Browse
Submit Data
Databases
API
Help

Dataset Information

15 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Significance of SARS-CoV-2 specific antibody testing during COVID-19 vaccine allocation.

ABSTRACT:

Objective

To assess the value of using SARS-CoV-2 specific antibody testing to prioritize the vaccination of susceptible individuals as part of a COVID-19 vaccine distribution plan when vaccine supply is limited.

Methods

An extended susceptible-infected-recovered (SIR) compartmental model was used to simulate COVID-19 spread when considering diagnosis, isolation, and vaccination of a cohort of 1 million individuals. The scenarios modeled represented 4 pandemic severity scenarios and various times when the vaccine becomes available during the pandemic. Eligible individuals have a probability p of receiving antibody testing prior to vaccination (p = 0, 0.25, 0.5, 0.75, and 1). The vaccine was modeled as a single dose vaccine with 90% and 70% efficacy. The value of serology testing was evaluated by comparing the infection attack rate, peak infections, peak day, and deaths.

Results

The use of antibody testing to prioritize the allocation of limited vaccines reduces infection attack rates and deaths. The size of the reduction depends on when the vaccine becomes available relative to the infection peak day. The largest percentage reduction in cases and deaths occurs when the vaccine is deployed before and close to the infection peak day. The reduction in the number of cases and deaths diminishes as vaccine deployment is delayed.

Conclusions

Antibody testing as part of the vaccination plan is an effective method to maximize the benefit of a COVID-19 vaccine. Decision-makers need to consider relative timing between the infection peak day and when the vaccine becomes available.

SUBMITTER: Fujimoto AB

PROVIDER: S-EPMC8233959 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

SARS-CoV-2 spike protein enhances MAP4K3/GLK-induced ACE2 stability in COVID-19

Project description:ACE2 on epithelial cells is the SARS-CoV-2 entry receptor. Single-cell RNA-sequencing data derived from two COVID-19 cohorts revealed that MAP4K3/GLK-positive epithelial cells were increased in patients. SARS-CoV-2-induced GLK overexpression in epithelial cells correlated with COVID-19 severity and vesicle secretion. GLK overexpression induced the epithelial cell-derived exosomes containing ACE2; the GLK-induced exosomes transported ACE2 proteins to recipient cells, facilitating pseudovirus infection. Consistently, ACE2 proteins were increased in the serum exosomes from another COVID-19 cohort. Remarkably, SARS-CoV-2 spike protein stimulated GLK, and GLK stabilized ACE2 in epithelial cells. Mechanistically, GLK phosphorylated ACE2 at two serine residues (Ser776, Ser783), leading to dissociation of ACE2 from its E3 ligase UBR4. Reduction of UBR4-induced Lys48-linked ubiquitination at three lysine residues (Lys26, Lys112, Lys114) of ACE2 prevented its degradation. Furthermore, SARS-CoV-2 pseudovirus or live virus infection in humanized ACE2 mice induced GLK and ACE2 protein levels, as well as ACE2-containing exosomes. Collectively, ACE2 stabilization by SARS-CoV-2-induced MAP4K3/GLK may contribute to the pathogenesis of COVID-19.

| S-SCDT-EMM-2022-15904 | biostudies-other

Cross-reactive Antibody Response to mRNA SARS-CoV-2 Vaccine After Recent COVID-19-Specific Monoclonal Antibody Therapy.

Project description:The efficacy of coronavirus disease 2019 (COVID-19) vaccines administered after COVID-19-specific monoclonal antibody is unknown, and "antibody interference" might hinder immune responses leading to vaccine failure. In an institutional review board-approved prospective study, we found that an individual who received mRNA COVID-19 vaccination <40 days after COVID-19-specific monoclonal antibody therapy for symptomatic COVID-19 had similar postvaccine antibody responses to SARS-CoV-2 receptor binding domain (RBD) for 4 important SARS-CoV-2 variants (B.1, B.1.1.7, B.1.351, and P.1) as other participants who were also vaccinated following COVID-19. Vaccination against COVID-19 shortly after COVID-19-specific monoclonal antibody can boost and expand antibody protection, questioning the need to delay vaccination in this setting.Trial registrationThe St. Jude Tracking of Viral and Host Factors Associated with COVID-19 study; NCT04362995; https://clinicaltrials.gov/ct2/show/NCT04362995.

| S-EPMC8454518 | biostudies-literature

Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome

Project description: Not available

| S-BSST955 | biostudies-other

COVID-19 mRNA vaccine induced antibody responses against three SARS-CoV-2 variants.

Project description:As SARS-CoV-2 has been circulating for over a year, dozens of vaccine candidates are under development or in clinical use. The BNT162b2 mRNA COVID-19 vaccine induces spike protein-specific neutralizing antibodies associated with protective immunity. The emergence of the B.1.1.7 and B.1.351 variants has raised concerns of reduced vaccine efficacy and increased re-infection rates. Here we show, that after the second dose, the sera of BNT162b2-vaccinated health care workers (n = 180) effectively neutralize the SARS-CoV-2 variant with the D614G substitution and the B.1.1.7 variant, whereas the neutralization of the B.1.351 variant is five-fold reduced. Despite the reduction, 92% of the seronegative vaccinees have a neutralization titre of >20 for the B.1.351 variant indicating some protection. The vaccinees' neutralization titres exceeded those of recovered non-hospitalized COVID-19 patients. Our work provides evidence that the second dose of the BNT162b2 vaccine induces cross-neutralization of at least some of the circulating SARS-CoV-2 variants.

| S-EPMC8239026 | biostudies-literature

Specific COVID-19 Symptoms Correlate with High Antibody Levels against SARS-CoV-2.

Project description:Lasting immunity will be critical for overcoming COVID-19. However, the factors associated with the development of high titers of anti-SARS-CoV-2 Abs and how long those Abs persist remain incompletely defined. In particular, an understanding of the relationship between COVID-19 symptoms and anti-SARS-CoV-2 Abs is limited. To address these unknowns, we quantified serum anti-SARS- CoV-2 Abs in clinically diverse COVID-19 convalescent human subjects 5 wk (n = 113) and 3 mo (n = 79) after symptom resolution with three methods: a novel multiplex assay to quantify IgG against four SARS-CoV-2 Ags, a new SARS-CoV-2 receptor binding domain-angiotensin converting enzyme 2 inhibition assay, and a SARS-CoV-2 neutralizing assay. We then identified clinical and demographic factors, including never-before-assessed COVID-19 symptoms, that consistently correlate with high anti-SARS-CoV-2 Ab levels. We detected anti-SARS-CoV-2 Abs in 98% of COVID-19 convalescent subjects 5 wk after symptom resolution, and Ab levels did not decline at 3 mo. Greater disease severity, older age, male sex, higher body mass index, and higher Charlson Comorbidity Index score correlated with increased anti-SARS-CoV-2 Ab levels. Moreover, we report for the first time (to our knowledge) that COVID-19 symptoms, most consistently fever, body aches, and low appetite, correlate with higher anti-SARS-CoV-2 Ab levels. Our results provide robust and new insights into the development and persistence of anti-SARS-CoV-2 Abs.

| S-EPMC8452279 | biostudies-literature

Disease severity dictates SARS-CoV-2-specific neutralizing antibody responses in COVID-19.

Project description:COVID-19 patients exhibit differential disease severity after SARS-CoV-2 infection. It is currently unknown as to the correlation between the magnitude of neutralizing antibody (NAb) responses and the disease severity in COVID-19 patients. In a cohort of 59 recovered patients with disease severity including severe, moderate, mild, and asymptomatic, we observed the positive correlation between serum neutralizing capacity and disease severity, in particular, the highest NAb capacity in sera from the patients with severe disease, while a lack of ability of asymptomatic patients to mount competent NAbs. Furthermore, the compositions of NAb subtypes were also different between recovered patients with severe symptoms and with mild-to-moderate symptoms. These results reveal the tremendous heterogeneity of SARS-CoV-2-specific NAb responses and their correlations to disease severity, highlighting the needs of future vaccination in COVID-19 patients recovered from asymptomatic or mild illness.

| S-EPMC7464057 | biostudies-literature

Return to normal pre-COVID-19 life is delayed by inequitable vaccine allocation and SARS-CoV-2 variants.

Project description:As a result of the COVID-19 pandemic, whether and when the world can reach herd immunity and return to normal life and a strategy for accelerating vaccination programmes constitute major concerns. We employed Metropolis-Hastings sampling and an epidemic model to design experiments based on the current vaccinations administered and a more equitable vaccine allocation scenario. The results show that most high-income countries can reach herd immunity in less than 1 year, whereas low-income countries should reach this state after more than 3 years. With a more equitable vaccine allocation strategy, global herd immunity can be reached in 2021. However, the spread of SARS-CoV-2 variants means that an additional 83 days will be needed to reach global herd immunity and that the number of cumulative cases will increase by 113.37% in 2021. With the more equitable vaccine allocation scenario, the number of cumulative cases will increase by only 5.70% without additional vaccine doses. As SARS-CoV-2 variants arise, herd immunity could be delayed to the point that a return to normal life is theoretically impossible in 2021. Nevertheless, a more equitable global vaccine allocation strategy, such as providing rapid vaccine assistance to low-income countries/regions, can improve the prevention of COVID-19 infection even though the virus could mutate.

| S-EPMC9058660 | biostudies-literature

Stochastic optimization for vaccine and testing kit allocation for the COVID-19 pandemic.

Project description:We present a formal mathematical modeling framework for a multi-agent sequential decision problem during an epidemic. The problem is formulated as a collaboration between a vaccination agent and learning agent to allocate stockpiles of vaccines and tests to a set of zones under various types of uncertainty. The model is able to capture passive information processes and maintain beliefs over the uncertain state of the world. We designed a parameterized direct lookahead approximation which is robust and scalable under different scenarios, resource scarcity, and beliefs about the environment. We design a test allocation policy designed to capture the value of information and demonstrate that it outperforms other learning policies when there is an extreme shortage of resources (information is scarce). We simulate the model with two scenarios including a resource allocation problem to each state in the United States and another for the nursing homes in Nevada. The US example demonstrates the scalability of the model and the nursing home example demonstrates the robustness under extreme resource shortages.

| S-EPMC8580866 | biostudies-literature

Linear epitope-specific IgG responses to SARS-CoV-2 and related human coronaviruses in human COVID-19 convalescent sera

Project description:The on-going COVID-19 pandemic requires a deeper understanding of the long-term antibody responses that persist following SARS-CoV-2 infection. To that end, we determined epitope-specific IgG antibody responses in COVID-19 convalescent sera collected at 5 months post-diagnosis and compared that to sera from naïve individuals. Each serum sample was reacted with a high-density peptide microarray representing the complete proteome of SARS-CoV-2 as 15 mer peptides with 11 amino acid overlap and homologs of spike glycoprotein, nucleoprotein, membrane protein, and envelope small membrane protein from related human coronaviruses. Binding signatures were compared between COVID-19 convalescent patients and naïve individuals using the web service tool EPIphany.

2022-02-05 | E-MTAB-10740 | biostudies-arrayexpress

Antibody and T-cellular response to COVID-19 booster vaccine in SARS-CoV-1 survivors.

Project description:The severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) survivors are more likely to produce a potent immune response to SARS-CoV-2 after booster vaccination. We assessed humoral and T cell responses against SARS-CoV-2 in previously vaccinated SARS-CoV-1 survivors and naïve healthy individuals (NHIs) after a booster Ad5-nCoV dose. Boosted SARS-CoV-1 survivors had a high neutralization of SARS-CoV-2 Wuhan-Hu-1 (WA1), Beta, and Delta but is limited to Omicron subvariants (BA.1, BA.2, BA.2.12.1, and BA.4/BA.5). Most boosted SARS-CoV-1 survivors had robust SARS-CoV-2-specific CD4+ and CD8+ T cell responses. While booster vaccination in NHIs elicited less or ineffective neutralization of WA1, Beta, and Delta, and none of them induced neutralizing antibodies against Omicron subvariants. However, they developed comparable SARS-CoV-2-specific T cell responses compared to boosted SARS-CoV-1 survivors. These findings suggest that boosted Ad5-nCoV would not elicit effective neutralizing antibodies against Omicron subvariants in SARS-CoV-1 survivors and NHIs but induced comparable robust T cell responses. Achieving a high antibody titer in SARS-CoV-1 survivors and NHIs is desirable to generate broad neutralization.

| S-EPMC9423872 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data