Contact tracing in configuration models

Ivan Kryven, Clara Stegehuis*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Downloads (Pure)

Abstract

Quarantining and contact tracing are popular ad hoc practices for mitigating epidemic outbreaks. However, few mathematical theories are currently available to asses the role of a network in the effectiveness of these practices. In this paper, we study how the final size of an epidemic is influenced by the procedure that combines contact tracing and quarantining on a network null model: the configuration model. Namely, we suppose that infected vertices may self-quarantine and trace their infector with a given success probability. A traced infector is, in turn, less likely to infect others. We show that the effectiveness of such tracing process strongly depends on the network structure. In contrast to previous findings, the tracing procedure is not necessarily more effective on networks with heterogeneous degrees. We also show that network clustering influences the effectiveness of the tracing process in a non-trivial way: depending on the infectiousness parameter, contact tracing on clustered networks may either be more, or less efficient than on networks without clustering.

Original languageEnglish
Article number025004
JournalJournal of Physics: Complexity
Volume2
Issue number2
Early online date2 Feb 2021
DOIs
Publication statusPublished - Jun 2021

Keywords

  • Configuration model
  • Contact tracing
  • Epidemic spreading
  • Random graphs

Fingerprint Dive into the research topics of 'Contact tracing in configuration models'. Together they form a unique fingerprint.

Cite this