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Related Experiment Video

Updated: Jun 28, 2025

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Contact Tracing for Disease Containment: a Network-Based Analysis.

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  • 1Institute of Information Systems Engineering, TU Wien, Favoritenstraße 11, 1050 Vienna, Austria.

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|April 15, 2024
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Summary
This summary is machine-generated.

Test, trace, and isolate (TTI) effectiveness depends on disease infectiousness and contact network structure. Higher clustering slightly improves containment, but high transmission significantly reduces TTI policy effectiveness.

Keywords:
COVID-19SARS-CoV-2agent-based modellingclusteringcontact-tracingdiscrete-event simulationepidemiologynetwork modelling

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Area of Science:

  • Epidemiology
  • Network Science
  • Public Health Interventions

Background:

  • The test, trace, and isolate (TTI) strategy is a key non-pharmaceutical intervention for controlling infectious disease spread.
  • While generally effective, the network-specific factors influencing TTI efficacy remain underexplored.

Purpose of the Study:

  • To evaluate the effectiveness of TTI strategies against diseases with varying infectiousness levels.
  • To assess the impact of different contact network structures, specifically clustering coefficients, on TTI efficacy.

Main Methods:

  • An agent-based network model integrating epidemiological (SEIR), quarantine, and contact-tracing components was utilized.
  • Simulations involved varying disease transmission probabilities and network clustering coefficients to test hypotheses.

Main Results:

  • TTI showed a slightly larger containment impact in networks with higher clustering coefficients, especially for rapidly spreading diseases.
  • A significant decrease in TTI policy effectiveness was observed as the disease transmission probability increased.

Conclusions:

  • The infectiousness of a disease is a more critical factor in TTI effectiveness than network clustering.
  • TTI strategies are more efficient when complemented by measures reducing infection probability or during periods with low negative seasonality.