Estimating unconfirmed COVID-19 infection cases and multiple waves of pandemic progression with consideration of testing capacity and non-pharmaceutical interventions : A dynamic spreading model

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

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Author(s)

  • Choujun Zhan
  • Lujiao Shao
  • Xinyu Zhang
  • Ziliang Yin
  • Ying Gao
  • Dong Yang
  • Di Wu
  • Haijun Zhang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)418-439
Journal / PublicationInformation Sciences
Volume607
Online published6 Jun 2022
Publication statusPublished - Aug 2022

Abstract

The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has unique epidemiological characteristics that include presymptomatic and asymptomatic infections, resulting in a large proportion of infected cases being unconfirmed, including patients with clinical symptoms who have not been identified by screening. These unconfirmed infected individuals move and spread the virus freely, presenting difficult challenges to the control of the pandemic. To reveal the actual pandemic situation in a given region, a simple dynamic susceptible-unconfirmed-confirmed-removed (D-SUCR) model is developed taking into account the influence of unconfirmed cases, the testing capacity, the multiple waves of the pandemic, and the use of non-pharmaceutical interventions. Using this model, the total numbers of infected cases in 51 regions of the USA and 116 countries worldwide are estimated, and the results indicate that only about 40% of the true number of infections have been confirmed. In addition, it is found that if local authorities could enhance their testing capacities and implement a timely strict quarantine strategy after identifying the first infection case, the total number of infected cases could be reduced by more than 90%. Delay in implementing quarantine measures would drastically reduce their effectiveness.

Research Area(s)

  • COVID-19, Testing capacity, Extended SEIR models, Spreading dynamics, Infection estimation

Citation Format(s)

Estimating unconfirmed COVID-19 infection cases and multiple waves of pandemic progression with consideration of testing capacity and non-pharmaceutical interventions : A dynamic spreading model. / Zhan, Choujun; Shao, Lujiao; Zhang, Xinyu; Yin, Ziliang; Gao, Ying; Tse, Chi K.; Yang, Dong; Wu, Di; Zhang, Haijun.

In: Information Sciences, Vol. 607, 08.2022, p. 418-439.

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