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Causal graph analysis of COVID-19 observational data in German districts reveals effects of determining factors on reported case numbers
Several determinants are suspected to be causal drivers for new cases of COVID-19 infection. Correcting for possible confounders, we estimated the effects of the most prominent determining factors on reported case numbers. To this end, we used a directed acyclic graph (DAG) as a graphical representa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158986/ https://www.ncbi.nlm.nih.gov/pubmed/34043653 http://dx.doi.org/10.1371/journal.pone.0237277 |