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Predictive performance of international COVID-19 mortality forecasting models

medRxiv(2020)10.1101/2020.07.13.20151233Source: DataRank Database

Predictive performance of international COVID-19 mortality forecasting models is a research paper published in medRxiv (2020). On theSindex it has a DataRank of 0. It has been cited 58 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access58 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)OA: greenTopics (25)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Patrick Liu ORCID,Emmanuela Gakidou ORCID,the IHME COVID19 Model Comparison Team,Joseph Friedman ORCID

Live enrichment

PubMed:33236023 OpenAlex:https://openalex.org/W3043818199

National Institutes of Health

Grant: 5T32GM008042-27

Medical Scientist Training Program

NIGMS NIH HHS

Grant: T32 GM008042

greenLicense: cc-by

repositoryhttps://www.medrxiv.org/content/medrxiv/early/2020/11/19/2020.07.13.20151233.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2020.07.13.20151233

repositoryhttps://doi.org/10.1101/2020.07.13.20151233

repositoryhttps://pubmed.ncbi.nlm.nih.gov/33236023

Fields of Study

COVID-19 epidemiological studiesCOVID-19 Pandemic ImpactsCOVID-19 impact on air quality0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Coronavirus disease 2019 (COVID-19)EconometricsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakEconomicsVirologyComputer scienceMedicineInternal medicineOutbreakModels, StatisticalTime FactorsSARS-CoV-2ScienceQCOVID-19HumansArticleForecasting

Sustainable Development Goals

SDG 3: 3. Good health