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Identification of disease propagation paths in two-layer networks
Guangjun Li1,2, Gang Liu3, Xiaoqun Wu3
1College of Sports Engineering and Information Technology, Wuhan Sports University, Wuhan, 430079, China. lgjsys@126.com.
Abstract:
To determine the path of disease in different types of networks, a new method based on compressive sensing is proposed for identifying the disease propagation paths in two-layer networks. If a limited amount of data from network nodes is collected, according to the principle of compressive sensing, it is feasible to accurately identify the path of disease propagation in a multilayer network. Experimental results show that the method can be applied to various networks, such as scale-free networks, small-world networks, and random networks. The impact of network density on identification accuracy is explored. The method could be used to aid in the prevention of disease spread.
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