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

研究成果: Paper同行評審

摘要

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].

原文American English
頁面48-52
頁數5
DOIs
出版狀態Published - 22 6月 2018
事件2018 2nd High Performance Computing and Cluster Technologies Conference, HPCCT 2018 - Beijing, 中國
持續時間: 22 6月 201824 6月 2018

Conference

Conference2018 2nd High Performance Computing and Cluster Technologies Conference, HPCCT 2018
國家/地區中國
城市Beijing
期間22/06/1824/06/18

指紋

深入研究「A Suggestion of a New Measure of Importance of Nodes in Disease-propagation Graphs」主題。共同形成了獨特的指紋。

引用此