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How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19

European Journal of Epidemiology(2021)10.1007/s10654-021-00727-7Source: DataRank Database

How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19 is a research paper published in European Journal of Epidemiology (2021). On theSindex it has a DataRank of 0. It has been cited 142 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access142 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 7.68)OA: hybridTopics (36)IDs (PubMed, PMC, OpenAlex)Annotations (1)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 (11)

Xueting Qiu ORCID,Éva Rumpler ORCID,Lee Kennedy‐Shaffer ORCID,Rebecca Kahn ORCID,Keya Joshi ORCID

Live enrichment

PubMed:33634345 PMC:PMC7906244 OpenAlex:https://openalex.org/W3129344682

NIGMS NIH HHS

Grant: U54 GM088558

NIAID NIH HHS

Grant: T32 AI007535

NCI NIH HHS

Grant: U01 CA261277

Morris-Singer Fund

FWCI

7.68

Citation Percentile

1.0%

Citation Trend

2021

2022

2023

2024

2025

2026

hybridLicense: cc-by

journalhttps://link.springer.com/content/pdf/10.1007/s10654-021-00727-7.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/s10654-021-00727-7.pdf

journalhttps://doi.org/10.1007/s10654-021-00727-7

repositoryhttps://pubmed.ncbi.nlm.nih.gov/33634345

repositoryhttp://infoscience.epfl.ch/record/284531

Fields of Study

SARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studiesCOVID-19 Clinical Research StudiesBiasCOVID-19HumansReproducibility of ResultsResearch DesignSARS-CoV-2Seroepidemiologic Studies

MeSH Terms

COVID-19SARS-CoV-2HumansResearch DesignReproducibility of ResultsBiasSeroepidemiologic Studies

Keywords

Observational studyMedicineConfoundingPandemicPublic healthEpidemiologyPopulationSelection biasCoronavirus disease 2019 (COVID-19)Environmental healthTransmissibility (structural dynamics)DiseaseInfectious disease (medical specialty)PathologyMeasurement errorMisclassificationObservational DataEpidemiological BiasesCovid-19

Sustainable Development Goals

SDG 0: Good health and well-being

How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19

FAIR Checklist

Authors (11)

Funding (4 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)