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Identification of Patient Zero in Static and Temporal Networks: Robustness and Limitations

Nino Antulov-Fantulin, Alen Lančić, Tomislav Šmuc, Hrvoje Štefančić, and Mile Šikić
Phys. Rev. Lett. 114, 248701 – Published 16 June 2015
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Abstract

Detection of patient zero can give new insights to epidemiologists about the nature of first transmissions into a population. In this Letter, we study the statistical inference problem of detecting the source of epidemics from a snapshot of spreading on an arbitrary network structure. By using exact analytic calculations and Monte Carlo estimators, we demonstrate the detectability limits for the susceptible-infected-recovered model, which primarily depend on the spreading process characteristics. Finally, we demonstrate the applicability of the approach in a case of a simulated sexually transmitted infection spreading over an empirical temporal network of sexual interactions.

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  • Received 31 October 2014

DOI:https://doi.org/10.1103/PhysRevLett.114.248701

© 2015 American Physical Society

Synopsis

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Finding Patient Zero

Published 16 June 2015

A new model could help narrow down the source of a disease outbreak.

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Authors & Affiliations

Nino Antulov-Fantulin1, Alen Lančić2, Tomislav Šmuc1, Hrvoje Štefančić3,4, and Mile Šikić5,6,*

  • 1Computational Biology and Bioinformatics Group, Division of Electronics, Rudjer Bošković Institute, Zagreb 10000, Croatia
  • 2Department of Mathematics, Faculty of Science, University of Zagreb, Zagreb 10000, Croatia
  • 3Theoretical Physics Division, Rudjer Bošković Institute, Zagreb 10000, Croatia
  • 4Catholic University of Croatia, Zagreb 10000, Croatia
  • 5Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb 10000, Croatia
  • 6Bioinformatics Institute, A*STAR, Singapore 138671, Republic of Singapore

  • *Corresponding author. mile.sikic@fer.hr

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Issue

Vol. 114, Iss. 24 — 19 June 2015

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