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A Suggestion of a New Measure of Importance of Nodes in Disease-propagation Graphs

Published: 22 June 2018 Publication History

Abstract

One of the most effective ways to protect people from being infected by infectious diseases is through vaccination. However, due to the limitation of vaccine supply, it is usually impractical to vaccinate all of the people in a community. Therefore, how to smartly select a small group of people for targeted vaccination becomes an important issue. Recently, reference [3] deploys a wireless sensor system in a high school in China to collect contacts between students happened within a disease transmission distance. Reference [3] constructs a graph model for disease propagation and presents a measure of importance of nodes, called connectivity centrality, so that targeted vaccination can be performed effectively. We find that although connectivity centrality does provide a nice measure of how a node affects the other nodes during disease propagation, it overemphasizes the contact frequency between nodes and overlooks the number of neighbors of a node. Therefore, in this paper, we suggest a new measure of importance of nodes in disease-propagation graphs. and we show that there exist an infinite number of disease-propagation graphs such that the node selected by our measure is better than that selected by [3].

References

[1]
L. C. Freeman, "Centrality in social networks conceptual clarification," Soc. Netw., vol. 1, no. 3, pp. 215--239, 1979.
[2]
J. Nieminen, "On centrality in a graph," Scandinavian Journal of Psychology, vol. 15, pp. 322--336, 1974.
[3]
X. Sun, Z. Lu, X. Zhang, M. Salathe, and G. Cao, "Infectious disease containment based on a wireless sensor system," IEEE Access, vol. 4, pp. 1558--1569, 2016.

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  1. A Suggestion of a New Measure of Importance of Nodes in Disease-propagation Graphs

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    HPCCT '18: Proceedings of the 2018 2nd High Performance Computing and Cluster Technologies Conference
    June 2018
    126 pages
    ISBN:9781450364850
    DOI:10.1145/3234664
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Shanghai Jiao Tong University: Shanghai Jiao Tong University
    • Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
    • Chinese Academy of Sciences

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 June 2018

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    Author Tags

    1. Disease containment
    2. graph
    3. node centrality
    4. node importance
    5. wireless sensor network

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    • Ministry of Science and Technology of Taiwan

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    HPCCT 2018

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