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Modeling COVID-19 Pandemic with Hierarchical Quarantine and Time Delay

Wei Yang1

  • 1Software College, Northeastern University, Shenyang, 110169 China.

Dynamic Games and Applications
|March 29, 2021
PubMed

Insights

This study models COVID-19 pandemic dynamics using hierarchical quarantine and time delays. Findings suggest potential COVID-19 recurrence, highlighting the importance of testing and quarantine strategies.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Public Health

Background:

  • The COVID-19 pandemic presented unprecedented public health challenges.
  • Understanding pandemic dynamics is crucial for effective control strategies.

Purpose of the Study:

  • To develop and analyze a pandemic model incorporating hierarchical quarantine and time delays.
  • To investigate factors influencing COVID-19 spread, including incubation periods and reinfection.

Main Methods:

  • A mathematical model was developed to simulate COVID-19 spread.
  • Analysis included stability of equilibrium and nonlinear dynamics.
  • Numerical simulations were used to validate analytical results.

Main Results:

  • The model identified potential for recurrent COVID-19 outbreaks.
  • Bifurcation analysis determined threshold values influencing disease dynamics.
  • Hierarchical quarantine (home and hospital) was analyzed as a control measure.

Conclusions:

  • Increased testing for symptomatic and asymptomatic individuals can aid early cluster identification.
  • Hierarchical quarantine strategies are effective in preventing pandemic spread before vaccine availability.

Keywords:
BifurcationCOVID-19Hierarchical quarantinePandemic modelTime delay

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