research-article

Sentinel Nodes Identification for Infectious Disease Surveillance on Temporal Social Networks

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Li TaoAuthors Info & Claims

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

Pages 493 - 499

https://doi.org/10.1145/3350546.3360739

Published: 14 October 2019 Publication History

Abstract

Active surveillance, which aims at detecting and controlling infectious diseases at an early stage, is essential to prevent the spread of infections, protect people’s health, and promote social good. One difficult problem in active surveillance is how to intelligently sample a small group of nodes as sentinels from a large number of individuals for detecting the outbreaks of infectious diseases as early as possible. To sample sentinels, the existing methods depending on the global information about a social network are infeasible for mapping out social connections is time-consuming and inaccurate. Instead, some existing studies utilize local information about individuals’ connected neighbors to heuristically select sentinels. However, few of them take into account the temporal structure of social connections, which is believed to have a direct effect on the spread of infectious diseases. In this paper, we propose two temporal-network surveillance strategies for selecting sentinels based on the friendship paradox theory, a sociological theory describing a phenomenon in social networks that most people have fewer friends than their friends have. By simulating our strategies with three existing strategies based on the susceptible-infected (SI) model, the results show that our proposed 1stAN and 2ndRN strategies can detect the outbreak of infectious diseases earlier than the other strategies on the synthetic temporal network and two real-world temporal social networks, respectively.

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Cited By

Medhat AIyer S(2024)The Friendship Paradox and Social Network ParticipationComplex Networks & Their Applications XII10.1007/978-3-031-53503-1_25(301-315)Online publication date: 29-Feb-2024
https://doi.org/10.1007/978-3-031-53503-1_25
Taha K(2022) Identifying the Top- k Influential Spreaders in Social Networks: a Survey and Experimental Evaluation IEEE Access10.1109/ACCESS.2022.321304410(107809-107845)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3213044
Obe OSarumi OAdebayo A(2022)Enhancing Epidemiological Surveillance Systems Using Dynamic Modeling: A Scoping ReviewProceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)10.1007/978-3-030-96302-6_48(512-523)Online publication date: 22-Feb-2022
https://doi.org/10.1007/978-3-030-96302-6_48
Show More Cited By

Index Terms

Sentinel Nodes Identification for Infectious Disease Surveillance on Temporal Social Networks
1. Applied computing
  1. Life and medical sciences
    1. Health informatics
2. Information systems

Index terms have been assigned to the content through auto-classification.

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cover image ACM Other conferences

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

October 2019

507 pages

ISBN:9781450369343

DOI:10.1145/3350546

Copyright © 2019 ACM.

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Published: 14 October 2019

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WI '19

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

October 14 - 17, 2019

Thessaloniki, Greece

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Overall Acceptance Rate 118 of 178 submissions, 66%

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Cited By

Medhat AIyer S(2024)The Friendship Paradox and Social Network ParticipationComplex Networks & Their Applications XII10.1007/978-3-031-53503-1_25(301-315)Online publication date: 29-Feb-2024
https://doi.org/10.1007/978-3-031-53503-1_25
Taha K(2022) Identifying the Top- k Influential Spreaders in Social Networks: a Survey and Experimental Evaluation IEEE Access10.1109/ACCESS.2022.321304410(107809-107845)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3213044
Obe OSarumi OAdebayo A(2022)Enhancing Epidemiological Surveillance Systems Using Dynamic Modeling: A Scoping ReviewProceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)10.1007/978-3-030-96302-6_48(512-523)Online publication date: 22-Feb-2022
https://doi.org/10.1007/978-3-030-96302-6_48
Amofa SGao JAmankona IQi XSu X(2021)Complementary Blockchain-Based Privacy Protection for Covid-19 Contact Tracing2021 IEEE 21st International Conference on Communication Technology (ICCT)10.1109/ICCT52962.2021.9658064(1455-1460)Online publication date: 13-Oct-2021
https://doi.org/10.1109/ICCT52962.2021.9658064
Li QLi MShi XWu BXiao Y(2021)A key elements influence discovery scheme based on ternary association graph and representation learningKnowledge-Based Systems10.1016/j.knosys.2021.107359229:COnline publication date: 11-Oct-2021
https://dl.acm.org/doi/10.1016/j.knosys.2021.107359
Vujjini DSalah RAlsadoon APrasa P(2020)Survey on Real-Time Tracking and Treatment of Infectious Diseases Using Mixed Reality in Visualisation Technique with Autoimmune Therapy2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)10.1109/CITISIA50690.2020.9371853(1-9)Online publication date: 25-Nov-2020
https://doi.org/10.1109/CITISIA50690.2020.9371853

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