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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.
Am J Public Health ; 112(1): 154-164, 2022 01.
Article in English | MEDLINE | ID: covidwho-1599518

ABSTRACT

Objectives. To estimate the direct and indirect effects of the COVID-19 pandemic on overall, race/ethnicity‒specific, and age-specific mortality in 2020 in the United States. Methods. Using surveillance data, we modeled expected mortality, compared it to observed mortality, and estimated the share of "excess" mortality that was indirectly attributable to the pandemic versus directly attributed to COVID-19. We present absolute risks and proportions of total pandemic-related mortality, stratified by race/ethnicity and age. Results. We observed 16.6 excess deaths per 10 000 US population in 2020; 84% were directly attributed to COVID-19. The indirect effects of the pandemic accounted for 16% of excess mortality, with proportions as low as 0% among adults aged 85 years and older and more than 60% among those aged 15 to 44 years. Indirect causes accounted for a higher proportion of excess mortality among racially minoritized groups (e.g., 32% among Black Americans and 23% among Native Americans) compared with White Americans (11%). Conclusions. The effects of the COVID-19 pandemic on mortality and health disparities are underestimated when only deaths directly attributed to COVID-19 are considered. An equitable public health response to the pandemic should also consider its indirect effects on mortality. (Am J Public Health. 2022;112(1):154-164. https://doi.org/10.2105/AJPH.2021.306541).


Subject(s)
COVID-19/mortality , Mortality , Statistics as Topic , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Child , Child, Preschool , Humans , Infant , Middle Aged , Risk , United States/epidemiology , Young Adult
4.
Sci Rep ; 11(1): 24477, 2021 12 29.
Article in English | MEDLINE | ID: covidwho-1599359

ABSTRACT

Assessing the impact of temperature on COVID-19 epidemiology is critical for implementing non-pharmaceutical interventions. However, few studies have accounted for the nature of contagious diseases, i.e., their dependent happenings. We aimed to quantify the impact of temperature on the transmissibility and virulence of COVID-19 in Tokyo, Japan, employing two epidemiological measurements of transmissibility and severity: the effective reproduction number ([Formula: see text]) and case fatality risk (CFR). We estimated the [Formula: see text] and time-delay adjusted CFR and to subsequently assess the nonlinear and delayed effect of temperature on [Formula: see text] and time-delay adjusted CFR. For [Formula: see text] at low temperatures, the cumulative relative risk (RR) at the first temperature percentile (3.3 °C) was 1.3 (95% confidence interval (CI): 1.1-1.7). As for the virulence to humans, moderate cold temperatures were associated with higher CFR, and CFR also increased as the temperature rose. The cumulative RR at the 10th and 99th percentiles of temperature (5.8 °C and 30.8 °C) for CFR were 3.5 (95% CI: 1.3-10.0) and 6.4 (95% CI: 4.1-10.1). Our results suggest the importance to take precautions to avoid infection in both cold and warm seasons to avoid severe cases of COVID-19. The results and our proposed approach will also help in assessing the possible seasonal course of COVID-19 in the future.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Temperature , Basic Reproduction Number , Cold Temperature , Humans , Mortality , Pandemics/prevention & control , Risk , SARS-CoV-2/pathogenicity , Seasons , Severity of Illness Index , Tokyo/epidemiology , Virulence
5.
Am J Public Health ; 112(1): 165-168, 2022 01.
Article in English | MEDLINE | ID: covidwho-1592228

ABSTRACT

Objectives. To test whether distortions in the age distribution of deaths can track pandemic activity. Methods. We compared weekly distributions of all-cause deaths by age during the COVID-19 pandemic in the United States from March to December 2020 with corresponding prepandemic weekly baseline distributions derived from data for 2015 to 2019. We measured distortions via Kolmogorov-Smirnov (K-S) and χ2 goodness-of-fit statistics as well as deaths among individuals aged 65 years or older as a percentage of total deaths (PERC65+). We computed bivariate correlations between these measures and the number of recorded COVID-19 deaths for the corresponding weeks. Results. Elevated COVID-19-associated fatalities were accompanied by greater distortions in the age structure of mortality. Distortions in the age distribution of weekly US COVID-19 deaths in 2020 relative to earlier years were highly correlated with COVID fatalities (K-S: r = 0.71, P < .001; χ2: r = 0.90, P < .001; PERC65+: r = 0.85, P < .001). Conclusions. A population-representative sample of age-at-death data can serve as a useful means of pandemic activity surveillance when precise cause-of-death data are incomplete, inaccurate, or unavailable, as is often the case in low-resource environments. (Am J Public Health. 2022;112(1):165-168. https://doi.org/10.2105/AJPH.2021.306567).


Subject(s)
COVID-19/mortality , Mortality , Adult , Age Distribution , Aged , Aged, 80 and over , Humans , Middle Aged , Statistics as Topic , Statistics, Nonparametric , United States/epidemiology
6.
BMJ Open ; 11(12): e052646, 2021 12 23.
Article in English | MEDLINE | ID: covidwho-1591557

ABSTRACT

OBJECTIVES: To examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity. DESIGN: A statistical model to estimate increased mortality in population subgroups during the COVID-19 pandemic by comparing observed with expected mortality in each group based on trends over the previous 5 years. SETTING: Information on deaths registered in England since 2015 was used, including age, sex, area of residence and cause of death. Ethnicity was obtained from Hospital Episode Statistics records linked to death data. PARTICIPANTS: Population study of England, including all 569 824 deaths from all causes registered between 21 March 2020 and 26 February 2021. MAIN OUTCOME MEASURES: Excess mortality in each subgroup over and above the number expected based on trends in mortality in that group over the previous 5 years. RESULTS: The gradient in excess mortality by area deprivation was greater in the under 75s (the most deprived areas had 1.25 times as many deaths as expected, least deprived 1.14) than in all ages (most deprived had 1.24 times as many deaths as expected, least deprived 1.20). Among the black and Asian groups, all area deprivation quintiles had significantly larger excesses than white groups in the most deprived quintiles and there were no clear gradients across quintiles. Among the white group, only those in the most deprived quintile had more excess deaths than deaths directly involving COVID-19. CONCLUSION: The COVID-19 pandemic has widened inequalities in premature mortality by area deprivation. Among those under 75, the direct and indirect effects of the pandemic on deaths have disproportionately impacted ethnic minority groups irrespective of area deprivation, and the white group the most deprived areas. Statistics limited to deaths directly involving COVID-19 understate the pandemic's impact on inequalities by area deprivation and ethnic group at younger ages.


Subject(s)
COVID-19 , Cross-Sectional Studies , England/epidemiology , Humans , Minority Groups , Mortality , Mortality, Premature , Pandemics , SARS-CoV-2
7.
Int J Equity Health ; 20(1): 258, 2021 12 18.
Article in English | MEDLINE | ID: covidwho-1582063

ABSTRACT

BACKGROUND: Belgium was one of the countries that was struck hard by COVID-19. Initially, the belief was that we were 'all in it together'. Emerging evidence showed however that deprived socioeconomic groups suffered disproportionally. Yet, few studies are available for Belgium. The main question addressed in this paper is whether excess mortality during the first COVID-19 wave followed a social gradient and whether the classic mortality gradient was reproduced. METHODS: We used nationwide individually linked data from the Belgian National Register and the Census 2011. Age-standardized all-cause mortality rates were calculated during the first COVID-19 wave in weeks 11-20 in 2020 and compared with the rates during weeks 11-20 in 2015-2019 to calculate absolute and relative excess mortality by socioeconomic and -demographic characteristics. For both periods, relative inequalities in total mortality between socioeconomic and -demographic groups were calculated using Poisson regression. Analyses were stratified by age, gender and care home residence. RESULTS: Excess mortality during the first COVID-19 wave was high in collective households, with care homes hit extremely hard by the pandemic. The social patterning of excess mortality was rather inconsistent and deviated from the usual gradient, mainly through higher mortality excesses among higher socioeconomic groups classes in specific age-sex groups. Overall, the first COVID-19 wave did not change the social patterning of mortality, however. Differences in relative inequalities between both periods were generally small and insignificant, except by household living arrangement. CONCLUSION: The social patterning during the first COVID-19 wave was exceptional as excess mortality did not follow the classic lines of higher mortality in lower classes and patterns were not always consistent. Relative mortality inequalities did not change substantially during the first COVID-19 wave compared to the reference period.


Subject(s)
COVID-19 , Belgium/epidemiology , Humans , Infant , Mortality , Pandemics , Residence Characteristics , SARS-CoV-2 , Socioeconomic Factors
8.
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
10.
Int J Environ Res Public Health ; 18(24)2021 12 15.
Article in English | MEDLINE | ID: covidwho-1572486

ABSTRACT

In 2020, the number of deaths increased in Italy, mainly because of the COVID-19 pandemic; mortality was among the highest in Europe, with a clear heterogeneity among regions and socio-demographic strata. The present work aims to describe trends in mortality and to quantify excess mortality variability over time and in relation to demographics, pre-existent chronic conditions and care setting of the Emilia-Romagna region (Northern Italy). This is a registry-based cross-sectional study comparing the 2020 observed mortality with figures of the previous five years by age, sex, month, place of death, and chronicity. It includes 300,094 deaths in those 18 years of age and above resident in the Emilia-Romagna region. Excess deaths were higher during the first pandemic wave, particularly among men and in March. Age-adjusted risk was similar among both men and women (Mortality Rate Ratio 1.15; IC95% 1.14-1.16). It was higher among females aged 75+ years and varied between sub-periods. Excluding COVID-19 related deaths, differences in the risk of dying estimates tended to disappear. Metabolic and neuropsychiatric diseases were more prevalent among those that deceased in 2020 compared to the deaths that occurred in 2015-2019 and therefore can be confirmed as elements of increased frailty, such as being in long-term care facilities or private homes as the place of death. Understanding the impact of the pandemic on mortality considering frailties is relevant in a changing scenario.


Subject(s)
COVID-19 , Cross-Sectional Studies , Female , Humans , Italy/epidemiology , Male , Mortality , Pandemics , SARS-CoV-2
11.
Lancet Infect Dis ; 21(11): 1590-1597, 2021 11.
Article in English | MEDLINE | ID: covidwho-1561435

ABSTRACT

BACKGROUND: Trials of BCG vaccination to prevent or reduce severity of COVID-19 are taking place in adults, some of whom have been previously vaccinated, but evidence of the beneficial, non-specific effects of BCG come largely from data on mortality in infants and young children, and from in-vitro and animal studies, after a first BCG vaccination. We assess all-cause mortality following a large BCG revaccination trial in Malawi. METHODS: The Karonga Prevention trial was a population-based, double-blind, randomised controlled in Karonga District, northern Malawi, that enrolled participants between January, 1986, and November, 1989. The trial compared BCG (Glaxo-strain) revaccination versus placebo to prevent tuberculosis and leprosy. 46 889 individuals aged 3 months to 75 years were randomly assigned to receive BCG revaccination (n=23 528) or placebo (n=23 361). Here we report mortality since vaccination as recorded during active follow-up in northern areas of the district in 1991-94, and in a demographic surveillance follow-up in the southern area in 2002-18. 7389 individuals who received BCG (n=3746) or placebo (n=3643) lived in the northern follow-up areas, and 5616 individuals who received BCG (n=2798) or placebo (n=2818) lived in the southern area. Year of death or leaving the area were recorded for those not found. We used survival analysis to estimate all-cause mortality. FINDINGS: Follow-up information was available for 3709 (99·0%) BCG recipients and 3612 (99·1%) placebo recipients in the northern areas, and 2449 (87·5%) BCG recipients and 2413 (85·6%) placebo recipients in the southern area. There was no difference in mortality between the BCG and placebo groups in either area, overall or by age group or sex. In the northern area, there were 129 deaths per 19 694 person-years at risk in the BCG group (6·6 deaths per 1000 person-years at risk [95% CI 5·5-7·8]) versus 133 deaths per 19 111 person-years at risk in the placebo group (7·0 deaths per 1000 person-years at risk [95% CI 5·9-8·2]; HR 0·94 [95% CI 0·74-1·20]; p=0·62). In the southern area, there were 241 deaths per 38 399 person-years at risk in the BCG group (6·3 deaths per 1000 person-years at risk [95% CI 5·5-7·1]) versus 230 deaths per 38 676 person-years at risk in the placebo group (5·9 deaths per 1000 person-years at risk [95% CI 5·2-6·8]; HR 1·06 [95% CI 0·88-1·27]; p=0·54). INTERPRETATION: We found little evidence of any beneficial effect of BCG revaccination on all-cause mortality. The high proportion of deaths attributable to non-infectious causes beyond infancy, and the long time interval since BCG for most deaths, might obscure any benefits. FUNDING: British Leprosy Relief Association (LEPRA); Wellcome Trust.


Subject(s)
BCG Vaccine/administration & dosage , Immunization, Secondary/statistics & numerical data , Mortality , Vaccination/methods , Adolescent , Adult , Aged , BCG Vaccine/immunology , COVID-19/epidemiology , COVID-19/immunology , COVID-19/prevention & control , Child , Child, Preschool , Double-Blind Method , Female , Follow-Up Studies , Humans , Immunogenicity, Vaccine , Leprosy/immunology , Leprosy/mortality , Leprosy/prevention & control , Malawi/epidemiology , Male , Middle Aged , Mycobacterium leprae/immunology , SARS-CoV-2/immunology , Treatment Outcome , Tuberculosis/immunology , Tuberculosis/mortality , Tuberculosis/prevention & control , Vaccination/statistics & numerical data , Young Adult
14.
Lancet Respir Med ; 9(5): 522-532, 2021 05.
Article in English | MEDLINE | ID: covidwho-1537199

ABSTRACT

BACKGROUND: Elevated proinflammatory cytokines are associated with greater COVID-19 severity. We aimed to assess safety and efficacy of sarilumab, an interleukin-6 receptor inhibitor, in patients with severe (requiring supplemental oxygen by nasal cannula or face mask) or critical (requiring greater supplemental oxygen, mechanical ventilation, or extracorporeal support) COVID-19. METHODS: We did a 60-day, randomised, double-blind, placebo-controlled, multinational phase 3 trial at 45 hospitals in Argentina, Brazil, Canada, Chile, France, Germany, Israel, Italy, Japan, Russia, and Spain. We included adults (≥18 years) admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and pneumonia, who required oxygen supplementation or intensive care. Patients were randomly assigned (2:2:1 with permuted blocks of five) to receive intravenous sarilumab 400 mg, sarilumab 200 mg, or placebo. Patients, care providers, outcome assessors, and investigators remained masked to assigned intervention throughout the course of the study. The primary endpoint was time to clinical improvement of two or more points (seven point scale ranging from 1 [death] to 7 [discharged from hospital]) in the modified intention-to-treat population. The key secondary endpoint was proportion of patients alive at day 29. Safety outcomes included adverse events and laboratory assessments. This study is registered with ClinicalTrials.gov, NCT04327388; EudraCT, 2020-001162-12; and WHO, U1111-1249-6021. FINDINGS: Between March 28 and July 3, 2020, of 431 patients who were screened, 420 patients were randomly assigned and 416 received placebo (n=84 [20%]), sarilumab 200 mg (n=159 [38%]), or sarilumab 400 mg (n=173 [42%]). At day 29, no significant differences were seen in median time to an improvement of two or more points between placebo (12·0 days [95% CI 9·0 to 15·0]) and sarilumab 200 mg (10·0 days [9·0 to 12·0]; hazard ratio [HR] 1·03 [95% CI 0·75 to 1·40]; log-rank p=0·96) or sarilumab 400 mg (10·0 days [9·0 to 13·0]; HR 1·14 [95% CI 0·84 to 1·54]; log-rank p=0·34), or in proportions of patients alive (77 [92%] of 84 patients in the placebo group; 143 [90%] of 159 patients in the sarilumab 200 mg group; difference -1·7 [-9·3 to 5·8]; p=0·63 vs placebo; and 159 [92%] of 173 patients in the sarilumab 400 mg group; difference 0·2 [-6·9 to 7·4]; p=0·85 vs placebo). At day 29, there were numerical, non-significant survival differences between sarilumab 400 mg (88%) and placebo (79%; difference +8·9% [95% CI -7·7 to 25·5]; p=0·25) for patients who had critical disease. No unexpected safety signals were seen. The rates of treatment-emergent adverse events were 65% (55 of 84) in the placebo group, 65% (103 of 159) in the sarilumab 200 mg group, and 70% (121 of 173) in the sarilumab 400 mg group, and of those leading to death 11% (nine of 84) were in the placebo group, 11% (17 of 159) were in the sarilumab 200 mg group, and 10% (18 of 173) were in the sarilumab 400 mg group. INTERPRETATION: This trial did not show efficacy of sarilumab in patients admitted to hospital with COVID-19 and receiving supplemental oxygen. Adequately powered trials of targeted immunomodulatory therapies assessing survival as a primary endpoint are suggested in patients with critical COVID-19. FUNDING: Sanofi and Regeneron Pharmaceuticals.


Subject(s)
Antibodies, Monoclonal, Humanized , COVID-19 , Cytokine Release Syndrome , Receptors, Interleukin-6/antagonists & inhibitors , Respiratory Distress Syndrome , SARS-CoV-2/isolation & purification , Antibodies, Monoclonal, Humanized/administration & dosage , Antibodies, Monoclonal, Humanized/adverse effects , COVID-19/complications , COVID-19/immunology , COVID-19/mortality , COVID-19/therapy , Critical Care/methods , Cytokine Release Syndrome/drug therapy , Cytokine Release Syndrome/etiology , Cytokine Release Syndrome/immunology , Dose-Response Relationship, Drug , Drug Monitoring/methods , Female , Humans , Immunologic Factors/administration & dosage , Immunologic Factors/adverse effects , International Cooperation , Male , Middle Aged , Mortality , Respiratory Distress Syndrome/diagnosis , Respiratory Distress Syndrome/etiology , Severity of Illness Index , Treatment Outcome
16.
Lancet Respir Med ; 9(5): 511-521, 2021 05.
Article in English | MEDLINE | ID: covidwho-1537197

ABSTRACT

BACKGROUND: Global randomised controlled trials of the anti-IL-6 receptor antibody tocilizumab in patients admitted to hospital with COVID-19 have shown conflicting results but potential decreases in time to discharge and burden on intensive care. Tocilizumab reduced progression to mechanical ventilation and death in a trial population enriched for racial and ethnic minorities. We aimed to investigate whether tocilizumab treatment could prevent COVID-19 progression in the first multicentre randomised controlled trial of tocilizumab done entirely in a lower-middle-income country. METHODS: COVINTOC is an open-label, multicentre, randomised, controlled, phase 3 trial done at 12 public and private hospitals across India. Adults (aged ≥18 years) admitted to hospital with moderate to severe COVID-19 (Indian Ministry of Health grading) confirmed by positive SARS-CoV-2 PCR result were randomly assigned (1:1 block randomisation) to receive tocilizumab 6 mg/kg plus standard care (the tocilizumab group) or standard care alone (the standard care group). The primary endpoint was progression of COVID-19 (from moderate to severe or from severe to death) up to day 14 in the modified intention-to-treat population of all participants who had at least one post-baseline assessment for the primary endpoint. Safety was assessed in all randomly assigned patients. The trial is completed and registered with the Clinical Trials Registry India (CTRI/2020/05/025369). FINDINGS: 180 patients were recruited between May 30, 2020, and Aug 31, 2020, and randomly assigned to the tocilizumab group (n=90) or the standard care group (n=90). One patient randomly assigned to the standard care group inadvertently received tocilizumab at baseline and was included in the tocilizumab group for all analyses. One patient randomly assigned to the standard care group withdrew consent after the baseline visit and did not receive any study medication and was not included in the modified intention-to-treat population but was still included in safety analyses. 75 (82%) of 91 in the tocilizumab group and 68 (76%) of 89 in the standard care group completed 28 days of follow-up. Progression of COVID-19 up to day 14 occurred in eight (9%) of 91 patients in the tocilizumab group and 11 (13%) of 88 in the standard care group (difference -3·71 [95% CI -18·23 to 11·19]; p=0·42). 33 (36%) of 91 patients in the tocilizumab group and 22 (25%) of 89 patients in the standard care group had adverse events; 18 (20%) and 15 (17%) had serious adverse events. The most common adverse event was acute respiratory distress syndrome, reported in seven (8%) patients in each group. Grade 3 adverse events were reported in two (2%) patients in the tocilizumab group and five (6%) patients in the standard care group. There were no grade 4 adverse events. Serious adverse events were reported in 18 (20%) patients in the tocilizumab group and 15 (17%) in the standard care group; 13 (14%) and 15 (17%) patients died during the study. INTERPRETATION: Routine use of tocilizumab in patients admitted to hospital with moderate to severe COVID-19 is not supported. However, post-hoc evidence from this study suggests tocilizumab might still be effective in patients with severe COVID-19 and so should be investigated further in future studies. FUNDING: Medanta Institute of Education and Research, Roche India, Cipla India, and Action COVID-19 India.


Subject(s)
Antibodies, Monoclonal, Humanized , COVID-19 , Cytokine Release Syndrome , Receptors, Interleukin-6/antagonists & inhibitors , Respiratory Distress Syndrome , SARS-CoV-2/isolation & purification , Antibodies, Monoclonal, Humanized/administration & dosage , Antibodies, Monoclonal, Humanized/adverse effects , COVID-19/complications , COVID-19/immunology , COVID-19/mortality , COVID-19/therapy , Critical Care/methods , Cytokine Release Syndrome/drug therapy , Cytokine Release Syndrome/etiology , Cytokine Release Syndrome/immunology , Drug Monitoring/methods , Female , Humans , Immunologic Factors/administration & dosage , Immunologic Factors/adverse effects , India , Male , Middle Aged , Mortality , Respiration, Artificial/methods , Respiratory Distress Syndrome/diagnosis , Respiratory Distress Syndrome/etiology , Severity of Illness Index , Treatment Outcome
17.
Int J Immunopathol Pharmacol ; 35: 20587384211059677, 2021.
Article in English | MEDLINE | ID: covidwho-1533223

ABSTRACT

Oral booster-single strain probiotic bifidobacteria could be a potential strategy for SARS-CoV-2. This study aims to evaluate the role of oral probiotic Bifidobacterium on moderate/severe SARS-CoV-2 inpatients. In this single-center study, we analyzed data of 44 moderate/severe inpatients with diagnosed COVID-19 in Istanbul Maltepe University Medical Faculty Hospital, 2020 from 1 November 2020 to 15 December 2020. Clinical and medication features were compared and analyzed between patients with or without probiotic. In result, 19 of the 44 patients (43.18%) who were administrated with oral booster-single strain probiotic were discharged with the median inpatient day of 7.6 days which were significantly shorter than those of patients without probiotic. There were significant differences in inpatient days, radiological improvement at day 6 and week 3, and reduction in interleukin-6 levels in those receiving oral probiotic therapy. Although the mortality rate was 5% in the probiotic group, it was 25% in the non-probiotic group. Booster-single strain probiotic bifidobacteria could be an effective treatment strategy for moderate/severe SARS-CoV-2 inpatients to reduce the mortality and length of stay in hospital.


Subject(s)
Bifidobacterium , COVID-19 , Interleukin-6/blood , Probiotics , COVID-19/diagnosis , COVID-19/drug therapy , COVID-19/epidemiology , COVID-19/immunology , Female , Hospitalization/statistics & numerical data , Humans , Immunologic Factors/administration & dosage , Immunologic Factors/adverse effects , Length of Stay/statistics & numerical data , Male , Middle Aged , Mortality , Probiotics/administration & dosage , Probiotics/adverse effects , Retrospective Studies , SARS-CoV-2/drug effects , Severity of Illness Index , Treatment Outcome , Turkey/epidemiology
18.
Epidemiol Health ; 43: e2021061, 2021.
Article in English | MEDLINE | ID: covidwho-1534391

ABSTRACT

OBJECTIVES: During the coronavirus disease 2019 (COVID-19) pandemic, crude incidence and mortality rates have been widely reported; however, age-standardized rates are more suitable for comparisons. In this study, we estimated and compared the age-standardized incidence, mortality, and case fatality rates (CFRs) among countries and investigated the relationship between these rates and factors associated with healthcare resources: gross domestic product per capita, number of hospital beds per population, and number of doctors per population. METHODS: The incidence, mortality, and CFRs of 79 countries were age-standardized using the World Health Organization standard population. The rates for persons 60 years or older were also calculated. The relationships among the rates were analysed using trend lines and coefficients of determination (R2). Pearson correlation coefficients between the rates and the healthcare resource-related factors were calculated. RESULTS: The countries with the highest age-standardized incidence, mortality, and CFRs were Czechia (14,253 cases/100,000), Mexico (182 deaths/100,000), and Mexico (6.7%), respectively. The R2 between the incidence and mortality rates was 0.852 for all ages and 0.945 for those 60 years or older. The healthcare resources-related factors were associated positively with incidence rates and negatively with CFRs, with weaker correlations among the elderly. CONCLUSIONS: Compared to age-standardized rates, crude rates showed greater variation among countries. Medical resources may be important in preventing COVID-19-related deaths; however, considering the small variation in fatality among the elderly, preventive measures such as vaccination are more important, especially for the elderly population, to minimize the mortality rates.


Subject(s)
COVID-19 , Aged , Cross-Sectional Studies , Humans , Incidence , Infant , Mortality , Pandemics , SARS-CoV-2
19.
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
20.
BMJ Open ; 11(11): e050361, 2021 11 16.
Article in English | MEDLINE | ID: covidwho-1523004

ABSTRACT

OBJECTIVES: Cause-of-death discrepancies are common in respiratory illness-related mortality. A standard epidemiological metric, excess all-cause death, is unaffected by these discrepancies but provides no actionable policy information when increased all-cause mortality is unexplained by reported specific causes. To assess the contribution of unexplained mortality to the excess death metric, we parsed excess deaths in the COVID-19 pandemic into changes in explained versus unexplained (unreported or unspecified) causes. DESIGN: Retrospective repeated cross-sectional analysis, US death certificate data for six influenza seasons beginning October 2014, comparing population-adjusted historical benchmarks from the previous two, three and five seasons with 2019-2020. SETTING: 48 of 50 states with complete data. PARTICIPANTS: 16.3 million deaths in 312 weeks, reported in categories-all causes, top eight natural causes and respiratory causes including COVID-19. OUTCOME MEASURES: Change in population-adjusted counts of deaths from seasonal benchmarks to 2019-2020, from all causes (ie, total excess deaths) and from explained versus unexplained causes, reported for the season overall and for time periods defined a priori: pandemic awareness (19 January through 28 March); initial pandemic peak (29 March through 30 May) and pandemic post-peak (31 May through 26 September). RESULTS: Depending on seasonal benchmark, 287 957-306 267 excess deaths occurred through September 2020: 179 903 (58.7%-62.5%) attributed to COVID-19; 44 022-49 311 (15.2%-16.1%) to other reported causes; 64 032-77 054 (22.2%-25.2%) unexplained (unspecified or unreported cause). Unexplained deaths constituted 65.2%-72.5% of excess deaths from 19 January to 28 March and 14.1%-16.1% from 29 March through 30 May. CONCLUSIONS: Unexplained mortality contributed substantially to US pandemic period excess deaths. Onset of unexplained mortality in February 2020 coincided with previously reported increases in psychotropic use, suggesting possible psychiatric or injurious causes. Because underlying causes of unexplained deaths may vary by group or region, results suggest excess death calculations provide limited actionable information, supporting previous calls for improved cause-of-death data to support evidence-based policy.


Subject(s)
COVID-19 , Pandemics , Cause of Death , Cross-Sectional Studies , Death Certificates , Humans , Mortality , Retrospective Studies , SARS-CoV-2
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