Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA

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BACKGROUND: Despite widespread use, the accuracy of the diagnostic test for SARS-CoV-2 infection is poorly understood. The aim of our work was to better quantify misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves using publ...

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Detalles Bibliográficos
Autores principales: Burstyn, Igor, Goldstein, Neal D., Gustafson, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7275354/
https://www.ncbi.nlm.nih.gov/pubmed/32505172
http://dx.doi.org/10.1186/s12874-020-01037-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7275354/
https://www.ncbi.nlm.nih.gov/pubmed/32505172
http://dx.doi.org/10.1186/s12874-020-01037-4

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