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This study focuses on investigating the manner in which a prompt quarantinemeasure suppresses epidemics in networks. A simple and ideal quarantine measureis considered in which an individual is detected with a probability immediatelyafter it becomes infected and the detected one and its neighbors are promptlyisolated. The efficiency of this quarantine in suppressing asusceptible-infected-removed (SIR) model is tested in random graphs anduncorrelated scale-free networks. Monte Carlo simulations are used to show thatthe prompt quarantine measure outperforms random and acquaintance preventivevaccination schemes in terms of reducing the number of infected individuals.The epidemic threshold for the SIR model is analytically derived under thequarantine measure, and the theoretical findings indicate that promptexecutions of quarantines are highly effective in containing epidemics. Even ifinfected individuals are detected with a very low probability, the SIR modelunder a prompt quarantine measure has finite epidemic thresholds in fat-tailedscale-free networks in which an infected individual can always cause anoutbreak of a finite relative size without any measure. The numericalsimulations also demonstrate that the present quarantine measure is effectivein suppressing epidemics in real networks.

Efficiency of prompt quarantine measures on a susceptible-infected-removed model in networks