Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks. (June 2021)
- Record Type:
- Journal Article
- Title:
- Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks. (June 2021)
- Main Title:
- Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks
- Authors:
- Haridy, Salah
Maged, Ahmed
Baker, Arthur W.
Shamsuzzaman, Mohammad
Bashir, Hamdi
Xie, Min - Abstract:
- Highlights: Monitoring scheme is proposed for early detection of coronavirus virus outbreaks. The sample size is optimized to ensure the best overall performance of the scheme. False alarm rate and inspection rate are used as constrains. The proposed scheme substantially outperforms its traditional counterpart. Abstract: 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 traditionalHighlights: Monitoring scheme is proposed for early detection of coronavirus virus outbreaks. The sample size is optimized to ensure the best overall performance of the scheme. False alarm rate and inspection rate are used as constrains. The proposed scheme substantially outperforms its traditional counterpart. Abstract: 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. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 156(2021)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 156(2021)
- Issue Display:
- Volume 156, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 156
- Issue:
- 2021
- Issue Sort Value:
- 2021-0156-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-06
- Subjects:
- Coronavirus -- COVID-19 -- Monitoring -- Statistical Process Control -- Control Chart -- Outbreak Detection
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2021.107235 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
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British Library HMNTS - ELD Digital store - Ingest File:
- 22483.xml