An Efficient Immunization Strategy for Community Networks

Abstract

An efficient algorithm that can properly identify the targets to immunize or quarantine for preventing an epidemic in a population without knowing the global structural information is of obvious importance. Typically, a population is characterized by its community structure and the heterogeneity in the weak ties among nodes bridging over communities. We propose and study an effective algorithm that searches for bridge hubs, which are bridge nodes with a larger number of weak ties, as immunizing targets based on the idea of referencing to an expanding friendship circle as a self-avoiding walk proceeds. Applying the algorithm to simulated networks and empirical networks constructed from social network data of five US universities, we show that the algorithm is more effective than other existing local algorithms for a given immunization coverage, with a reduced final epidemic ratio, lower peak prevalence and fewer nodes that need to be visited before identifying the target nodes. The effectiveness stems from the breaking up of community networks by successful searches on target nodes with more weak ties. The effectiveness remains robust even when errors exist in the structure of the networks.

Statistical physics of vaccination

“…However, their importance is not necessarily reflected by their degree centrality. In this regard, identifying the bridge nodes in community networks is crucial in preventing epidemic outbreaks [321,350]. Identification of community Table 3: Summary of non-behavioral epidemiological vaccination strategies, with details concerning vaccinated nodes, network models, and the required knowledge about the structure of the network.…”

“…Inspired by this finding, Gong et al turned their attention to a particular kind of bridge nodes, named bridge hubs, which connect a community to many other communities, i.e., bridge hubs have a large number of weak ties [350]. They proposed a vaccination strategy named bridge-hub detector (BHD) to identify the bridge hubs.…”

“…A pair of nodes, a bridge node and a bridge hub, are searched for vaccination via a self-avoiding walk. Compared with other local vaccination strategies such as acquaintance vaccination and CBF, this strategy is proven to be more effective in preventing the epidemic [350].…”

Control Strategies of Contagion Processes in Time-Varying Networks

“…At the same time immunization was also studied on meta-population networks [68]. In other studies, it has been argued that efficient immunization strategies can be developed by considering the higher-order organization of connectivity patterns [57,69,70,71,72,73,74]. Further studies proposed vaccination strategies using evolutionary games [75], or considering complex contagion processes [76].…”

Coupled effects of local movement and global interaction on contagion

“…The spread of infectious disease is closely related to mobility patterns and interaction patterns of the population [12,13,14,15]. An individual may move about aimlessly like a floating boat in the ocean or travel along a certain path like a move on the chessboard.…”