  Detection of patient-zero can give new insights to the epidemiologists about
the nature of first transmissions into a population. In this paper, 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 SIR 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.
