Effect of manual and digital contact tracing on COVID-19 outbreaks: a study on empirical contact data

A. Barrat, C. Cattuto, M. Kivelä, S. Lehmann, J. Saramäki

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
32 Downloads (Pure)

Abstract

Non-pharmaceutical interventions are crucial to mitigate the COVID-19 pandemic and contain re-emergence phenomena. Targeted measures such as case isolation and contact tracing can alleviate the societal cost of lock-downs by containing the spread where and when it occurs. To assess the relative and combined impact of manual contact tracing (MCT) and digital (app-based) contact tracing, we feed a compartmental model for COVID-19 with high-resolution datasets describing contacts between individuals in several contexts. We show that the benefit (epidemic size reduction) is generically linear in the fraction of contacts recalled during MCT and quadratic in the app adoption, with no threshold effect. The cost (number of quarantines) versus benefit curve has a characteristic parabolic shape, independent of the type of tracing, with a potentially high benefit and low cost if app adoption and MCT efficiency are high enough. Benefits are higher and the cost lower if the epidemic reproductive number is lower, showing the importance of combining tracing with additional mitigation measures. The observed phenomenology is qualitatively robust across datasets and parameters. We moreover obtain analytically similar results on simplified models.

Original languageEnglish
Article number20201000
Pages (from-to)20201000
Number of pages11
JournalJournal of the Royal Society Interface
Volume18
Issue number178
DOIs
Publication statusPublished - 5 May 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • contact tracing
  • COVID-19
  • temporal contact networks

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