Responsive and agile vaccination strategies against COVID-19 in India.
Ontology highlight
ABSTRACT:
SUBMITTER: Mandal S
PROVIDER: S-EPMC8248922 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
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:ObjectiveWe undertook the study to present a comprehensive overview of COVID-19 related measures, largely centred around the development of vaccination related policies, their implementation and challenges faced in the vaccination drive in India.MethodsA targeted review of literature was conducted to collect relevant data from official government documents, national as well as international databases, media reports and published research articles. The data were summarized to assess Indian government's vaccination campaign and its outcomes as a response to COVID-19 pandemic.ResultsThe five-point strategy adopted by government of India was "COVID appropriate behaviour, test, track, treat and vaccinate". With respect to vaccination, there have been periodic shifts in the policies in terms of eligible beneficiaries, procurement, and distribution plans, import and export strategy, involvement of private sector and use of technology. The government utilized technology for facilitating vaccination for the beneficiaries and monitoring vaccination coverage.ConclusionThe monopoly of central government in vaccine procurement resulted in bulk orders at low price rates. However, the implementation of liberalized policy led to differential pricing and delayed achievement of set targets. The population preference for free vaccines and low profit margins for the private sector due to price caps resulted in a limited contribution of the dominant private health sector of the country. A wavering pattern was observed in the vaccination coverage, which was related majorly to vaccine availability and hesitancy. The campaign will require consistent monitoring for timely identification of bottlenecks for the lifesaving initiative.
| S-EPMC9069978 | biostudies-literature
Project description:Messenger RNA (mRNA) vaccines represent a new class of vaccines that has been shown to be highly effective during the COVID-19 pandemic and that holds great potential for other preventative and therapeutic applications. Understanding the underlying mechanisms of the immune responses induced by this novel vaccine type and their relation to vaccine responses might help to further refine and optimize future vaccine design. In this study, we conducted an in-depth analysis of the blood transcriptome before and 24h after second and third vaccination with licensed mRNA vaccines against COVID-19 in humans, following a prime vaccination with either mRNA or ChAdOx vaccines. Utilizing an unsupervised weighted gene correlation network analysis, we identified distinct gene networks of co-varying genes characterized by either an expressional up- or down-regulation in response to vaccination. Down-regulated networks were associated with cell metabolic processes and regulation of transcription factors, while up-regulated networks were associated with myeloid differentiation, antigen presentation, and antiviral, interferon-driven pathways. Within this interferon-associated network, we identified highly connected hub genes such as STAT2 and RIGI, potentially playing important regulatory roles in the vaccine-induced immune response. The expression profile of this network significantly correlated with S1-specific IgG levels at the follow-up visit in vaccinated individuals. Those findings could be corroborated in an independent cohort of mRNA vaccine recipients. Collectively, insights from this study might contribute to current research endeavors aimed at further enhancing/ or optimizing vaccine-induced immunity.
2024-01-29 | GSE247401 | GEO
Project description:Background and objective The impact of COVID-19 infection and the effect of COVID-19 vaccinations on patients with demyelinating central nervous system disease in low middle income countries (LMIC's) have not been reported in detail earlier. We sought to identify risk factors associated with COVID-19 infection and the role of vaccination in order to develop management guidelines relevant to our patients. Methods A total of 621 patients from our registry that included 297 MS and 324 non MS disorders (Aquaporin- 4 antibody positive [50], Myelin oligodendrocyte glycoprotein antibody positive [81], seronegative [162] and clinically isolated syndrome [31]) were contacted. COVID-19 infection and vaccination status were queried. Patients who self reported COVID-19 infection based on a positive RT PCR report were compared with non infected patients to identify factors associated with susceptibility for COVID-19 infection. Univariate and multivariate analysis of potential risk factors included demographic and clinical features, body mass index (BMI), presence of comorbidities, absolute lymphocyte count, treatment types and vaccination status. Results Sixty seven patients with MS and 27 with non MS disorders developed COVID-19 infection. Among them 81 patients had mild infection and remained quarantined at home. All 13 patients who needed hospitalization recovered. Vaccination status was known in 582 patients among whom 69.8% had completed or taken one dose of vaccine at the time of inquiry. Majority of treated patients (61.3%) were on nonspecific immunosuppressants. In univariate analysis, presence of ≥1 comorbidity was significantly associated with COVID-19 infection in both MS (p value 0.01, OR-2.28, 95%CI- 1.18- 4.4) and non MS patients (p- 0.001, OR-4.4, 95% CI-1.88-10.24). In the latter, BMI ≥ 30 (p-0.04, OR-3.27, 95% CI- 0.98- 10.87) and EDSS score ≥ 3 (p-0.02, OR- 2.59,95% CI- 1.08- 6.23) were other significant associations. History of prior COVID-19 vaccination was associated with reduced frequency of COVID- 19 infection among MS (p- 0.001,OR- 0.24,95% CI- 0.13- 0.43) and non MS patients (p- 0.0001,OR-0.14, 95% CI- 0.058- 0.35). In multivariate analysis presence of comorbidities significantly increased and prior vaccination significantly reduced frequency of COVID-19 infection for both MS and related disorders. Concurrent disease modifying treatments showed a trend for association with infection. In the unvaccinated group, patients on disease modifying treatment were significantly at risk of infection, 81.5% unvaccinated and treated versus 18.5% who were unvaccinated and untreated (p- 0.0001, OR-10.1, 95% CI-0.56-2.11). Conclusion Frequency and severity of COVID-19 infection was low among our patient cohort. Higher rate of infection in the treated group was significantly seen among unvaccinated patients. Our preliminary results suggests that in LMIC's, where “off label therapies” with inexpensive immunosuppressives are the main disease modifying drugs, mRNA vaccinations appear safe and effective against severe COVID-19 infection.
| S-EPMC9252866 | biostudies-literature
Project description: Not available
| S-EPMC7906735 | biostudies-literature
Project description:BackgroundUnderreporting cases of infectious diseases poses a major challenge in the analysis of their epidemiological characteristics and dynamical aspects. Without accurate numerical estimates it is difficult to precisely quantify the proportions of severe and critical cases, as well as the mortality rate. Such estimates can be provided for instance by testing the presence of the virus. However, during an ongoing epidemic, such tests' implementation is a daunting task. This work addresses this issue by presenting a methodology to estimate underreported infections based on approximations of the stable rates of hospitalization and death.MethodsWe present a novel methodology for the stable rate estimation of hospitalization and death related to the Corona Virus Disease 2019 (COVID-19) using publicly available reports from various distinct communities. These rates are then used to estimate underreported infections on the corresponding areas by making use of reported daily hospitalizations and deaths. The impact of underreporting infections on vaccination strategies is estimated under different disease-transmission scenarios using a Susceptible-Exposed-Infective-Removed-like (SEIR) epidemiological model.ResultsFor the considered locations, during the period of study, the estimations suggest that the number of infected individuals could reach 30% of the population of these places, representing, in some cases, more than six times the observed numbers. These results are in close agreement with estimates from independent seroprevalence studies, thus providing a strong validation of the proposed methodology. Moreover, the presence of large numbers of underreported infections can reduce the perceived impact of vaccination strategies in reducing rates of mortality and hospitalization.ConclusionspBy using the proposed methodology and employing a judiciously chosen data analysis implementation, we estimate COVID-19 underreporting from publicly available data. This leads to a powerful way of quantifying underreporting impact on the efficacy of vaccination strategies. As a byproduct, we evaluate the impact of underreporting in the designing of vaccination strategies.
| S-EPMC8552982 | biostudies-literature
Project description:RNA was extracted from whole blood of subjects collected in Tempus tubes prior to COVID-19 mRNA booster vaccination. D01 and D21 correspond to samples collected at pre-dose 1 and pre-dose 2 respectively. RNA was also extracted from blood collected at indicated time points post-vaccination. DB1, DB2, DB4 and DB7 correspond to booster day 1 (pre-booster), booster day 2, booster day 4 and booster day 7 respectively. The case subject experienced cardiac complication following mRNA booster vaccination. We performed gene expression analysis of case versus controls over time.
2023-03-20 | E-MTAB-12829 | biostudies-arrayexpress
Project description:BackgroundVaccine is supposed to be the most effective means to prevent COVID-19 as it may not only save lives but also reduce productivity loss due to resuming pre-pandemic activities. Providing the results of economic evaluation for mass vaccination is of paramount importance for all stakeholders worldwide.MethodsWe developed a Markov decision tree for the economic evaluation of mass vaccination against COVID-19. The effectiveness of reducing outcomes after the administration of three COVID-19 vaccines (BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and AZD1222 (Oxford-AstraZeneca)) were modelled with empirical parameters obtained from literatures. The direct cost of vaccine and COVID-19 related medical cost, the indirect cost of productivity loss due to vaccine jabs and hospitalization, and the productivity loss were accumulated given different vaccination scenarios. We reported the incremental cost-utility ratio and benefit/cost (B/C) ratio of three vaccines compared to no vaccination with a probabilistic approach.ResultsModerna and Pfizer vaccines won the greatest effectiveness among the three vaccines under consideration. After taking both direct and indirect costs into account, all of the three vaccines dominated no vaccination strategy. The results of B/C ratio show that one dollar invested in vaccine would have USD $13, USD $23, and USD $28 in return for Moderna, Pfizer, and AstraZeneca, respectively when health and education loss are considered. The corresponding figures taking value of the statistical life into account were USD $176, USD $300, and USD $443.ConclusionMass vaccination against COVID-19 with three current available vaccines is cost-saving for gaining more lives and less cost incurred.
| S-EPMC8148613 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) is an on-going pandemic caused by the SARS-coronavirus-2 (SARS-CoV-2) which targets the respiratory system of humans. The published data show that children, unlike adults, are less susceptible to contracting the disease. This article aims at understanding why children constitute a minor group among hospitalized COVID-19 patients. Here, we hypothesize that the measles, mumps, and rubella (MMR) vaccine could provide a broad neutralizing antibody against numbers of diseases, including COVID-19. Our hypothesis is based on the 30 amino acid sequence homology between the SARS-CoV-2 Spike (S) glycoprotein (PDB: 6VSB) of both the measles virus fusion (F1) glycoprotein (PDB: 5YXW_B) and the rubella virus envelope (E1) glycoprotein (PDB: 4ADG_A). Computational analysis of the homologous region detected the sequence as antigenic epitopes in both measles and rubella. Therefore, we believe that humoral immunity, created through the MMR vaccination, provides children with advantageous protection against COVID-19 as well, however, an experimental analysis is required.
| S-EPMC7292051 | biostudies-literature
Project description: Not available
| S-EPMC8683117 | biostudies-literature