Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Salah Haridy
  • Arthur W. Baker
  • Mohammad Shamsuzzaman
  • Hamdi Bashir

Detail(s)

Original languageEnglish
Article number107235
Journal / PublicationComputers & Industrial Engineering
Volume156
Online published16 Mar 2021
Publication statusPublished - Jun 2021

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.

Research Area(s)

  • Control Chart, Coronavirus, COVID-19, Monitoring, Outbreak Detection, Statistical Process Control

Citation Format(s)

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.

In: Computers & Industrial Engineering, Vol. 156, 107235, 06.2021.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review