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Zoekresultaten - 6 results

BY-COVID D5.1 Enriched report viral variants and health outcomes

demonstrate how mobilisation and linkage of heterogeneous real-world population data sources hosted at multiple sites can enhance the understanding of the direct and indirect effects of the pandemic on health ...

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

Causality COVID-19 COVID-19 Vaccines Humans SARS-CoV-2 Vaccine Efficacy Abstract: INTRODUCTION: Causal inference helps researchers and policy-makers to evaluate public health interventions. When comparing ...

Evaluating methodological approaches to assess the severity of infection with SARS-CoV-2 variants: scoping review and applications on Belgian COVID-19 data.

health. However, causally inferring the intrinsic severity of infection with variants using observational data is a challenging process on which guidance is still limited. We describe potential limitations ...

Unravelling data for rapid evidence-based response to COVID-19: a summary of the unCoVer protocol.

unCoVer-Unravelling data for rapid evidence-based response to COVID-19-is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response ...

Strategy to Develop and Evaluate a Multiplex RT-ddPCR in Response to SARS-CoV-2 Genomic Evolution.

appearing around the world. However, even by using a large collection of samples, laboratories are not able to test a representative collection of samples that deals with the same level of diversity that is ...

Real-World Comparative Effectiveness of SARS-CoV-2 Primary Vaccination Campaigns Against SARS-CoV-2 Infections: A Federated Observational Study Emulating a Target Trial in Three Nations

Bernal-Delgado Source: The Lancet, Elsevier BV (2024) Keywords: Cohort Studies COVID-19 Electronic Health Records Humans Kaplan-Meier Estimate prevention & control SARS-CoV-2 Vaccine Efficacy Viral Vaccines ...

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