Research output: Contribution to journal › Article › Scientific › peer-review

**Pulse strategy for suppressing spreading on networks.** / Liu, Qiang; Zhou, Xiaoyu; Van Mieghem, Piet.

Research output: Contribution to journal › Article › Scientific › peer-review

Liu, Q, Zhou, X & Van Mieghem, P 2019, 'Pulse strategy for suppressing spreading on networks' *EPL*, vol. 127, no. 3, 38001, pp. 38001-p1 - 38001-p4. https://doi.org/10.1209/0295-5075/127/38001

Liu, Q., Zhou, X., & Van Mieghem, P. (2019). Pulse strategy for suppressing spreading on networks. *EPL*, *127*(3), 38001-p1 - 38001-p4. [38001]. https://doi.org/10.1209/0295-5075/127/38001

Liu Q, Zhou X, Van Mieghem P. Pulse strategy for suppressing spreading on networks. EPL. 2019;127(3):38001-p1 - 38001-p4. 38001. https://doi.org/10.1209/0295-5075/127/38001

@article{badd95ff737b4931ba1ab22c3da585c4,

title = "Pulse strategy for suppressing spreading on networks",

abstract = "In previous modelling efforts to understand the spreading process on networks, each node can infect its neighbors and cure spontaneously, and the curing is traditionally assumed to occur uniformly over time. This traditional curing is not optimal in terms of the trade-off between the effectiveness and cost. A pulse immunization/curing strategy is more efficient and broadly applied to suppress the spreading process. We analyze the pulse curing strategy on networks with the Susceptible-Infected (SI) process. We analytically compute the mean-field epidemic threshold $\tau_c^{p}$ of the pulse SI model and show that $\tau_c^{p}=\frac{1}{\lambda_1}\ln\frac{1}{1-p}$ , where $\lambda_1$ and p are the largest eigenvalue of the adjacency matrix of the contact graph and the fraction of nodes covered by each curing, respectively. These analytical results agree with simulations. Compared to the asynchronous curing process in the extensively studied Markovian SIS process, we show that the pulse curing strategy saves about 36.8{\%}, i.e., $p\approx 0.632$ , of the number of curing operations invariant to the network structure. Our results may help policymakers to design optimal containment strategies and minimize the controlling cost.",

author = "Qiang Liu and Xiaoyu Zhou and {Van Mieghem}, Piet",

note = "Accepted author manuscript",

year = "2019",

doi = "10.1209/0295-5075/127/38001",

language = "English",

volume = "127",

pages = "38001--p1 -- 38001--p4",

journal = "Europhysics Letters: a letters journal exploring the frontiers of physics",

issn = "0295-5075",

publisher = "IOP Publishing Ltd.",

number = "3",

}

TY - JOUR

T1 - Pulse strategy for suppressing spreading on networks

AU - Liu, Qiang

AU - Zhou, Xiaoyu

AU - Van Mieghem, Piet

N1 - Accepted author manuscript

PY - 2019

Y1 - 2019

N2 - In previous modelling efforts to understand the spreading process on networks, each node can infect its neighbors and cure spontaneously, and the curing is traditionally assumed to occur uniformly over time. This traditional curing is not optimal in terms of the trade-off between the effectiveness and cost. A pulse immunization/curing strategy is more efficient and broadly applied to suppress the spreading process. We analyze the pulse curing strategy on networks with the Susceptible-Infected (SI) process. We analytically compute the mean-field epidemic threshold $\tau_c^{p}$ of the pulse SI model and show that $\tau_c^{p}=\frac{1}{\lambda_1}\ln\frac{1}{1-p}$ , where $\lambda_1$ and p are the largest eigenvalue of the adjacency matrix of the contact graph and the fraction of nodes covered by each curing, respectively. These analytical results agree with simulations. Compared to the asynchronous curing process in the extensively studied Markovian SIS process, we show that the pulse curing strategy saves about 36.8%, i.e., $p\approx 0.632$ , of the number of curing operations invariant to the network structure. Our results may help policymakers to design optimal containment strategies and minimize the controlling cost.

AB - In previous modelling efforts to understand the spreading process on networks, each node can infect its neighbors and cure spontaneously, and the curing is traditionally assumed to occur uniformly over time. This traditional curing is not optimal in terms of the trade-off between the effectiveness and cost. A pulse immunization/curing strategy is more efficient and broadly applied to suppress the spreading process. We analyze the pulse curing strategy on networks with the Susceptible-Infected (SI) process. We analytically compute the mean-field epidemic threshold $\tau_c^{p}$ of the pulse SI model and show that $\tau_c^{p}=\frac{1}{\lambda_1}\ln\frac{1}{1-p}$ , where $\lambda_1$ and p are the largest eigenvalue of the adjacency matrix of the contact graph and the fraction of nodes covered by each curing, respectively. These analytical results agree with simulations. Compared to the asynchronous curing process in the extensively studied Markovian SIS process, we show that the pulse curing strategy saves about 36.8%, i.e., $p\approx 0.632$ , of the number of curing operations invariant to the network structure. Our results may help policymakers to design optimal containment strategies and minimize the controlling cost.

U2 - 10.1209/0295-5075/127/38001

DO - 10.1209/0295-5075/127/38001

M3 - Article

VL - 127

SP - 38001-p1 - 38001-p4

JO - Europhysics Letters: a letters journal exploring the frontiers of physics

T2 - Europhysics Letters: a letters journal exploring the frontiers of physics

JF - Europhysics Letters: a letters journal exploring the frontiers of physics

SN - 0295-5075

IS - 3

M1 - 38001

ER -

ID: 56644763