@id | ./ |
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name [?] | BY-COVID WP5 T5.2 Baseline Use Case |
@type | Dataset |
description [?] | This publication corresponds to the Research Objects (RO) of the Baseline Use Case proposed in T.5.2 (WP5) in the BY-COVID project on “COVID-19 Vaccine(s) effectiveness in preventing SARS-CoV-2 infection”. |
funder [?] | European Commission |
datePublished [?] | 2023-04-19 |
author [?] | |
conformsTo [?] | |
codeRepository [?] | https://github.com/by-covid/BY-COVID_WP5_T5.2_baseline-use-case |
hasPart [?] |
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distribution [?] | https://github.com/by-covid/BY-COVID_WP5_T5.2_baseline-use-case/archive/refs/heads/main.zip |
identifier [?] | https://doi.org/10.5281/zenodo.6913045 |
cite-as [?] | https://w3id.org/ro/doi/10.5281/zenodo.6913045 |
isBasedOn [?] | |
keywords [?] | COVID-19, vaccines, comparative effectiveness, causal inference, international comparison, SARS-CoV-2, common data model, directed acyclic graph, synthetic data |
license [?] | Creative Commons Attribution 4.0 International |
dateModified [?] | 2023-10-05 |
publisher [?] | BY-COVID |
funding [?] | HORIZON-INFRA-2021-EMERGENCY-01 101046203 |
mentions [?] |
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url [?] | https://by-covid.github.io/BY-COVID_WP5_T5.2_baseline-use-case/ |
version [?] | 1.2.0 |
assesses [?] | Research Question: How effective have the SARS-CoV-2 vaccination programmes been in preventing SARS-CoV-2 infections? |
material [?] | Cohort definition: All individuals (from 5 to 115 years old, included) vaccinated with at least one dose of the SARS-CoV-2 vaccine (any of the available brands) and all individuals eligible to be vaccinated with a documented positive diagnosis (irrespective of the type of test) for a SARS-CoV-2 infection during the data extraction period. |
materialExtent [?] | Inclusion criteria: All people vaccinated with at least one dose of the COVID-19 vaccine (any of the available brands) in an area of residence. Any person eligible to be vaccinated (from 5 to 115 years old, included) with a positive diagnosis (irrespective of the type of test) for SARS-CoV-2 infection (COVID-19) during the period of data extraction. Exclusion criteria: People not eligible for the vaccine (from 0 to 4 years old, included) |
publishingPrinciples [?] | Study Design: An observational retrospective longitudinal study to assess the effectiveness of the SARS-CoV-2 vaccines in preventing SARS-CoV-2 infections using routinely collected social, health and care data from several countries. A causal model was established using Directed Acyclic Graphs (DAGs) to map domain knowledge, theories and assumptions about the causal relationship between exposure and outcome. |
temporalCoverage [?] | Study Period: From the date of the first documented SARS-CoV-2 infection in each country to the most recent date in which data is available at the time of analysis. Roughly from 01-03-2020 to 30-06-2022, depending on the country. |
usageInfo [?] | The scripts (software) included in the publication are offered "as-is", without warranty, and disclaiming liability for damages resulting from using it. The software is released under the CC-BY-4.0 licence, which gives you permission to use the content for almost any purpose (but does not grant you any trademark permissions), so long as you note the license and give credit. |
releaseNotes [?] | - Updated Causal model to eliminate the consideration of 'vaccination_schedule_cd' as a mediator - Adjusted the study period to be consistent with the Study Protocol - Updated 'sex_cd' as a required variable - Added 'chronic_liver_disease_bl' as a comorbidity at the individual level - Updated 'socecon_lvl_cd' at the area level as a recommended variable -Added crosswalks for the definition of 'chronic_liver_disease_bl' in a separate sheet -Updated the 'vaccination_schedule_cd' reference to the 'Vaccine' node in the updated DAG -Updated the description of the 'confirmed_case_dt' and 'previous_infection_dt' variables to clarify the definition and the need for a single registry per person |
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about [?] |
@id | https://ror.org/00k4n6c32 |
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name [?] | European Commission |
@type | Organization |
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funder [?] |
@id | https://orcid.org/0000-0002-6285-8120 |
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name [?] | Francisco Estupiñán-Romero |
@type | Person |
affiliation [?] | Instute for Health Science in Aragon (IACS) |
email [?] | festupinnan.iacs@aragon.es |
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author [?] | |
creator [?] |
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@id | https://orcid.org/0000-0001-7316-6990 |
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name [?] | Nina Van Goethem |
@type | Person |
affiliation [?] | Sciensano |
email [?] | Nina.VanGoethem@sciensano.be |
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author [?] | |
creator [?] |
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@id | https://orcid.org/0000-0002-4409-0664 |
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name [?] | Marjan Meurisse |
@type | Person |
affiliation [?] | Sciensano |
email [?] | Marjan.Meurisse@sciensano.be |
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author [?] | |
creator [?] |
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@id | https://orcid.org/0000-0002-8783-5478 |
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name [?] | Javier González-Galindo |
@type | Person |
affiliation [?] | Instute for Health Science in Aragon (IACS) |
email [?] | jgonzalezga.iacs@aragon.es |
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author [?] | |
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@id | https://orcid.org/0000-0002-0961-3298 |
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name [?] | Enrique Bernal-Delgado |
@type | Person |
affiliation [?] | Instute for Health Science in Aragon (IACS) |
email [?] | ebernal.iacs@aragon.es |
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name [?] | Process Run Crate |
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version [?] | 0.1 |
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@id | vaccine_effectiveness_analytical_pipeline/ |
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name [?] | BY-COVID - WP5 - Baseline Use Case: SARS-CoV-2 vaccine effectiveness assessment - Analytical pipeline |
@type | Dataset |
description [?] | Reproducable analytical pipeline to apply causal inference techniques using distributed observational data |
datePublished [?] | 2023-04-26 |
author [?] | |
version [?] | 1.0.0 |
url [?] | https://github.com/by-covid/BY-COVID_WP5_T5.2_baseline-use-case/tree/main/vaccine_effectiveness_analytical_pipeline |
hasPart [?] |
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@id | vaccine_effectiveness_causal_model/ |
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name [?] | BY-COVID - WP5 - Baseline Use Case: SARS-CoV-2 vaccine effectiveness assessment - Causal Model |
@type | File |
description [?] | Causal model responding to the research question, using a Directed Acyclic Graph |
datePublished [?] | 2023-01-26 |
version [?] | 1.1.0 |
identifier [?] | https://doi.org/10.5281/zenodo.6913045 |
url [?] | https://zenodo.org/record/7572373 |
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@id | vaccine_effectiveness_common_data_model_specification/ |
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name [?] | COVID-19 vaccine(s) effectiveness assessment (synthetic dataset) |
@type | Dataset |
description [?] | Synthetic data set to test the causal model proposed by the baseline use case in BY-COVID WP5 assessing the effectiveness of the COVID-19 vaccine(s) |
datePublished [?] | 2023-01-26 |
version [?] | 1.1.0 |
identifier [?] | https://doi.org/10.5281/zenodo.6913045 |
url [?] | https://zenodo.org/record/7572373 |
creator [?] | |
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distribution [?] | vaccine_effectiveness_synthetic_pop_10k_v.1.1.0 |
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keywords [?] |
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license [?] | Creative Commons Attribution 4.0 International |
mainEntity [?] | Quarto script sourcing consecutive scripts of the analytical pipeline (QMD) |
spatialCoverage [?] | Europe |
subjectOf [?] | Metadata for Common data model specification |
temporalCoverage [?] | 01-01-2020/31-12-2024 |
variableMeasured [?] |
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mainEntity [?] | COVID-19 vaccine effectiveness data model specification dataspice (JSON) |
@id | vaccine_effectiveness_data_management_plan/ |
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name [?] | BY-COVID - WP5 - Baseline Use Case: SARS-CoV-2 vaccine effectiveness assessment - Data Management Plan |
@type | Dataset |
description [?] | Data management plan |
datePublished [?] | 2023-02-09 |
version [?] | 0.0.1 |
identifier [?] | https://doi.org/10.5281/zenodo.7625783 |
url [?] | https://zenodo.org/record/7625784 |
creator [?] | |
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hasPart [?] | BY-COVID WP5 T5.2 Baseline Use Case |
@id | vaccine_effectiveness_study_protocol/ |
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name [?] | BY-COVID - WP5 - Baseline Use Case: SARS-CoV-2 vaccine effectiveness assessment - Study protocol |
@type | Dataset |
description [?] | Study protocol |
datePublished [?] | 2023-04-13 |
version [?] | 1.0.3 |
identifier [?] | https://doi.org/10.5281/zenodo.7551181 |
url [?] | https://zenodo.org/record/7825979 |
creator [?] | |
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@id | vaccine_effectiveness_synthetic_dataset/ |
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name [?] | Common data model specification |
@type | Dataset |
description [?] | following the causal model |
datePublished [?] | 2023-01-26 |
version [?] | 1.1.0 |
identifier [?] | https://doi.org/10.5281/zenodo.6913045 |
url [?] | https://zenodo.org/record/7572373 |
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@id | analytical-pipeline.png |
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name [?] | Diagram of analytical pipeline |
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about [?] | Quarto script sourcing consecutive scripts of the analytical pipeline (QMD) |
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image [?] | Quarto script sourcing consecutive scripts of the analytical pipeline (QMD) |
@id | conceptual-phase.png |
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name [?] | Conceptual phases |
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description [?] | From Causal model, via a data model spec to generation of synthetic data |
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@id | README.md |
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@type | File |
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encodingFormat [?] | text/markdown |
about [?] | BY-COVID WP5 T5.2 Baseline Use Case |
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object [?] | RO-Crate metadata created based on README and dataspice JSON-LD |
@id | https://github.com/by-covid/BY-COVID_WP5_T5.2_baseline-use-case/archive/refs/heads/main.zip |
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encodingFormat [?] | application/zip |
contentSize [?] | 10978259 |
contentUrl [?] | https://github.com/by-covid/BY-COVID_WP5_T5.2_baseline-use-case/archive/refs/heads/main.zip |
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distribution [?] | BY-COVID WP5 T5.2 Baseline Use Case |
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identifier [?] | CC-BY-4.0 |
url [?] | https://creativecommons.org/licenses/by/4.0/ |
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license [?] |
@id | https://by-covid.eu/ |
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name [?] | BY-COVID |
@type | Project |
description [?] | BeYond-COVID, make data from COVID-19 and other infectious diseases open and accessible to everyone |
url [?] | https://by-covid.eu/ |
funding [?] | HORIZON-INFRA-2021-EMERGENCY-01 101046203 |
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publisher [?] | BY-COVID WP5 T5.2 Baseline Use Case |
@id | https://doi.org/10.3030/101046203 |
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name [?] | HORIZON-INFRA-2021-EMERGENCY-01 101046203 |
@type | Grant |
funder [?] | European Commission |
identifier [?] | https://doi.org/10.3030/101046203 |
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funding [?] |
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name [?] | Generating HTML from QMD |
@type | CreateAction |
endTime [?] | 2022-07-27T12:00:00+01:00 |
instrument [?] | Quarto |
object [?] | COVID-19 vaccine effectiveness causal model v.1.1.0 (QMD) |
result [?] | COVID-19 vaccine effectiveness causal model v.1.1.0 (HTML) |
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mentions [?] | BY-COVID WP5 T5.2 Baseline Use Case |
@id | #panda-analysis |
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name [?] | Execution of pandas-profiling for exploratory data analysis |
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@id | #dataspice-creation |
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name [?] | dataspice JSON-LD created from CSV templates |
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endTime [?] | 2022-07-27 |
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@id | #notebook-execution-650k |
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name [?] | Second (?) execution of Jupyter Notebook to generate 650k synthetic dataset |
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description [?] | Note that this CSV has only 650k entries, but the Notebook code is meant to crate 1M entries. A modified notebook must have been executed. |
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mentions [?] | BY-COVID WP5 T5.2 Baseline Use Case |
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agent [?] | Stian Soiland-Reyes |
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