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.
Project description:BackgroundBreakthrough coronavirus disease 2019 (COVID-19) may occur in fully vaccinated persons.MethodsWe assessed the clinical outcomes of breakthrough COVID-19 in fully vaccinated individuals.ResultsIn 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. Antispike monoclonal antibody treatment was significantly associated with a lower risk of hospitalization (odds ratio, 0.227; 95% confidence interval, 0.128-0.403; P < .001). The number needed to treat (NNT) to prevent 1 hospitalization was 225 among the lowest risk patient group compared with NNT of 4 among those with highest numbers of medical comorbidity.ConclusionsMonoclonal antibody treatment is associated with reduced hospitalization in vaccinated high-risk persons with mild to moderate COVID-19.
Project description:BackgroundA definition of the immunological features of COVID-19 pneumonia is needed to support clinical management of aged patients. In this study, we characterized the humoral and cellular immune responses in presence or absence of SARS-CoV-2 vaccination, in aged patients admitted to the IRCCS San Raffaele Hospital (Italy) for COVID-19 pneumonia between November 2021 and March 2022.MethodsThe study was approved by local authorities. Disease severity was evaluated according to WHO guidelines. We tested: (A) anti-SARS-CoV-2 humoral response (anti-RBD-S IgG, anti-S IgM, anti-N IgG, neutralizing activity against Delta, BA1, BA4/5 variants); (B) Lymphocyte B, CD4 and CD8 T-cell phenotype; (C) plasma cytokines. The impact of vaccine administration and different variants on the immunological responses was evaluated using standard linear regression models and Tobit models for censored outcomes adjusted for age, vaccine doses and gender.ResultWe studied 47 aged patients (median age 78.41), 22 (47%) female, 33 (70%) older than 70 years (elderly). At hospital admission, 36% were unvaccinated (VACno), whilst 63% had received 2 (VAC2) or 3 doses (VAC3) of vaccine. During hospitalization, WHO score > 5 was higher in unvaccinated (14% in VAC3 vs. 43% in VAC2 and 44% VACno). Independently from vaccination doses and gender, elderly had overall reduced anti-SARS-CoV-2 humoral response (IgG-RBD-S, p = 0.0075). By linear regression, the anti-RBD-S (p = 0.0060), B (p = 0.0079), CD8 (p = 0.0043) and Th2 cell counts (p = 0.0131) were higher in VAC2 + 3 compared to VACno. Delta variant was the most representative in VAC2 (n = 13/18, 72%), detected in 41% of VACno, whereas undetected in VAC3, and anti-RBD-S production was higher in VAC2 vs. VACno (p = 0.0001), alongside neutralization against Delta (p = 0141), BA1 (p = 0.0255), BA4/5 (p = 0.0162). Infections with Delta also drove an increase of pro-inflammatory cytokines (IFN-α, p = 0.0463; IL-6, p = 0.0010).ConclusionsAdministration of 3 vaccination doses reduces the severe symptomatology in aged and elderly. Vaccination showed a strong association with anti-SARS-CoV-2 humoral response and an expansion of Th2 T-cells populations, independently of age. Delta variants and number of vaccine doses affected the magnitude of the humoral response against the original SARS-CoV-2 and emerging variants. A systematic surveillance of the emerging variants is paramount to define future vaccination strategies.
Project description:ImportanceAssociations have been found between COVID-19 and subsequent mental illness in both hospital- and population-based studies. However, evidence regarding which mental illnesses are associated with COVID-19 by vaccination status in these populations is limited.ObjectiveTo determine which mental illnesses are associated with diagnosed COVID-19 by vaccination status in both hospitalized patients and the general population.Design, setting, and participantsThis study was conducted in 3 cohorts, 1 before vaccine availability followed during the wild-type/Alpha variant eras (January 2020-June 2021) and 2 (vaccinated and unvaccinated) during the Delta variant era (June-December 2021). With National Health Service England approval, OpenSAFELY-TPP was used to access linked data from 24 million people registered with general practices in England using TPP SystmOne. People registered with a GP in England for at least 6 months and alive with known age between 18 and 110 years, sex, deprivation index information, and region at baseline were included. People were excluded if they had COVID-19 before baseline. Data were analyzed from July 2022 to June 2024.ExposureConfirmed COVID-19 diagnosis recorded in primary care secondary care, testing data, or the death registry.Main outcomes and measuresAdjusted hazard ratios (aHRs) comparing the incidence of mental illnesses after diagnosis of COVID-19 with the incidence before or without COVID-19 for depression, serious mental illness, general anxiety, posttraumatic stress disorder, eating disorders, addiction, self-harm, and suicide.ResultsThe largest cohort, the pre-vaccine availability cohort, included 18 648 606 people (9 363 710 [50.2%] female and 9 284 896 [49.8%] male) with a median (IQR) age of 49 (34-64) years. The vaccinated cohort included 14 035 286 individuals (7 308 556 [52.1%] female and 6 726 730 [47.9%] male) with a median (IQR) age of 53 (38-67) years. The unvaccinated cohort included 3 242 215 individuals (1 363 401 [42.1%] female and 1 878 814 [57.9%] male) with a median (IQR) age of 35 (27-46) years. Incidence of most outcomes was elevated during weeks 1 through 4 after COVID-19 diagnosis, compared with before or without COVID-19, in each cohort. Incidence of mental illnesses was lower in the vaccinated cohort compared with the pre-vaccine availability and unvaccinated cohorts: aHRs for depression and serious mental illness during weeks 1 through 4 after COVID-19 were 1.93 (95% CI, 1.88-1.98) and 1.49 (95% CI, 1.41-1.57) in the pre-vaccine availability cohort and 1.79 (95% CI, 1.68-1.90) and 1.45 (95% CI, 1.27-1.65) in the unvaccinated cohort compared with 1.16 (95% CI, 1.12-1.20) and 0.91 (95% CI, 0.85-0.98) in the vaccinated cohort. Elevation in incidence was higher and persisted longer after hospitalization for COVID-19.Conclusions and relevanceIn this study, incidence of mental illnesses was elevated for up to a year following severe COVID-19 in unvaccinated people. These findings suggest that vaccination may mitigate the adverse effects of COVID-19 on mental health.
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.
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.
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.
Project description:Better understanding the risk factors that exacerbate Covid-19 symptoms and lead to worse health outcomes is vitally important in the public health fight against the virus. One such risk factor that is currently under investigation is air pollution concentrations, with some studies finding statistically significant effects while other studies have found no consistent associations. The aim of this paper is to add to this global evidence base on the potential association between air pollution concentrations and Covid-19 hospitalisations and deaths, by presenting the first study on this topic at the small-area scale in Scotland, United Kingdom. Our study is one of the most comprehensive to date in terms of its temporal coverage, as it includes all hospitalisations and deaths in Scotland between 1st March 2020 and 31st July 2021. We quantify the effects of air pollution on Covid-19 outcomes using a small-area spatial ecological study design, with inference using Bayesian hierarchical models that allow for the residual spatial correlation present in the data. A key advantage of our study is its extensive sensitivity analyses, which examines the robustness of the results to our modelling assumptions. We find clear evidence that PM2.5 concentrations are associated with hospital admissions, with a 1 μgm-3 increase in concentrations being associated with between a 7.4% and a 9.3% increase in hospitalisations. In addition, we find some evidence that PM2.5 concentrations are associated with deaths, with a 1 μgm-3 increase in concentrations being associated with between a 2.9% and a 10.3% increase in deaths.