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1.
PLoS Med ; 19(1): e1003870, 2022 01.
Article in English | MEDLINE | ID: covidwho-1608093

ABSTRACT

BACKGROUND: Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic. METHODS AND FINDINGS: We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception. CONCLUSIONS: The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Mortality/trends , Adult , Aged , Female , Humans , Male , Middle Aged , Models, Statistical , Pandemics , Risk Factors , SARS-CoV-2/pathogenicity , Time Factors , United Kingdom/epidemiology
2.
Lancet ; 398(10311): 1593-1618, 2021 10 30.
Article in English | MEDLINE | ID: covidwho-1590726

ABSTRACT

BACKGROUND: Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10-24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. METHODS: We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10-24 years by age group (10-14 years, 15-19 years, and 20-24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10-24 years with that in children aged 0-9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10-24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017). FINDINGS: In 2019 there were 1·49 million deaths (95% uncertainty interval 1·39-1·59) worldwide in people aged 10-24 years, of which 61% occurred in males. 32·7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32·1% were due to communicable, nutritional, or maternal causes; 27·0% were due to non-communicable diseases; and 8·2% were due to self-harm. Since 1950, deaths in this age group decreased by 30·0% in females and 15·3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10-14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15-19 years was 1·3% in males and 1·6% in females, almost half that of males aged 1-4 years (2·4%), and around a third less than in females aged 1-4 years (2·5%). The proportion of global deaths in people aged 0-24 years that occurred in people aged 10-24 years more than doubled between 1950 and 2019, from 9·5% to 21·6%. INTERPRETATION: Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10-24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group. FUNDING: Bill & Melinda Gates Foundation.


Subject(s)
Cause of Death/trends , Global Burden of Disease , Mortality/trends , Adolescent , Age Distribution , Child , Female , Humans , Male , Sex Distribution , Socioeconomic Factors , Young Adult
3.
Sci Rep ; 11(1): 23963, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1585798

ABSTRACT

We demonstrate that finite impulse response (FIR) models can be applied to analyze the time evolution of an epidemic with its impact on deaths and healthcare strain. Using time series data for COVID-19-related cases, ICU admissions and deaths from Sweden, the FIR model gives a consistent epidemiological trajectory for a simple delta filter function. This results in a consistent scaling between the time series if appropriate time delays are applied and allows the reconstruction of cases for times before July 2020, when RT-PCR testing was not widely available. Combined with randomized RT-PCR study results, we utilize this approach to estimate the total number of infections in Sweden, and the corresponding infection-to-fatality ratio (IFR), infection-to-case ratio (ICR), and infection-to-ICU admission ratio (IIAR). Our values for IFR, ICR and IIAR are essentially constant over large parts of 2020 in contrast with claims of healthcare adaptation or mutated virus variants importantly affecting these ratios. We observe a diminished IFR in late summer 2020 as well as a strong decline during 2021, following the launch of a nation-wide vaccination program. The total number of infections during 2020 is estimated to 1.3 million, indicating that Sweden was far from herd immunity.


Subject(s)
COVID-19/epidemiology , Mortality/trends , SARS-CoV-2/isolation & purification , COVID-19/mortality , COVID-19 Nucleic Acid Testing , Finite Element Analysis , Hospitalization/statistics & numerical data , Humans , Intensive Care Units , SARS-CoV-2/genetics , Sweden/epidemiology , Time Factors
6.
MMWR Morb Mortal Wkly Rep ; 70(46): 1613-1616, 2021 Nov 19.
Article in English | MEDLINE | ID: covidwho-1524681

ABSTRACT

Surges in COVID-19 cases have stressed hospital systems, negatively affected health care and public health infrastructures, and degraded national critical functions (1,2). Resource limitations, such as available hospital space, staffing, and supplies led some facilities to adopt crisis standards of care, the most extreme operating condition for hospitals, in which the focus of medical decision-making shifted from achieving the best outcomes for individual patients to addressing the immediate care needs of larger groups of patients (3). When hospitals deviated from conventional standards of care, many preventive and elective procedures were suspended, leading to the progression of serious conditions among some persons who would have benefitted from earlier diagnosis and intervention (4). During March-May 2020, U.S. emergency department visits declined by 23% for heart attacks, 20% for strokes, and 10% for diabetic emergencies (5). The Cybersecurity & Infrastructure Security Agency (CISA) COVID Task Force* examined the relationship between hospital strain and excess deaths during July 4, 2020-July 10, 2021, to assess the impact of COVID-19 surges on hospital system operations and potential effects on other critical infrastructure sectors and national critical functions. The study period included the months during which the highly transmissible SARS-CoV-2 B.1.617.2 (Delta) variant became predominant in the United States.† The negative binomial regression model used to calculate estimated deaths predicted that, if intensive care unit (ICU) bed use nationwide reached 75% capacity an estimated 12,000 additional excess deaths would occur nationally over the next 2 weeks. As hospitals exceed 100% ICU bed capacity, 80,000 excess deaths would be expected in the following 2 weeks. This analysis indicates the importance of controlling case growth and subsequent hospitalizations before severe strain. State, local, tribal, and territorial leaders could evaluate ways to reduce strain on public health and health care infrastructures, including implementing interventions to reduce overall disease prevalence such as vaccination and other prevention strategies, as well as ways to expand or enhance capacity during times of high disease prevalence.


Subject(s)
COVID-19/epidemiology , Hospitals/statistics & numerical data , Mortality/trends , Pandemics , Adult , Bed Occupancy/statistics & numerical data , COVID-19/mortality , COVID-19/therapy , Humans , Intensive Care Units/statistics & numerical data , United States/epidemiology
7.
Biomed Pharmacother ; 144: 112230, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1517059

ABSTRACT

The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has become a serious challenge for medicine and science. Analysis of the molecular mechanisms associated with the clinical manifestations and severity of COVID-19 has identified several key points of immune dysregulation observed in SARS-CoV-2 infection. For diabetic patients, factors including higher binding affinity and virus penetration, decreased virus clearance and decreased T cell function, increased susceptibility to hyperinflammation, and cytokine storm may make these patients susceptible to a more severe course of COVID-19 disease. Metabolic changes induced by diabetes, especially hyperglycemia, can directly affect the immunometabolism of lymphocytes in part by affecting the activity of the mTOR protein kinase signaling pathway. High mTOR activity can enhance the progression of diabetes due to the activation of effector proinflammatory subpopulations of lymphocytes and, conversely, low activity promotes the differentiation of T-regulatory cells. Interestingly, metformin, an extensively used antidiabetic drug, inhibits mTOR by affecting the activity of AMPK. Therefore, activation of AMPK and/or inhibition of the mTOR-mediated signaling pathway may be an important new target for drug therapy in COVID-19 cases mostly by reducing the level of pro-inflammatory signaling and cytokine storm. These suggestions have been partially confirmed by several retrospective analyzes of patients with diabetes mellitus hospitalized for severe COVID-19.


Subject(s)
COVID-19/drug therapy , Diabetes Mellitus/drug therapy , Hypoglycemic Agents/therapeutic use , Immunity, Cellular/drug effects , Metformin/therapeutic use , Severity of Illness Index , COVID-19/epidemiology , COVID-19/immunology , COVID-19/metabolism , Diabetes Mellitus/epidemiology , Diabetes Mellitus/immunology , Diabetes Mellitus/metabolism , Humans , Hypoglycemic Agents/pharmacology , Immunity, Cellular/physiology , Lymphocytes/drug effects , Lymphocytes/immunology , Lymphocytes/metabolism , Metformin/pharmacology , Mortality/trends , T-Lymphocytes, Regulatory/drug effects , T-Lymphocytes, Regulatory/immunology , T-Lymphocytes, Regulatory/metabolism , TOR Serine-Threonine Kinases/antagonists & inhibitors , TOR Serine-Threonine Kinases/immunology , TOR Serine-Threonine Kinases/metabolism
9.
Anesthesiology ; 135(6): 1076-1090, 2021 12 01.
Article in English | MEDLINE | ID: covidwho-1507118

ABSTRACT

BACKGROUND: Mortality in critically ill COVID-19 patients remains high. Although randomized controlled trials must continue to definitively evaluate treatments, further hypothesis-generating efforts to identify candidate treatments are required. This study's hypothesis was that certain treatments are associated with lower COVID-19 mortality. METHODS: This was a 1-yr retrospective cohort study involving all COVID-19 patients admitted to intensive care units in six hospitals affiliated with Yale New Haven Health System from February 13, 2020, to March 4, 2021. The exposures were any COVID-19-related pharmacologic and organ support treatments. The outcome was in-hospital mortality. RESULTS: This study analyzed 2,070 patients after excluding 23 patients who died within 24 h after intensive care unit admission and 3 patients who remained hospitalized on the last day of data censoring. The in-hospital mortality was 29% (593 of 2,070). Of 23 treatments analyzed, apixaban (hazard ratio, 0.42; 95% CI, 0.363 to 0.48; corrected CI, 0.336 to 0.52) and aspirin (hazard ratio, 0.72; 95% CI, 0.60 to 0.87; corrected CI, 0.54 to 0.96) were associated with lower mortality based on the multivariable analysis with multiple testing correction. Propensity score-matching analysis showed an association between apixaban treatment and lower mortality (with vs. without apixaban, 27% [96 of 360] vs. 37% [133 of 360]; hazard ratio, 0.48; 95% CI, 0.337 to 0.69) and an association between aspirin treatment and lower mortality (with vs. without aspirin, 26% [121 of 473] vs. 30% [140 of 473]; hazard ratio, 0.57; 95% CI, 0.41 to 0.78). Enoxaparin showed similar associations based on the multivariable analysis (hazard ratio, 0.82; 95% CI, 0.69 to 0.97; corrected CI, 0.61 to 1.05) and propensity score-matching analysis (with vs. without enoxaparin, 25% [87 of 347] vs. 34% [117 of 347]; hazard ratio, 0.53; 95% CI, 0.367 to 0.77). CONCLUSIONS: Consistent with the known hypercoagulability in severe COVID-19, the use of apixaban, enoxaparin, or aspirin was independently associated with lower mortality in critically ill COVID-19 patients.


Subject(s)
COVID-19/drug therapy , COVID-19/mortality , Critical Illness/mortality , Critical Illness/therapy , Aged , Aged, 80 and over , Anti-Inflammatory Agents, Non-Steroidal/administration & dosage , Anticoagulants/administration & dosage , Antiviral Agents/administration & dosage , Cohort Studies , Factor Xa Inhibitors/administration & dosage , Female , Humans , Male , Middle Aged , Mortality/trends , Retrospective Studies , Treatment Outcome
10.
Crit Care ; 25(1): 382, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1506095

ABSTRACT

BACKGROUND: There are few reports of new functional impairment following critical illness from COVID-19. We aimed to describe the incidence of death or new disability, functional impairment and changes in health-related quality of life of patients after COVID-19 critical illness at 6 months. METHODS: In a nationally representative, multicenter, prospective cohort study of COVID-19 critical illness, we determined the prevalence of death or new disability at 6 months, the primary outcome. We measured mortality, new disability and return to work with changes in the World Health Organization Disability Assessment Schedule 2.0 12L (WHODAS) and health status with the EQ5D-5LTM. RESULTS: Of 274 eligible patients, 212 were enrolled from 30 hospitals. The median age was 61 (51-70) years, and 124 (58.5%) patients were male. At 6 months, 43/160 (26.9%) patients died and 42/108 (38.9%) responding survivors reported new disability. Compared to pre-illness, the WHODAS percentage score worsened (mean difference (MD), 10.40% [95% CI 7.06-13.77]; p < 0.001). Thirteen (11.4%) survivors had not returned to work due to poor health. There was a decrease in the EQ-5D-5LTM utility score (MD, - 0.19 [- 0.28 to - 0.10]; p < 0.001). At 6 months, 82 of 115 (71.3%) patients reported persistent symptoms. The independent predictors of death or new disability were higher severity of illness and increased frailty. CONCLUSIONS: At six months after COVID-19 critical illness, death and new disability was substantial. Over a third of survivors had new disability, which was widespread across all areas of functioning. Clinical trial registration NCT04401254 May 26, 2020.


Subject(s)
COVID-19/epidemiology , Critical Illness/epidemiology , Disabled Persons , Recovery of Function/physiology , Return to Work/trends , Aged , Aged, 80 and over , Australia/epidemiology , COVID-19/diagnosis , COVID-19/therapy , Cohort Studies , Critical Illness/therapy , Female , Follow-Up Studies , Health Status , Humans , Male , Middle Aged , Mortality/trends , Prospective Studies , Time Factors , Treatment Outcome
11.
Sci Rep ; 11(1): 21650, 2021 11 04.
Article in English | MEDLINE | ID: covidwho-1504883

ABSTRACT

The SARS-CoV2 has now spread worldwide causing over four million deaths. Testing strategies are highly variable between countries and their impact on mortality is a major issue. Retrospective multicenter study with a prospective database on all inpatients throughout mainland France. Using fixed effects models, we exploit policy discontinuities at region borders in France to estimate the effect of testing on the case fatality rate. In France, testing policies are determined at a regional level, generating exogenous variation in testing rates between departments on each side of a region border. We compared all contiguous department pairs located on the opposite sides of a region border. The increase of one percentage point in the test rate is associated with a decrease of 0.0015 percentage point in the death rate, that is, for each additional 2000 tests, we could observe three fewer deaths. Our study suggests that COVID-19 population testing could have a significant impact on the mortality rate which should be considered in decision-making. As concern grows over the current second wave of COVID-19, our findings support the implementation of large-scale screening strategies in such epidemic contexts.


Subject(s)
COVID-19 Testing/trends , COVID-19/diagnosis , COVID-19/mortality , France/epidemiology , Humans , Mass Screening/methods , Mass Screening/trends , Mortality/trends , Retrospective Studies , SARS-CoV-2/pathogenicity
12.
MMWR Morb Mortal Wkly Rep ; 70(43): 1520-1524, 2021 Oct 29.
Article in English | MEDLINE | ID: covidwho-1498054

ABSTRACT

By September 21, 2021, an estimated 182 million persons in the United States were fully vaccinated against COVID-19.* Clinical trials indicate that Pfizer-BioNTech (BNT162b2), Moderna (mRNA-1273), and Janssen (Johnson & Johnson; Ad.26.COV2.S) vaccines are effective and generally well tolerated (1-3). However, daily vaccination rates have declined approximately 78% since April 13, 2021†; vaccine safety concerns have contributed to vaccine hesitancy (4). A cohort study of 19,625 nursing home residents found that those who received an mRNA vaccine (Pfizer-BioNTech or Moderna) had lower all-cause mortality than did unvaccinated residents (5), but no studies comparing mortality rates within the general population of vaccinated and unvaccinated persons have been conducted. To assess mortality not associated with COVID-19 (non-COVID-19 mortality) after COVID-19 vaccination in a general population setting, a cohort study was conducted during December 2020-July 2021 among approximately 11 million persons enrolled in seven Vaccine Safety Datalink (VSD) sites.§ After standardizing mortality rates by age and sex, this study found that COVID-19 vaccine recipients had lower non-COVID-19 mortality than did unvaccinated persons. After adjusting for demographic characteristics and VSD site, this study found that adjusted relative risk (aRR) of non-COVID-19 mortality for the Pfizer-BioNTech vaccine was 0.41 (95% confidence interval [CI] = 0.38-0.44) after dose 1 and 0.34 (95% CI = 0.33-0.36) after dose 2. The aRRs of non-COVID-19 mortality for the Moderna vaccine were 0.34 (95% CI = 0.32-0.37) after dose 1 and 0.31 (95% CI = 0.30-0.33) after dose 2. The aRR after receipt of the Janssen vaccine was 0.54 (95% CI = 0.49-0.59). There is no increased risk for mortality among COVID-19 vaccine recipients. This finding reinforces the safety profile of currently approved COVID-19 vaccines in the United States.


Subject(s)
COVID-19 Vaccines/administration & dosage , Mortality/trends , Vaccination/statistics & numerical data , Adolescent , Adult , Aged , COVID-19/epidemiology , COVID-19/prevention & control , Child , Delivery of Health Care, Integrated , Female , Humans , Male , Middle Aged , Risk , United States/epidemiology , Young Adult
13.
PLoS Med ; 18(10): e1003807, 2021 10.
Article in English | MEDLINE | ID: covidwho-1484840

ABSTRACT

BACKGROUND: We examined whether key sociodemographic and clinical risk factors for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and mortality changed over time in a population-based cohort study. METHODS AND FINDINGS: In a cohort of 9,127,673 persons enrolled in the United States Veterans Affairs (VA) healthcare system, we evaluated the independent associations of sociodemographic and clinical characteristics with SARS-CoV-2 infection (n = 216,046), SARS-CoV-2-related mortality (n = 10,230), and case fatality at monthly intervals between February 1, 2020 and March 31, 2021. VA enrollees had a mean age of 61 years (SD 17.7) and were predominantly male (90.9%) and White (64.5%), with 14.6% of Black race and 6.3% of Hispanic ethnicity. Black (versus White) race was strongly associated with SARS-CoV-2 infection (adjusted odds ratio [AOR] 5.10, [95% CI 4.65 to 5.59], p-value <0.001), mortality (AOR 3.85 [95% CI 3.30 to 4.50], p-value < 0.001), and case fatality (AOR 2.56, 95% CI 2.23 to 2.93, p-value < 0.001) in February to March 2020, but these associations were attenuated and not statistically significant by November 2020 for infection (AOR 1.03 [95% CI 1.00 to 1.07] p-value = 0.05) and mortality (AOR 1.08 [95% CI 0.96 to 1.20], p-value = 0.21) and were reversed for case fatality (AOR 0.86, 95% CI 0.78 to 0.95, p-value = 0.005). American Indian/Alaska Native (AI/AN versus White) race was associated with higher risk of SARS-CoV-2 infection in April and May 2020; this association declined over time and reversed by March 2021 (AOR 0.66 [95% CI 0.51 to 0.85] p-value = 0.004). Hispanic (versus non-Hispanic) ethnicity was associated with higher risk of SARS-CoV-2 infection and mortality during almost every time period, with no evidence of attenuation over time. Urban (versus rural) residence was associated with higher risk of infection (AOR 2.02, [95% CI 1.83 to 2.22], p-value < 0.001), mortality (AOR 2.48 [95% CI 2.08 to 2.96], p-value < 0.001), and case fatality (AOR 2.24, 95% CI 1.93 to 2.60, p-value < 0.001) in February to April 2020, but these associations attenuated over time and reversed by September 2020 (AOR 0.85, 95% CI 0.81 to 0.89, p-value < 0.001 for infection, AOR 0.72, 95% CI 0.62 to 0.83, p-value < 0.001 for mortality and AOR 0.81, 95% CI 0.71 to 0.93, p-value = 0.006 for case fatality). Throughout the observation period, high comorbidity burden, younger age, and obesity were consistently associated with infection, while high comorbidity burden, older age, and male sex were consistently associated with mortality. Limitations of the study include that changes over time in the associations of some risk factors may be affected by changes in the likelihood of testing for SARS-CoV-2 according to those risk factors; also, study results apply directly to VA enrollees who are predominantly male and have comprehensive healthcare and need to be confirmed in other populations. CONCLUSIONS: In this study, we found that strongly positive associations of Black and AI/AN (versus White) race and urban (versus rural) residence with SARS-CoV-2 infection, mortality, and case fatality observed early in the pandemic were ameliorated or reversed by March 2021.


Subject(s)
COVID-19/mortality , Population Surveillance , Rural Population/trends , United States Department of Veterans Affairs/trends , Urban Population/trends , Aged , COVID-19/diagnosis , COVID-19/economics , Cohort Studies , Female , Humans , Male , Middle Aged , Mortality/trends , Population Surveillance/methods , Risk Factors , Socioeconomic Factors , United States/epidemiology
14.
Lancet Public Health ; 6(11): e805-e816, 2021 11.
Article in English | MEDLINE | ID: covidwho-1467001

ABSTRACT

BACKGROUND: High-resolution data for how mortality and longevity have changed in England, UK are scarce. We aimed to estimate trends from 2002 to 2019 in life expectancy and probabilities of death at different ages for all 6791 middle-layer super output areas (MSOAs) in England. METHODS: We performed a high-resolution spatiotemporal analysis of civil registration data from the UK Small Area Health Statistics Unit research database using de-identified data for all deaths in England from 2002 to 2019, with information on age, sex, and MSOA of residence, and population counts by age, sex, and MSOA. We used a Bayesian hierarchical model to obtain estimates of age-specific death rates by sharing information across age groups, MSOAs, and years. We used life table methods to calculate life expectancy at birth and probabilities of death in different ages by sex and MSOA. FINDINGS: In 2002-06 and 2006-10, all but a few (0-1%) MSOAs had a life expectancy increase for female and male sexes. In 2010-14, female life expectancy decreased in 351 (5·2%) of 6791 MSOAs. By 2014-19, the number of MSOAs with declining life expectancy was 1270 (18·7%) for women and 784 (11·5%) for men. The life expectancy increase from 2002 to 2019 was smaller in MSOAs where life expectancy had been lower in 2002 (mostly northern urban MSOAs), and larger in MSOAs where life expectancy had been higher in 2002 (mostly MSOAs in and around London). As a result of these trends, the gap between the first and 99th percentiles of MSOA life expectancy for women increased from 10·7 years (95% credible interval 10·4-10·9) in 2002 to reach 14·2 years (13·9-14·5) in 2019, and for men increased from 11·5 years (11·3-11·7) in 2002 to 13·6 years (13·4-13·9) in 2019. INTERPRETATION: In the decade before the COVID-19 pandemic, life expectancy declined in increasing numbers of communities in England. To ensure that this trend does not continue or worsen, there is a need for pro-equity economic and social policies, and greater investment in public health and health care throughout the entire country. FUNDING: Wellcome Trust, Imperial College London, Medical Research Council, Health Data Research UK, and National Institutes of Health Research.


Subject(s)
Life Expectancy/trends , Mortality/trends , Adolescent , Adult , Aged , Aged, 80 and over , Bayes Theorem , Child , Child, Preschool , England/epidemiology , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Registries , Residence Characteristics/statistics & numerical data , Risk Assessment , Spatio-Temporal Analysis , Young Adult
15.
Crit Care ; 25(1): 355, 2021 10 09.
Article in English | MEDLINE | ID: covidwho-1463260

ABSTRACT

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) was frequently used to treat patients with severe coronavirus disease-2019 (COVID-19)-associated acute respiratory distress (ARDS) during the initial outbreak. Care of COVID-19 patients evolved markedly during the second part of 2020. Our objective was to compare the characteristics and outcomes of patients who received ECMO for severe COVID-19 ARDS before or after July 1, 2020. METHODS: We included consecutive adults diagnosed with COVID-19 in Paris-Sorbonne University Hospital Network ICUs, who received ECMO for severe ARDS until January 28, 2021. Characteristics and survival probabilities over time were estimated during the first and second waves. Pre-ECMO risk factors predicting 90-day mortality were assessed using multivariate Cox regression. RESULTS: Characteristics of the 88 and 71 patients admitted, respectively, before and after July 1, 2020, were comparable except for older age, more frequent use of dexamethasone (18% vs. 82%), high-flow nasal oxygenation (19% vs. 82%) and/or non-invasive ventilation (7% vs. 37%) after July 1. Respective estimated probabilities (95% confidence intervals) of 90-day mortality were 36% (27-47%) and 48% (37-60%) during the first and the second periods. After adjusting for confounders, probability of 90-day mortality was significantly higher for patients treated after July 1 (HR 2.27, 95% CI 1.02-5.07). ECMO-related complications did not differ between study periods. CONCLUSIONS: 90-day mortality of ECMO-supported COVID-19-ARDS patients increased significantly after July 1, 2020, and was no longer comparable to that of non-COVID ECMO-treated patients. Failure of prolonged non-invasive oxygenation strategies before intubation and increased lung damage may partly explain this outcome.


Subject(s)
COVID-19/mortality , Extracorporeal Membrane Oxygenation/mortality , Extracorporeal Membrane Oxygenation/trends , Hospitalization/trends , Respiratory Distress Syndrome/mortality , Severity of Illness Index , Adult , COVID-19/therapy , Cohort Studies , Female , Follow-Up Studies , Humans , Intensive Care Units/trends , Male , Middle Aged , Mortality/trends , Paris/epidemiology , Respiratory Distress Syndrome/therapy , Treatment Outcome
16.
PLoS One ; 16(9): e0258018, 2021.
Article in English | MEDLINE | ID: covidwho-1443853

ABSTRACT

BACKGROUND: Data of critically ill COVID-19 patients are being evaluated worldwide, not only to understand the various aspects of the disease and to refine treatment strategies but also to improve clinical decision-making. For clinical decision-making in particular, prognostic factors of a lethal course of the disease would be highly relevant. METHODS: In this retrospective cohort study, we analyzed the first 59 adult critically ill Covid-19 patients treated in one of the intensive care units of the University Medical Center Regensburg, Germany. Using uni- and multivariable regression models, we extracted a set of parameters that allowed for prognosing in-hospital mortality. RESULTS: Within the cohort, 19 patients died (mortality 32.2%). Blood pH value, mean arterial pressure, base excess, troponin, and procalcitonin were identified as highly significant prognostic factors of in-hospital mortality. However, no significant differences were found for other parameters expected to be relevant prognostic factors, like low arterial partial pressure of oxygen or high lactate levels. In the multivariable logistic regression analysis, the pH value and the mean arterial pressure turned out to be the most influential prognostic factors for a lethal course.


Subject(s)
COVID-19/blood , COVID-19/mortality , Adult , Aged , Arterial Pressure/physiology , Blood Physiological Phenomena , Blood Pressure/physiology , Cohort Studies , Critical Illness/mortality , Female , Germany/epidemiology , Hospital Mortality/trends , Humans , Hydrogen-Ion Concentration , Intensive Care Units/trends , Male , Middle Aged , Mortality/trends , Prognosis , Retrospective Studies , Risk Factors , SARS-CoV-2/pathogenicity
17.
Proc Natl Acad Sci U S A ; 118(40)2021 10 05.
Article in English | MEDLINE | ID: covidwho-1442867

ABSTRACT

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans' mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.


Subject(s)
/statistics & numerical data , Life Expectancy/ethnology , Mortality/ethnology , /statistics & numerical data , Adolescent , Adult , Aged , Child , Child, Preschool , Europe , Humans , Infant , Life Expectancy/trends , Middle Aged , Mortality/trends , United States , Young Adult
18.
Sci Rep ; 11(1): 19143, 2021 09 27.
Article in English | MEDLINE | ID: covidwho-1440479

ABSTRACT

The number of reported coronavirus disease (COVID-19) deaths per 100,000 persons observed so far in 2020 is described in 15 European countries and the USA as dependent on age groups and sex. It is compared with the corresponding historic all-cause mortality per year depending on age and sex observed in these countries. Some common features exist although substantial differences in age and sex dependency of COVID-19 mortality were noted between countries. An exponential increase with age is a good model to describe and analyze both COVID-19 and all-cause mortality above 40 years old, where almost all COVID-19 deaths occur. Moreover, age dependency is stronger for COVID-19 mortality than for all-cause mortality, and males have an excess risk compared with women, which is less pronounced in the higher age groups. Additionally, concerning calendar time, differences in the age and sex dependency between countries were noted with the common tendency that male excess risk for COVID-19 mortality was smaller in the second half of the year.


Subject(s)
COVID-19/mortality , Cause of Death , Models, Theoretical , Mortality/trends , Adult , Age Factors , Aged , COVID-19/virology , Europe , Female , Humans , Male , Middle Aged , Risk Factors , SARS-CoV-2/physiology , Sex Factors , United States
19.
Sci Rep ; 11(1): 18938, 2021 09 23.
Article in English | MEDLINE | ID: covidwho-1437693

ABSTRACT

Coronavirus disease (COVID-19) has been spreading all over the world; however, its incidence and case-fatality ratio differ greatly between countries and between continents. We investigated factors associated with international variation in COVID-19 incidence and case-fatality ratio (CFR) across 107 northern hemisphere countries, using publicly available COVID-19 outcome data as of 14 September 2020. We included country-specific geographic, demographic, socio-economic features, global health security index (GHSI), healthcare capacity, and major health behavior indexes in multivariate models to explain this variation. Multiple linear regression highlighted that incidence was associated with ethnic region (p < 0.05), global health security index 4 (GHSI4) (beta coefficient [ß] 0.50, 95% Confidence Interval [CI] 0.14-0.87), population density (ß 0.35, 95% CI 0.10-0.60), and water safety level (ß 0.51, 95% CI 0.19-0.84). The CFR was associated with ethnic region (p < 0.05), GHSI4 (ß 0.53, 95% CI 0.14-0.92), proportion of population over 65 (ß 0.71, 95% CI 0.19-1.24), international tourism receipt level (ß - 0.23, 95% CI - 0.43 to - 0.03), and the number of physicians (ß - 0.37, 95% CI - 0.69 to - 0.06). Ethnic region was the most influential factor for both COVID-19 incidence (partial [Formula: see text] = 0.545) and CFR (partial [Formula: see text] = 0.372), even after adjusting for various confounding factors.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Mortality/trends , Global Health , Humans , Incidence , Population Density , Risk Factors , SARS-CoV-2/pathogenicity
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