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Estimation of COVID-19 spread curves integrating global data and borrowing information

Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Dru...

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Detalles Bibliográficos
Autores principales: Lee, Se Yoon, Lei, Bowen, Mallick, Bani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390340/
https://www.ncbi.nlm.nih.gov/pubmed/32726361
http://dx.doi.org/10.1371/journal.pone.0236860
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author Lee, Se Yoon
Lei, Bowen
Mallick, Bani
author_facet Lee, Se Yoon
Lei, Bowen
Mallick, Bani
author_sort Lee, Se Yoon
collection PubMed
description Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19.
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spelling pubmed-73903402020-08-05 Estimation of COVID-19 spread curves integrating global data and borrowing information Lee, Se Yoon Lei, Bowen Mallick, Bani PLoS One Research Article Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19. Public Library of Science 2020-07-29 /pmc/articles/PMC7390340/ /pubmed/32726361 http://dx.doi.org/10.1371/journal.pone.0236860 Text en © 2020 Lee et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lee, Se Yoon
Lei, Bowen
Mallick, Bani
Estimation of COVID-19 spread curves integrating global data and borrowing information
title Estimation of COVID-19 spread curves integrating global data and borrowing information
title_full Estimation of COVID-19 spread curves integrating global data and borrowing information
title_fullStr Estimation of COVID-19 spread curves integrating global data and borrowing information
title_full_unstemmed Estimation of COVID-19 spread curves integrating global data and borrowing information
title_short Estimation of COVID-19 spread curves integrating global data and borrowing information
title_sort estimation of covid-19 spread curves integrating global data and borrowing information
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390340/
https://www.ncbi.nlm.nih.gov/pubmed/32726361
http://dx.doi.org/10.1371/journal.pone.0236860
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