Advancements in Epidemic Transmission Suppression: A Comprehensive Survey

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-06-12 DOI:10.1109/TNSE.2025.3579136

Lili Tong;Shan Zhang;Hao Sun;Yuliang Cai;Jiawei Zhang;Wei Qian;Qingchao Zhang;Qiang He;Junxin Chen;Jia Li

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Abstract

The large-scale spread of epidemics poses a serious threat to human life and health security. It disrupts educational development, cripples the global economy, triggers social unrest, and jeopardizes global stability. Consequently, understanding how to rapidly comprehend the transmission of epidemics and control their outbreaks has become a prominent topic in the field of epidemiology. This paper provides a comprehensive overview of the application of computer technology in epidemiological research, categorizing the challenge of curbing epidemic spread into three key areas: 1) epidemic transmission, 2) epidemic source tracing, and 3) epidemic suppression strategies. Each area is thoroughly reviewed and summarized. First, in the context of epidemic transmission, this paper summarizes various transmission models used to describe and predict the spread of epidemics within populations. Second, regarding epidemic source tracing, the paper reviews relevant studies from the perspectives of single-source and multi-source detection. Third, in terms of epidemic suppression strategies, it offers a detailed overview of diverse approaches aimed at reducing the spread and prevalence of diseases among populations. Finally, the paper discusses the challenges faced in the field of epidemic suppression and explores potential future directions for research and development.

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流行病传播抑制进展：综合调查

流行病的大规模传播对人类生命和健康安全构成严重威胁。它扰乱了教育发展，削弱了全球经济，引发了社会动荡，危害了全球稳定。因此，了解如何快速了解流行病的传播并控制其爆发已成为流行病学领域的一个突出课题。本文全面概述了计算机技术在流行病学研究中的应用，并将控制流行病传播的挑战分为三个关键领域：1)流行病传播，2)流行病来源追踪，3)流行病抑制策略。每个领域都进行了彻底的审查和总结。首先，在流行病传播的背景下，本文总结了用于描述和预测流行病在人群中的传播的各种传播模型。其次，在疫情源溯源方面，从单源检测和多源检测两方面综述了相关研究。第三，在抑制流行病战略方面，它详细概述了旨在减少疾病在人群中的传播和流行的各种方法。最后，讨论了流行病抑制领域面临的挑战，并探讨了未来可能的研究和发展方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.