severe COVID-19 to prior drug prescribing. What this study addsSevere COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression or dyskinesia, have anticholinergic effects or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. These results support earlier warnings that these drug classes that these drugs might increase susceptibility to COVID-19, and reinforce existing guidance on reducing overprescribing of these drug classes.
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BackgroundCOVID-19 has had large impact on care-home residents internationally. This study systematically examines care-home outbreaks of COVID-19 in a large Scottish health board. MethodsAnalysis of testing, cases and deaths using linked care-home, testing and mortality data for 189 care-homes with 5843 beds in a large Scottish Health Board up to 15/06/20. Findings70 (37.0%) of care-homes experienced a COVID-19 outbreak, 66 of which were in care-homes for older people where care-home size was strongly associated with outbreaks (OR per 20-bed increase 3.50, 95%CI 2.06 to 5.94). There were 852 confirmed cases and 419 COVID-related deaths, 401 (95.7%) of which occurred in care-homes with an outbreak, 16 (3.8%) in hospital, and two in the 119 care-homes without a known outbreak. For non-COVID related deaths, there were 73 excess deaths in care-homes with an outbreak, but no excess deaths in care-homes without an outbreak, and 24 fewer deaths than expected of care-home residents in hospital. A quarter of COVID-19 related cases and deaths occurred in five (2.6%) care-homes, and half in 13 (6.9%) care-homes. InterpretationThe large impact on excess deaths appears to be primarily a direct effect of COVID-19, with cases and deaths are concentrated in a minority of care homes. A key implication is that there is a large pool of susceptible residents if community COVID-19 incidence increases again. Shielding residents from potential sources of infection and rapid action into minimise outbreak size where infection is introduced will be critical in any wave 2. FundingNot externally funded. O_TEXTBOXResearch in context Evidence before this study We searched PubMed and the medRxiv preprint server using terms long-term care, nursing home, care home, or residential care combined with COVID-19 and/or SARS-CoV-2, updated to 25th June. The existing published literature highlights the large impact in care-homes, and that atypical disease presentation, asymptomatic carriage and a presymptomatic infectious period is common in both residents and staff. One living systematic review confirms the international outbreak burden among residents and staff and high but varied international mortality rates. International modelling studies have failed to take account of the care-home environment and context, making estimates informed by general community transmission of infection. Only one peer-reviewed study was identified which evaluated US nursing home characteristics associated with outbreaks, finding associations with larger facility size, urban location, and ethnicity, but no association with quality ratings or ownership. Added value of this study This study reports data for all 189 care homes in one large Scottish health board, where 37% experienced an outbreak of COVID-19, with 95% of outbreaks in care-homes for older people. The number of beds was the only care-home characteristic statistically significantly associated with the presence of an outbreak. One-third of affected care homes had only single cases or short outbreaks, but sustained outbreaks were common, and there was evidence of potential reintroduction of infection in some care-homes with >14 day gaps between confirmed cases. Cases and mortality were heavily concentrated. In care-homes with an outbreak there were 472 excess deaths (12.3% of bed capacity, 3.1 times the average in the previous five years), 85% of which were COVID-19 related. There were only 16 COVID-19 related deaths and 14 other deaths of care-home residents in hospital in the same period, consistent with [~]20 non-COVID excess deaths occurring in care-homes being deaths that would have happened anyway. 99% of the excess deaths and of the COVID-19 related deaths were in care-homes with an outbreak, suggesting that quality and safety of care in the wider care system was not affected. Implications of all the available evidence Outbreak patterns varied considerably and more detailed understanding of why some care homes avoided or controlled outbreaks would allow learning to prepare for wave two. Systematic, regular testing and use of whole genome sequencing will inform understanding of transmission dynamics and future outbreak management. Future research should consider the built environment and organisation of care as other potentially modifiable factors to support infection control. Improving national and local data on the care-home population is a priority both for COVID-19 and for ensuring this vulnerable population receives better care in the future. C_TEXTBOX
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BackgroundAccurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19. MethodsModel derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK. Findings4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups. InterpretationOur prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care. FundingMRC, Wellcome Trust, HDR-UK, LifeArc, participating hospitals, NNSFC, National Key R&D Program, Pudong Health and Family Planning Commission Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral prognostic models for predicting mortality risk, progression to severe disease, or length of hospital stay in COVID-19 have been published.1 Commonly reported predictors of severe prognosis in patients with COVID-19 include age, sex, computed tomography scan features, C-reactive protein (CRP), lactic dehydrogenase, and lymphocyte count. Symptoms (notably dyspnoea) and comorbidities (e.g. chronic lung disease, cardiovascular disease and hypertension) are also reported to have associations with poor prognosis.2 However, most studies have not described the study population or intended use of prediction models, and external validation is rare and to date done using datasets originating from different Wuhan hospitals.3 Given different patterns of testing and organisation of healthcare pathways, external validation in datasets from other countries is required. Added value of this studyThis study used data from Wuhan, China to derive and internally validate multivariable models to predict poor outcome and death in COVID-19 patients after hospital admission, with external validation using data from Kings College Hospital, London, UK. Mortality and poor outcome occurred in 4.3% and 9.7% of patients in Wuhan, compared to 34.1% and 42.9% of patients in London. Models based on age, sex and simple routinely available laboratory tests (lymphocyte count, neutrophil count, platelet count, CRP and creatinine) had good discrimination and calibration in internal validation, but performed only moderately well in external validation. Models based on age, sex, symptoms and comorbidity were adequate in internal validation for poor outcome (ICU admission or death) but had poor performance for death alone. Implications of all the available evidenceThis study and others find that relatively simple risk prediction models using demographic, clinical and laboratory data perform well in internal validation but at best moderately in external validation, either because derivation and external validation populations are small (Xie et al3) and/or because they vary greatly in casemix and severity (our study). There are three decision points where risk prediction may be most useful: (1) deciding who to test; (2) deciding which patients in the community are at high-risk of poor outcomes; and (3) identifying patients at high-risk at the point of hospital admission. Larger studies focusing on particular decision points, with rapid external validation in multiple datasets are needed. A key gap is risk prediction tools for use in community triage (decisions to admit, or to keep at home with varying intensities of follow-up including telemonitoring) or in low income settings where laboratory tests may not be routinely available at the point of decision-making. This requires systematic data collection in community and low-income settings to derive and evaluate appropriate models.
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BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score. MethodsTraining cohorts comprised 1276 patients admitted to Kings College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. ResultsA baseline model of NEWS2 + age had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% CI: 0.680, 0.722; Brier score = 0.192; 95% CI: 0.186, 0.197). A supplemented model adding eight routinely-collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI: 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWMESSAGESC_SCPLOWO_LIThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients. C_LIO_LIRisk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death. C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites. C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches. C_LI
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BackgroundThe risk of severe COVID-19 disease is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 illness, and how this varies between countries may inform the design of possible strategies to shield those at highest risk. MethodsWe estimated the number of individuals at increased risk of severe COVID-19 disease by age (5-year age groups), sex and country (n=188) based on prevalence data from the Global Burden of Disease (GBD) study for 2017 and United Nations population estimates for 2020. We also calculated the number of individuals without an underlying condition that could be considered at-risk because of their age, using thresholds from 50-70 years. The list of underlying conditions relevant to COVID-19 disease was determined by mapping conditions listed in GBD to the guidelines published by WHO and public health agencies in the UK and US. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. ResultsWe estimate that 1.7 (1.0 - 2.4) billion individuals (22% [15-28%] of the global population) are at increased risk of severe COVID-19 disease. The share of the population at increased risk ranges from 16% in Africa to 31% in Europe. Chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes and chronic respiratory disease (CRD) were the most prevalent conditions in males and females aged 50+ years. African countries with a high prevalence of HIV/AIDS and Island countries with a high prevalence of diabetes, also had a high share of the population at increased risk. The prevalence of multimorbidity (>1 underlying conditions) was three times higher in Europe than in Africa (10% vs 3%). ConclusionBased on current guidelines and prevalence data from GBD, we estimate that one in five individuals worldwide has a condition that is on the list of those at increased risk of severe COVID-19 disease. However, for many of these individuals the underlying condition will be undiagnosed or not severe enough to be captured in health systems, and in some cases the increase in risk may be quite modest. There is an urgent need for robust analyses of the risks associated with different underlying conditions so that countries can identify the highest risk groups and develop targeted shielding policies to mitigate the effects of the COVID-19 pandemic. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAs the COVID-19 pandemic evolves, countries are considering policies of shielding the most vulnerable, but there is currently very limited evidence on the number of individuals that might need to be shielded. Guidelines on who is currently believed to be at increased risk of severe COVID-19 illness have been published online by the WHO and public health agencies in the UK and US. We searched PubMed ("Risk factors" AND "COVID-19") without language restrictions, from database inception until April 5, 2020, and identified 62 studies published between Feb 15, 2020 and March 20, 2020. Evidence from China, Italy and the USA indicates that older individuals, males and those with underlying conditions, such as CVD, diabetes and CRD, are at greater risk of severe COVID-19 illness and death. Added value of this studyThis study combines evidence from large international databases and new analysis of large multimorbidity studies to inform policymakers about the number of individuals that may be at increased risk of severe COVID-19 illness in different countries. We developed a tool for rapid assessments of the number and percentage of country populations that would need to be targeted under different shielding policies. Implications of all the available evidenceQuantifying how many and who is at increased risk of severe COVID-19 illness is critical to help countries design more effective interventions to protect vulnerable individuals and reduce pressure on health systems. This information can also inform a broader assessment of the health, social and economic implications of shielding various groups.
