title: Identification of Patient Zero in Static and Temporal Networks: Robustness and Limitations.
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.
authors.affiliation: Computational Biology and Bioinformatics Group, Division of Electronics, Rudjer Bošković Institute, Zagreb 10000, Croatia.
authors.forename: Nino
authors.initials: N
authors.lastname: Antulov-Fantulin
authors.affiliation: Department of Mathematics, Faculty of Science, University of Zagreb, Zagreb 10000, Croatia.
authors.forename: Alen
authors.initials: A
authors.lastname: Lančić
authors.affiliation: Computational Biology and Bioinformatics Group, Division of Electronics, Rudjer Bošković Institute, Zagreb 10000, Croatia.
authors.forename: Tomislav
authors.initials: T
authors.lastname: Šmuc
authors.affiliation: Theoretical Physics Division, Rudjer Bošković Institute, Zagreb 10000, Croatia.|Catholic University of Croatia, Zagreb 10000, Croatia.
authors.forename: Hrvoje
authors.initials: H
authors.lastname: Štefančić
authors.affiliation: Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb 10000, Croatia.|Bioinformatics Institute, A*STAR, Singapore 138671, Republic of Singapore.
authors.forename: Mile
authors.initials: M
authors.lastname: Šikić
mesh_terms: D003198:Computer Simulation; D016358:Contact Tracing / Q000379:methods*; D004812:Epidemiologic Methods; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D012749:Sexually Transmitted Diseases / Q000453:epidemiology* / Q000635:transmission