This study focuses on investigating the manner in which a prompt quarantine
measure suppresses epidemics in networks. A simple and ideal quarantine measure
is considered in which an individual is detected with a probability immediately
after it becomes infected and the detected one and its neighbors are promptly
isolated. The efficiency of this quarantine in suppressing a
susceptible-infected-removed (SIR) model is tested in random graphs and
uncorrelated scale-free networks. Monte Carlo simulations are used to show that
the prompt quarantine measure outperforms random and acquaintance preventive
vaccination schemes in terms of reducing the number of infected individuals.
The epidemic threshold for the SIR model is analytically derived under the
quarantine measure, and the theoretical findings indicate that prompt
executions of quarantines are highly effective in containing epidemics. Even if
infected individuals are detected with a very low probability, the SIR model
under a prompt quarantine measure has finite epidemic thresholds in fat-tailed
scale-free networks in which an infected individual can always cause an
outbreak of a finite relative size without any measure. The numerical
simulations also demonstrate that the present quarantine measure is effective
in suppressing epidemics in real networks.Comment: 10 pages, 7 figure
