Characteristics and risk of COVID-19-related death in fully vaccinated people in Scotland
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ABSTRACT:
SUBMITTER: Grange Z
PROVIDER: S-EPMC8553268 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesThe mRNA coronavirus disease 2019 (COVID-19) vaccines have shown high effectiveness in the prevention of symptomatic COVID-19, hospitalization, severe disease and death. Nevertheless, a minority of vaccinated individuals might become infected and experience significant morbidity. Characteristics of vaccine breakthrough infections have not been studied. We sought to portray the population of Israeli patients, who were hospitalized with COVID-19 despite full vaccination.MethodsA retrospective multicentre cohort study of 17 hospitals included patients fully vaccinated with Pfizer/BioNTech's BNT162b2 vaccine who developed COVID-19 more than 7 days after the second vaccine dose and required hospitalization. The risk for poor outcome, defined as a composite of mechanical ventilation or death, was assessed.ResultsA total of 152 patients were included, accounting for half of hospitalized fully vaccinated patients in Israel. Poor outcome was noted in 38 patients and mortality rate reached 22% (34/152). Notably, the cohort was characterized by a high rate of co-morbidities predisposing to severe COVID-19, including hypertension (108; 71%), diabetes (73; 48%), congestive heart failure (41; 27%), chronic kidney and lung diseases (37; 24% each), dementia (29; 19%) and cancer (36; 24%), and only six (4%) had no co-morbidities. Sixty (40%) of the patients were immunocompromised. Higher viral load was associated with a significant risk for poor outcome. Risk also appeared higher in patients receiving anti-CD20 treatment and in patients with low titres of anti-Spike IgG, but these differences did not reach statistical significance.ConclusionsWe found that severe COVID-19 infection, associated with a high mortality rate, might develop in a minority of fully vaccinated individuals with multiple co-morbidities. Our patients had a higher rate of co-morbidities and immunosuppression compared with previously reported non-vaccinated hospitalized individuals with COVID-19. Further characterization of this vulnerable population may help to develop guidance to augment their protection, either by continued social distancing, or by additional active or passive vaccinations.
| S-EPMC8261136 | biostudies-literature
Project description:Breakthrough COVID-19 may occur in fully vaccinated persons. In this cohort of 1395 persons (mean age, 54.3 years; 60% female; median body mass index, 30.7) who developed breakthrough COVID-19, there were 107 (7.7%) who required hospitalization by day 28. Hospitalization was significantly associated with the number of medical comorbidities. Anti-spike monoclonal antibody treatment was significantly associated with a lower risk of hospitalization (Odds Ratio: 0.227; 95% confidence interval, 0.128 - 0.403; p<0.001). The number needed to treat (NNT) to prevent one hospitalization was 225 among the lowest-risk patient group compared to NNT of 4 among those with highest numbers of medical comorbidity.
| S-EPMC8767864 | biostudies-literature
Project description:IntroductionThis study aimed to examine the heterogeneity of the associations between social determinants and COVID-19 fully vaccinated rate.MethodsThis study proposes 3 multiscale dimensions of spatial process, including level of influence (the percentage of population affected by a certain determinant across the entire area), scalability (the spatial process of a determinant into global, regional, and local process), and specificity (the determinant that has the strongest association with the fully vaccinated rate). The multiscale geographically weighted regression was applied to the COVID-19 fully vaccinated rates in U.S. counties (N=3,106) as of October 26, 2021, and the analyses were conducted in May 2022.ResultsThe results suggest the following: (1) Percentage of Republican votes in the 2020 presidential election is a primary influencer because 84% of the U.S. population lived in counties where this determinant is found the most dominant; (2) Demographic compositions (e.g., percentages of racial/ethnic minorities) play a larger role than socioeconomic conditions (e.g., unemployment) in shaping fully vaccinated rates; (3) The spatial process underlying fully vaccinated rates is largely local.ConclusionsThe findings challenge the 1-size-fits-all approach to designing interventions promoting COVID-19 vaccination and highlight the importance of a place-based perspective in ecological health research.
| S-EPMC9259504 | biostudies-literature
Project description:We provide new evidence about the work-related exposure of disabled people to COVID-19 using household survey data combined with a novel occupational risk indicator. Despite their higher clinical vulnerability, disabled people in employment in the UK were significantly more likely to be going out to work during the pandemic rather than working from home, and were working in occupations that were more exposed to COVID-19 than the occupations of non-disabled workers. Our results raise questions about whether there are sufficient safeguards for disabled people in the workplace, and have longer-term implications for a labour market where COVID-19 is a persistent health issue.
| S-EPMC8629513 | biostudies-literature
Project description:We use the cutting-edge causal forest algorithm to analyze the heterogeneous treatment effects of the COVID-19 outbreak on China's industry indexes. The variable importance index is used with the causal forest and complex network methods to analyze the characteristics of industrial relations and the types of industry risk contagion before and after the COVID-19 outbreak. The results show that the heterogeneity of industries was significantly weakened during the COVID-19 outbreak. In addition, the COVID-19 outbreak changed the original structure of the industry-related network, which shifted to a star network structure with leisure services at the core. It also changed the type of risk contagion between industries, from the original middleman risk type to the input risk type.
| S-EPMC7834769 | biostudies-literature
Project description: Not available
| S-EPMC8653163 | biostudies-literature
Project description:BackgroundWe aimed to ascertain the cumulative risk of fatal or critical care unit-treated COVID-19 in people with diabetes and compare it with that of people without diabetes, and to investigate risk factors for and build a cross-validated predictive model of fatal or critical care unit-treated COVID-19 among people with diabetes.MethodsIn this cohort study, we captured the data encompassing the first wave of the pandemic in Scotland, from March 1, 2020, when the first case was identified, to July 31, 2020, when infection rates had dropped sufficiently that shielding measures were officially terminated. The participants were the total population of Scotland, including all people with diabetes who were alive 3 weeks before the start of the pandemic in Scotland (estimated Feb 7, 2020). We ascertained how many people developed fatal or critical care unit-treated COVID-19 in this period from the Electronic Communication of Surveillance in Scotland database (on virology), the RAPID database of daily hospitalisations, the Scottish Morbidity Records-01 of hospital discharges, the National Records of Scotland death registrations data, and the Scottish Intensive Care Society and Audit Group database (on critical care). Among people with fatal or critical care unit-treated COVID-19, diabetes status was ascertained by linkage to the national diabetes register, Scottish Care Information Diabetes. We compared the cumulative incidence of fatal or critical care unit-treated COVID-19 in people with and without diabetes using logistic regression. For people with diabetes, we obtained data on potential risk factors for fatal or critical care unit-treated COVID-19 from the national diabetes register and other linked health administrative databases. We tested the association of these factors with fatal or critical care unit-treated COVID-19 in people with diabetes, and constructed a prediction model using stepwise regression and 20-fold cross-validation.FindingsOf the total Scottish population on March 1, 2020 (n=5 463 300), the population with diabetes was 319 349 (5·8%), 1082 (0·3%) of whom developed fatal or critical care unit-treated COVID-19 by July 31, 2020, of whom 972 (89·8%) were aged 60 years or older. In the population without diabetes, 4081 (0·1%) of 5 143 951 people developed fatal or critical care unit-treated COVID-19. As of July 31, the overall odds ratio (OR) for diabetes, adjusted for age and sex, was 1·395 (95% CI 1·304-1·494; p<0·0001, compared with the risk in those without diabetes. The OR was 2·396 (1·815-3·163; p<0·0001) in type 1 diabetes and 1·369 (1·276-1·468; p<0·0001) in type 2 diabetes. Among people with diabetes, adjusted for age, sex, and diabetes duration and type, those who developed fatal or critical care unit-treated COVID-19 were more likely to be male, live in residential care or a more deprived area, have a COVID-19 risk condition, retinopathy, reduced renal function, or worse glycaemic control, have had a diabetic ketoacidosis or hypoglycaemia hospitalisation in the past 5 years, be on more anti-diabetic and other medication (all p<0·0001), and have been a smoker (p=0·0011). The cross-validated predictive model of fatal or critical care unit-treated COVID-19 in people with diabetes had a C-statistic of 0·85 (0·83-0·86).InterpretationOverall risks of fatal or critical care unit-treated COVID-19 were substantially elevated in those with type 1 and type 2 diabetes compared with the background population. The risk of fatal or critical care unit-treated COVID-19, and therefore the need for special protective measures, varies widely among those with diabetes but can be predicted reasonably well using previous clinical history.FundingNone.
| S-EPMC7832778 | biostudies-literature
Project description:ObjectivesTo derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination.DesignProspective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries.SettingsAdults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021.Main outcome measuresPrimary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices.ResultsOf 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down's syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson's disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%.ConclusionThis population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.
| S-EPMC8446717 | biostudies-literature
Project description:RationaleCOVID-19 is likely to be stigmatized. The people of Hubei province perceived courtesy and affiliate stigma due to the geographic linkage to COVID-19. Perceived courtesy stigma refers to the perception of stigma of people who are associated with COVID-19 (e.g., the geographic linkage). Affiliate stigma is the internalization and psychological responses of perceived courtesy stigma among the associates.ObjectiveThe current study aims to reveal different patterns of perceived courtesy and affiliate stigma among people who are at high risk of contagion of COVID-19, and to examine the possible risk factors.MethodA sample including 2813 adults who located in Hubei Province, China (female: n = 2,184, 77.64%; male: n = 629, 22.36%; mean age = 37.85 years, SD = 6.61 years, range = 18-63 years) were employed in the current study, using latent profile analysis for searching stigma profiles.ResultsThree profiles of stigma were found: the "Denier" (35.98%), "Confused moderate" (48.13%) and "Perceiver" (15.89%) displaying the low, moderate and high level of perceived courtesy and affiliate stigma, respectively. Multinomial logistic regression analyses revealed that generally people with a high level of education, perceived threats, anxiety symptoms, and familiarity with quarantined cases have a high likelihood to be distributed into the "Perceiver".Discussion and conclusionsOur findings highlight the issues of COVID-19-related stigma and provide evidence for launching effective health actions to promote a cohesive society and culture of health. The media can transmit scientific knowledge, promote positive interactions and social cohesion between the stigmatized group and the dominant group, and create spaces for stories that nurture group identification among the implicated people. Future studies should use more representative sample and improve the measures.
| S-EPMC7540249 | biostudies-literature
Project description:IntroductionRecent research underscores the exceptionally young age distribution of Covid-19 deaths in the United States compared with international peers. This brief characterizes how high levels of Covid mortality at midlife ages (45-64) are deeply intertwined with continuing racial inequity in Covid-19 mortality.MethodsMortality data from Minnesota in 2020-2022 were analyzed in June 2022. Death certificate data and published vaccination rates in Minnesota allow vaccination and mortality rates to be observed with greater age and temporal precision than national data.ResultsBlack, Hispanic, and Asian adults under age 65 were all more highly vaccinated than white populations of the same ages during most of Minnesota's substantial and sustained Delta surge and all of the subsequent Omicron surge. However, white mortality rates were lower than those of all other groups. These disparities were extreme; at midlife ages (ages 45-64), during the Omicron period, more highly-vaccinated populations had COVID-19 mortality that was 164% (Asian-American), 115% (Hispanic), or 208% (Black) of white Covid-19 mortality at these ages. In Black, Indigenous, and People of Color (BIPOC) populations as a whole, Covid-19 mortality at ages 55-64 was greater than white mortality at 10 years older.ConclusionsThis discrepancy between vaccination and mortality patterning by race/ethnicity suggests that, if the current period is a "pandemic of the unvaccinated," it also remains a "pandemic of the disadvantaged" in ways that can decouple from vaccination rates. This result implies an urgent need to center health equity in the development of Covid-19 policy measures.
| S-EPMC8923115 | biostudies-literature