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2.
Science ; 375(6585): 1069, 2022 Mar 11.
Article in English | MEDLINE | ID: covidwho-1736010

ABSTRACT

As the world reflects on 2 years of the COVID-19 pandemic, we need to change how to tackle the enormous challenges of the future. The good news is that the past 2 years of the COVID-19 pandemic have shown that change is possible.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Climate Change , Humans , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Public Health
4.
Health Policy ; 126(3): 234-244, 2022 03.
Article in English | MEDLINE | ID: covidwho-1620689

ABSTRACT

The COVID-19 pandemic has shone a light on the complex relationship between science and policy. Policymakers have had to make decisions at speed in conditions of uncertainty, implementing policies that have had profound consequences for people's lives. Yet this process has sometimes been characterised by fragmentation, opacity and a disconnect between evidence and policy. In the United Kingdom, concerns about the secrecy that initially surrounded this process led to the creation of Independent SAGE, an unofficial group of scientists from different disciplines that came together to ask policy-relevant questions, review the evolving evidence, and make evidence-based recommendations. The group took a public health approach with a population perspective, worked in a holistic transdisciplinary way, and were committed to public engagement. In this paper, we review the lessons learned during its first year. These include the importance of learning from local expertise, the value of learning from other countries, the role of civil society as a critical friend to government, finding appropriate relationships between science and policy, and recognising the necessity of viewing issues through an equity lens.


Subject(s)
COVID-19 , Pandemics , Communication , Emergencies , Humans , SARS-CoV-2 , United Kingdom
8.
Science ; 374(6566): 403-404, 2021 Oct 22.
Article in English | MEDLINE | ID: covidwho-1494924
9.
J R Soc Med ; 114(11): 513-524, 2021 11.
Article in English | MEDLINE | ID: covidwho-1488342

ABSTRACT

OBJECTIVE: To offer a quantitative risk-benefit analysis of two doses of SARS-CoV-2 vaccination among adolescents in England. SETTING: England. DESIGN: Following the risk-benefit analysis methodology carried out by the US Centers for Disease Control, we calculated historical rates of hospital admission, Intensive Care Unit admission and death for ascertained SARS-CoV-2 cases in children aged 12-17 in England. We then used these rates alongside a range of estimates for incidence of long COVID, vaccine efficacy and vaccine-induced myocarditis, to estimate hospital and Intensive Care Unit admissions, deaths and cases of long COVID over a period of 16 weeks under assumptions of high and low case incidence. PARTICIPANTS: All 12-17 year olds with a record of confirmed SARS-CoV-2 infection in England between 1 July 2020 and 31 March 2021 using national linked electronic health records, accessed through the British Heart Foundation Data Science Centre. MAIN OUTCOME MEASURES: Hospitalisations, Intensive Care Unit admissions, deaths and cases of long COVID averted by vaccinating all 12-17 year olds in England over a 16-week period under different estimates of future case incidence. RESULTS: At high future case incidence of 1000/100,000 population/week over 16 weeks, vaccination could avert 4430 hospital admissions and 36 deaths over 16 weeks. At the low incidence of 50/100,000/week, vaccination could avert 70 hospital admissions and two deaths over 16 weeks. The benefit of vaccination in terms of hospitalisations in adolescents outweighs risks unless case rates are sustainably very low (below 30/100,000 teenagers/week). Benefit of vaccination exists at any case rate for the outcomes of death and long COVID, since neither have been associated with vaccination to date. CONCLUSIONS: Given the current (as at 15 September 2021) high case rates (680/100,000 population/week in 10-19 year olds) in England, our findings support vaccination of adolescents against SARS-CoV2.


Subject(s)
COVID-19 Vaccines , COVID-19/prevention & control , Hospitalization , Intensive Care Units , Public Health , Severity of Illness Index , Vaccination , Adolescent , Adolescent Health , Age Factors , COVID-19/complications , COVID-19/mortality , COVID-19/therapy , COVID-19 Vaccines/adverse effects , Child , Child Health , England , Female , Humans , Incidence , Male , Myocarditis/etiology , Risk , SARS-CoV-2 , Treatment Outcome , Vaccination/adverse effects
10.
BMJ Open ; 11(9): e049006, 2021 09 30.
Article in English | MEDLINE | ID: covidwho-1443595

ABSTRACT

OBJECTIVES: Globally, healthcare systems have been stretched to the limit by the COVID-19 pandemic. Significant changes have had to be made to the way in which non-COVID-19-related care has been delivered. Our objective was to understand, from the perspective of patients with a chronic, life-long condition (congenital heart disease, CHD) and their parents/carers, the impact of COVID-19 on the delivery of care, how changes were communicated and whether healthcare providers should do anything differently in a subsequent wave of COVID-19 infections. DESIGN AND SETTING: Qualitative study involving a series of asynchronous discussion forums set up and moderated by three patient charities via their Facebook pages. PARTICIPANTS: Patients with CHD and parents/carers of patients with CHD. MAIN OUTCOME MEASURES: Qualitative responses to questions posted on the discussion forums. RESULTS: The forums ran over a 6-week period and involved 109 participants. Following thematic analysis, we identified three themes and 10 subthemes related to individual condition-related factors, patient-related factors and health professional/centre factors that may have influenced how patients and parents/carers experienced changes to service delivery as a result of COVID-19. Specifically, respondents reported high levels of disruption to the delivery of care, inconsistent advice and messaging and variable communication from health professionals, with examples of both excellent and very poor experiences of care reported. Uncertainty about follow-up and factors related to the complexity and stability of their condition contributed to anxiety and stress. CONCLUSIONS: The importance of clear, consistent communication cannot be over-estimated. Our findings, while collected in relation to patients with CHD, are not necessarily specific to this population and we believe that they reflect the experiences of many thousands of people with life-long conditions in the UK. Recommendations related to communication, service delivery and support during the pandemic may improve patients' experience of care and, potentially, their outcomes.


Subject(s)
COVID-19 , Heart Defects, Congenital , Adult , Anxiety Disorders , Child , Heart Defects, Congenital/therapy , Humans , Pandemics , SARS-CoV-2
12.
BMC Med ; 19(1): 213, 2021 08 30.
Article in English | MEDLINE | ID: covidwho-1379790

ABSTRACT

BACKGROUND: The literature paints a complex picture of the association between mortality risk and ICU strain. In this study, we sought to determine if there is an association between mortality risk in intensive care units (ICU) and occupancy of beds compatible with mechanical ventilation, as a proxy for strain. METHODS: A national retrospective observational cohort study of 89 English hospital trusts (i.e. groups of hospitals functioning as single operational units). Seven thousand one hundred thirty-three adults admitted to an ICU in England between 2 April and 1 December, 2020 (inclusive), with presumed or confirmed COVID-19, for whom data was submitted to the national surveillance programme and met study inclusion criteria. A Bayesian hierarchical approach was used to model the association between hospital trust level (mechanical ventilation compatible), bed occupancy, and in-hospital all-cause mortality. Results were adjusted for unit characteristics (pre-pandemic size), individual patient-level demographic characteristics (age, sex, ethnicity, deprivation index, time-to-ICU admission), and recorded chronic comorbidities (obesity, diabetes, respiratory disease, liver disease, heart disease, hypertension, immunosuppression, neurological disease, renal disease). RESULTS: One hundred thirty-five thousand six hundred patient days were observed, with a mortality rate of 19.4 per 1000 patient days. Adjusting for patient-level factors, mortality was higher for admissions during periods of high occupancy (> 85% occupancy versus the baseline of 45 to 85%) [OR 1.23 (95% posterior credible interval (PCI): 1.08 to 1.39)]. In contrast, mortality was decreased for admissions during periods of low occupancy (< 45% relative to the baseline) [OR 0.83 (95% PCI 0.75 to 0.94)]. CONCLUSION: Increasing occupancy of beds compatible with mechanical ventilation, a proxy for operational strain, is associated with a higher mortality risk for individuals admitted to ICU. Further research is required to establish if this is a causal relationship or whether it reflects strain on other operational factors such as staff. If causal, the result highlights the importance of strategies to keep ICU occupancy low to mitigate the impact of this type of resource saturation.


Subject(s)
Bed Occupancy/statistics & numerical data , COVID-19/mortality , Cause of Death , Critical Care/statistics & numerical data , Hospital Mortality , Intensive Care Units , Ventilators, Mechanical , Adolescent , Adult , Aged , Aged, 80 and over , Bayes Theorem , Female , Humans , Male , Middle Aged , Retrospective Studies , SARS-CoV-2 , Young Adult
14.
BMJ ; 373: n986, 2021 Apr 19.
Article in English | MEDLINE | ID: covidwho-1194204
18.
Lancet ; 395(10238): 1715-1725, 2020 05 30.
Article in English | MEDLINE | ID: covidwho-245277

ABSTRACT

BACKGROUND: The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. METHODS: In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. FINDINGS: We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41-4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. INTERPRETATION: We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. FUNDING: National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.


Subject(s)
Coronavirus Infections/epidemiology , Mortality/trends , Pneumonia, Viral/epidemiology , Adult , Aged , Aged, 80 and over , COVID-19 , Cohort Studies , Coronavirus Infections/complications , Female , Humans , Male , Middle Aged , Models, Statistical , Multimorbidity , Pandemics , Pneumonia, Viral/complications , Risk Factors , United Kingdom/epidemiology
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