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Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers

Proceedings of the National Academy of Sciences(2021)10.1073/pnas.2025786118Source: DataRank Database

Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers is a research paper published in Proceedings of the National Academy of Sciences (2021). On theSindex it has a DataRank of 0.813. It has been cited 225 times.

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0.813DataRank · unranked

Scored on demand from live citation data

Open Access225 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)Impact (FWCI 17.09)OA: hybridTopics (59)Linked Datasets (8)DataCite Reuse (8)IDs (PubMed, OpenAlex)SDGs (2)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.813

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (3)

Gerardo Chowell ORCID,Michael Springborn ORCID,Jack H. Buckner ORCID

Live enrichment

PubMed:33811185 OpenAlex:https://openalex.org/W3140873963

National Science Foundation

Grant: 1650042

University of California

Grant: R00RG2419

National Science Foundation

Grant: 2026797

Collaborative Research: RAPID: RTEM: Rapid Testing as Multi-fidelity Data Collection for Epidemic Modeling

National Science Foundation

Grant: 2034003

Collaborative Research: RAPID: Behavioral Epidemic Modeling For COVID-19 Containment

HHS | NIH | National Institute of Allergy and Infectious Diseases

Grant: R01 GM 130900

National Institutes of Health

Grant: 3R01GM130900-01A1S1

Ebola modeling: behavior, asymptomatic infection, and contacts (2019-nCoV Admin Supplement)

FWCI

17.09

Citation Percentile

1.0%

Citation Trend

2020

2021

2022

2023

2024

2025

2026

hybridLicense: cc-by

journalhttps://www.pnas.org/doi/pdf/10.1073/pnas.2025786118

publisherhttps://www.pnas.org/doi/pdf/10.1073/pnas.2025786118

publisherhttp://www.pnas.org/syndication/doi/10.1073/pnas.2025786118

publisherhttps://pnas.org/doi/pdf/10.1073/pnas.2025786118

journalhttps://doi.org/10.1073/pnas.2025786118

Fields of Study

COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchInfluenza Virus Research Studies0301 basic medicine03 medical and health sciences0303 health sciences

MeSH Terms

Physical DistancingCOVID-19COVID-19 VaccinesAdultAgedHealth PersonnelHumansMiddle AgedVaccinationModels, Immunological

Keywords

Software deploymentPrioritizationSocial distanceCoronavirus disease 2019 (COVID-19)PandemicPopulationBusinessRisk analysis (engineering)Environmental healthMedicineDiseaseComputer scienceInfectious disease (medical specialty)Process managementAdultand promotion of well-beingCOVID-19 VaccinesHealth PersonnelPhysical Distancing613ArticleVaccine RelatedModelsBiodefense616Humansessential workersAgedPreventionVaccinationModels, ImmunologicalCOVID-19Biological SciencesMiddle AgedPrevention of disease and conditionsEmerging Infectious DiseasesInfectious DiseasesGood Health and Well BeingImmunological3.4 Vaccinesvaccine prioritizationImmunizationInfection

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being

Additional file 1 of COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies

10.6084/m9.figshare.19367708.v1figshare

Additional file 1 of COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies

10.6084/m9.figshare.19367708figshare

Additional file 2 of COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies

10.6084/m9.figshare.19367711.v1figshare

Additional file 2 of COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies

10.6084/m9.figshare.19367711figshare

Additional file 1 of Inequality in the distribution of Covid-19 vaccine: a systematic review

10.6084/m9.figshare.20745413.v1figshare

Additional file 1 of Inequality in the distribution of Covid-19 vaccine: a systematic review

10.6084/m9.figshare.20745413figshare

Additional file 3 of COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies

10.6084/m9.figshare.19367714.v1figshare

Additional file 3 of COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies

10.6084/m9.figshare.19367714figshare