Requirements for the containment of COVID-19 disease outbreaks through periodic testing, isolation, and quarantine

Abstract

We employ individual-based Monte Carlo computer simulations of a stochastic SEIR model variant on a two-dimensional Newman–Watts small-world network to investigate the control of epidemic outbreaks through periodic testing and isolation of infectious individuals, and subsequent quarantine of their immediate contacts. Using disease parameters informed by the COVID-19 pandemic, we investigate the effects of various crucial mitigation features on the epidemic spreading: fraction of the infectious population that is identifiable through the tests; testing frequency; time delay between testing and isolation of positively tested individuals; and the further time delay until quarantining their contacts as well as the quarantine duration. We thus determine the required ranges for these intervention parameters to yield effective control of the disease through both considerable delaying the epidemic peak and massively reducing the total number of sustained infections.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 23, 2021
Source ID
10.1088/1751-8121/ac3fc3

Entities

People

  • Lauren M. Childs
  • Priyanka
  • Ruslan I. Mukhamadiarov
  • Shannon R. Serrao
  • Shengfeng Deng
  • Uwe C. Täuber

Organizations

  • Army Research Office
  • China Scholarship Council
  • National Science Foundation

Tags

Fields of Study

  • Biology
  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Fluid Mechanics and Fluid Dynamics.
  • Infectious Disease/Epidemiology