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Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks
In December 2019, an outbreak of pneumonia caused by a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) began in Wuhan, China. SARS-CoV-2 exhibited efficient person-to-person transmission of what became labeled as COVID-19. It has spread worldwide with over 83,000,000...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962947/ https://www.ncbi.nlm.nih.gov/pubmed/33746343 http://dx.doi.org/10.1016/j.cie.2021.107235 |
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author | Haridy, Salah Maged, Ahmed Baker, Arthur W. Shamsuzzaman, Mohammad Bashir, Hamdi Xie, Min |
author_facet | Haridy, Salah Maged, Ahmed Baker, Arthur W. Shamsuzzaman, Mohammad Bashir, Hamdi Xie, Min |
author_sort | Haridy, Salah |
collection | PubMed |
description | In December 2019, an outbreak of pneumonia caused by a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) began in Wuhan, China. SARS-CoV-2 exhibited efficient person-to-person transmission of what became labeled as COVID-19. It has spread worldwide with over 83,000,000 infected cases and more than 1,800,000 deaths to date (December 31, 2020). This research proposes a statistical monitoring scheme in which an optimized np control chart is utilized by sentinel metropolitan airports worldwide for early detection of coronavirus and other respiratory virus outbreaks. The sample size of this chart is optimized to ensure the best overall performance for detecting a wide range of shifts in the infection rate, based on the available resources, such as the inspection rate and the allowable false alarm rate. The effectiveness of the proposed optimized np chart is compared with that of the traditional np chart with a predetermined sample size under both sampling inspection and 100% inspection. For a variety of scenarios including a real case, the optimized np control chart is found to substantially outperform its traditional counterpart in terms of the average number of infections. Therefore, this control chart has potential to be an effective tool for early detection of respiratory virus outbreaks, promoting early outbreak investigation and mitigation. |
format | Online Article Text |
id | pubmed-7962947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79629472021-03-17 Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks Haridy, Salah Maged, Ahmed Baker, Arthur W. Shamsuzzaman, Mohammad Bashir, Hamdi Xie, Min Comput Ind Eng Article In December 2019, an outbreak of pneumonia caused by a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) began in Wuhan, China. SARS-CoV-2 exhibited efficient person-to-person transmission of what became labeled as COVID-19. It has spread worldwide with over 83,000,000 infected cases and more than 1,800,000 deaths to date (December 31, 2020). This research proposes a statistical monitoring scheme in which an optimized np control chart is utilized by sentinel metropolitan airports worldwide for early detection of coronavirus and other respiratory virus outbreaks. The sample size of this chart is optimized to ensure the best overall performance for detecting a wide range of shifts in the infection rate, based on the available resources, such as the inspection rate and the allowable false alarm rate. The effectiveness of the proposed optimized np chart is compared with that of the traditional np chart with a predetermined sample size under both sampling inspection and 100% inspection. For a variety of scenarios including a real case, the optimized np control chart is found to substantially outperform its traditional counterpart in terms of the average number of infections. Therefore, this control chart has potential to be an effective tool for early detection of respiratory virus outbreaks, promoting early outbreak investigation and mitigation. Elsevier Ltd. 2021-06 2021-03-16 /pmc/articles/PMC7962947/ /pubmed/33746343 http://dx.doi.org/10.1016/j.cie.2021.107235 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Haridy, Salah Maged, Ahmed Baker, Arthur W. Shamsuzzaman, Mohammad Bashir, Hamdi Xie, Min Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
title | Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
title_full | Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
title_fullStr | Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
title_full_unstemmed | Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
title_short | Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
title_sort | monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962947/ https://www.ncbi.nlm.nih.gov/pubmed/33746343 http://dx.doi.org/10.1016/j.cie.2021.107235 |
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