A Survey on Contact Tracing: The Latest Advancements and Challenges

Author:

Jiang Ting1,Zhang Yang1,Zhang Minhao1,Yu Ting1,Chen Yizheng1,Lu Chenhao1,Zhang Ji2,Li Zhao3,Gao Jun4,Zhou Shuigeng5

Affiliation:

1. Zhejiang Lab, Hangzhou, China

2. The University of Southern Queensland, Toowoomba, Australia

3. Alibaba Group, Hangzhou, China

4. Peking University, Beijing, China

5. Fudan University, Beijing, China

Abstract

Infectious diseases are caused by pathogenic microorganisms, such as bacteria, viruses, parasites or fungi, which can be spread, directly or indirectly, from one person to another. Infectious diseases pose a serious threat to human health, especially COVID-19 that has became a serious worldwide health concern since the end of 2019. Contact tracing is the process of identifying, assessing, and managing people who have been exposed to a disease to prevent its onward transmission. Contact tracing can help us better understand the transmission link of the virus, whereby better interrupting its transmission. Given the worldwide pandemic of COVID-19, contact tracing has become one of the most critical measures to effectively curb the spread of the virus. This paper presents a comprehensive survey on contact tracing, with a detailed coverage of the recent advancements the models, digital technologies, protocols and issues involved in contact tracing. The current challenges as well as future directions of contact tracing technologies are also presented.

Funder

National Key Research and Development Plan of China

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

PI Research Project of Zhejiang Lab

Publisher

Association for Computing Machinery (ACM)

Subject

Discrete Mathematics and Combinatorics,Geometry and Topology,Computer Science Applications,Modeling and Simulation,Information Systems,Signal Processing

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1. Toward Deep Digital Contact Tracing: Opportunities and Challenges;IEEE Pervasive Computing;2023-10

2. A Cloud Architecture for Monitoring and Controlling Viral COVID-19;Proceedings of the 2023 Fifteenth International Conference on Contemporary Computing;2023-08-03

3. Temporal Cascade Model for Analyzing Spread in Evolving Networks;ACM Transactions on Spatial Algorithms and Systems;2023-04-12

4. A smartphone-based zero-effort method for mitigating epidemic propagation;EURASIP Journal on Advances in Signal Processing;2023-02-01

5. Visual Analytics Platform for Centralized COVID-19 Digital Contact Tracing;IEEE Computer Graphics and Applications;2023-01-01

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