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Risk-aware temporal cascade reconstruction to detect asymptomatic cases.

Hankyu Jang1, Shreyas Pai2, Bijaya Adhikari1

  • 1Department of Computer Science, University of Iowa, Iowa City, 52242 IA USA.

Knowledge and Information Systems
|September 20, 2022
PubMed
Summary

Detecting asymptomatic cases requires considering individual risk and disease spread. Our directed prize-collecting Steiner tree approach significantly improves detection and prediction of infectious diseases.

Keywords:
Asymptomatic casesC. diff infectionsPrize-collecting Steiner treeTemporal contact networks

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Area of Science:

  • Epidemiology
  • Network Science
  • Computational Biology

Background:

  • Detecting asymptomatic cases is crucial for controlling infectious disease outbreaks.
  • Temporal contact networks provide valuable data for understanding disease transmission.
  • Existing methods may not fully capture individual risk and disease flow dynamics.

Purpose of the Study:

  • To develop a novel method for detecting asymptomatic cases in temporal contact networks.
  • To improve the accuracy of infectious disease prediction and source identification.
  • To demonstrate the clinical relevance of the proposed detection approach.

Main Methods:

  • Formulating asymptomatic case detection as a directed prize-collecting Steiner tree (Directed PCST) problem.
  • Developing an approximation-preserving reduction to the directed Steiner tree problem.
  • Implementing scalable algorithms for large-scale synthetic and hospital network data.

Main Results:

  • The proposed Directed PCST method significantly outperforms existing baselines in detecting asymptomatic cases.
  • The method shows substantial improvements in infectious disease prediction tasks.
  • The approach effectively identifies infection sources ('patient zero') with higher accuracy.
  • Case studies confirm the clinical meaningfulness of the obtained solutions.

Conclusions:

  • Integrating individual risk and disease flow is key for effective asymptomatic case detection.
  • The Directed PCST framework offers a scalable and accurate solution for epidemiological challenges.
  • This approach enhances infectious disease surveillance, prediction, and outbreak investigation.