Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment

Abstract Introduction Causal inference helps researchers and policy-makers to evaluate public health interventions. When comparing interventions or public health programs by leveraging observational sensitive individual-level data from populations crossing jurisdictional borders, a federated approac...

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Bibliographic Details
Main Authors: Marjan Meurisse, Francisco Estupiñán-Romero, Javier González-Galindo, Natalia Martínez-Lizaga, Santiago Royo-Sierra, Simon Saldner, Lorenz Dolanski-Aghamanoukjan, Alexander Degelsegger-Marquez, Stian Soiland-Reyes, Nina Van Goethem, Enrique Bernal-Delgado, for the BeYond-COVID project
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Medical Research Methodology
Subjects:
Federated analysis
Causal inference
Real-world data
Comparative effectiveness
Vaccines
COVID-19
Online Access:https://doi.org/10.1186/s12874-023-02068-3

Internet

https://doi.org/10.1186/s12874-023-02068-3

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