Trend in COVID-19 vaccination among people with diabetes: A short study from India.
Ontology highlight
ABSTRACT:
SUBMITTER: Nachimuthu S
PROVIDER: S-EPMC8239314 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: Not available
| S-EPMC8032917 | biostudies-literature
Project description:High throughput sequencing is performed on mRNA isolated from whole blood of adult Covid-19 patients, bacterial coinfection with Covid-19 and healthy controls in a South Indian cohort. Samples were collected from individuals at the time of hospitalization or visit to clinic. The Covid-19 samples are categorized by severeity.
2022-02-22 | GSE196822 | GEO
Project description:To assess the current epidemic trend of COVID-19/SARS-CoV-2 in India, the epidemic dynamics of COVID-19 cases in India in terms of Case Fatality Rate (CFR), Case Recovery Rate (CRR) and Mortality rate (MR) COVID-19 have been evaluated during Lockdown-1. The analysis includes (i) epidemic curve of Covid-19 cases (ii) demographic analysis (iii) calculation of the CFR and CRR by different methods (iv) calculation of MR (v) Geo-temporal analysis (vi) epidemiological transmission factor (vii) evaluation of the effects and impact of infection, prevention and control in India. A total of 10,815 COVID-19 confirmed cases have been reported in 31 states/union territories as of April 14, 2020 with 9272 active cases (85.73%), 1190 cured/discharged (11%), and 353 deaths (3.23%). Among confirmed cases, most cases (59%) are aged 20-49 which is working age in India and 76% cases are reported for men. The median age of Indian COVID-19 patients found to be 39. As of April 14, the CFR per total cases in India is 3.32% and per closed cases is 23.27%. The CRR per total cases in India is 11.00% and per closed cases is 76.72%, which indicates that the recovery rate of COVID-19 is more than the fatality rate in India. The prevention and control measures taken by the state and central governments at all levels and measure of maintenance of social distancing by people have resulted in effective curbing in the COVID-19 transmission in India.
| S-EPMC7309423 | biostudies-literature
Project description: Not available
| S-EPMC7885981 | biostudies-literature
Project description:BackgroundHesitancy to receive COVID-19 vaccination is a major public health concern. COVID-19 vaccine willingness and the factors contributing to willingness in adults with multiple sclerosis (MS) is unknown. We administered an online survey from 1 December 2020 to 7 January 2021 to adults with MS to estimate COVID-19 vaccine willingness among adults with MS. Bivariate analysis with chi-square testing compared categorical variables associated with vaccine willingness.ResultsOf 401 respondents, 70.1% were willing to receive an authorized COVID-19 vaccination if it was available to them, 22.7% were unsure, and 7.2% were unwilling. The most frequent concern for those unsure was vaccine safety. Vaccine willingness was associated with increased perceived personal risk of COVID-19 (χ2 = 45.4; p < 0.0001), prior influenza vaccine acceptance (χ2 = 97.6; p < 0.0001), higher educational level (χ2 = 50.2; p < 0.0001), and if respondents discussed or planned to discuss the COVID-19 vaccine with their neurologists (χ2 = 64.3; p < 0.0001).ConclusionWhile COVID-19 vaccination willingness is high among people with MS, nearly 30% were either unwilling or unsure about being vaccinated. Neurologists should be aware of patient-centered factors associated with COVID-19 vaccine willingness and address COVID-19 vaccine safety concerns in discussions with their vaccine-unsure MS patients.
| S-EPMC8172949 | biostudies-literature
Project description: Not available
| S-EPMC8248922 | biostudies-literature
Project description:As the outbreak of coronavirus disease 2019 (COVID-19) is rapidly spreading in different parts of India, a reliable forecast for the cumulative confirmed cases and the number of deaths can be helpful for policymakers in making the decisions for utilizing available resources in the country. Recently, various mathematical models have been used to predict the outbreak of COVID-19 worldwide and also in India. In this article we use exponential, logistic, Gompertz growth and autoregressive integrated moving average (ARIMA) models to predict the spread of COVID-19 in India after the announcement of various unlock phases. The mean absolute percentage error and root mean square error comparative measures were used to check the goodness-of-fit of the growth models and Akaike information criterion for ARIMA model selection. Using COVID-19 pandemic data up to 20 December 2020 from India and its five most affected states (Maharashtra, Karnataka, Andhra Pradesh, Tamil Nadu and Kerala), we report 15-days-ahead forecasts for cumulative confirmed cases and the number of deaths. Based on available data, we found that the ARIMA model is the best-fitting model for COVID-19 cases in India and its most affected states.
| S-EPMC8194983 | biostudies-literature
Project description: Not available
| S-EPMC8133530 | biostudies-literature
Project description:Early in the COVID-19 pandemic, type 2 diabetes (T2D) was marked as a risk-factor for severe disease. Inflammation is central to the aetiology of both conditions where immune responses influence disease course. Identifying at-risk groups through immuno-inflammatory signatures can direct personalised care and help develop potential targets for precision therapy. This observational study characterised immunophenotypic variation associated with COVID-19 severity in T2D. Broad-spectrum immunophenotyping quantified 15 leukocyte populations in circulation from a cohort of 45 hospitalised COVID-19 patients with and without T2D. Lymphocytopenia, of CD8+ lymphocytes, was associated with severe COVID-19 and intensive care admission in non-diabetic and T2D patients. A morphological anomaly of increased monocyte size and monocytopenia of classical monocytes were specifically associated with severe COVID-19 in patients with T2D requiring intensive care. Over-expression of inflammatory markers reminiscent of the type-1 interferon pathway underlaid the immunophenotype associated with T2D. These changes may contribute to severity of COVID-19 in T2D. These findings show characteristics of severe COVID-19 in T2D as well as provide evidence that type-1 interferons may be actionable targets for future studies.
| S-SCDT-EMM-2020-13038 | biostudies-other