The University of Southampton
University of Southampton Institutional Repository

传染病智慧化症状监测的进展与挑战

传染病智慧化症状监测的进展与挑战
传染病智慧化症状监测的进展与挑战
Intelligent syndromic surveillance is an important part of multi-point triggering and multi-channel surveillance system of intelligent early warning of infectious diseases in China, and an inevitable development process of traditional syndromic surveillance as the constant emergence of new technologies. Intelligent syndromic surveillance collects not only the medical data of patients seeking medical care in hospitals but also massive non-medical information. However, along with its rapid development, challenges in intelligent syndromic surveillance have emerged, such as information explosion, cost-effective balance, information sharing, data security and privacy. This paper summarizes the concept and development of intelligent syndromic surveillance to provide references for the method and technique development of intelligent early warning of infectious diseases and new thought for the prevention and control of infectious diseases in China and in the world.
Challenge, Intelligent syndromic surveillance, Prevention and control of infectious disease, Progression
442-446
Fan, Guohui
c4be26d5-992a-410e-bb63-de6db1afb927
Zhang, Ting
f6f3a882-7280-48ff-8ea2-495aa17d245a
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Feng, Luzhao
5ac76d87-7782-493e-803b-eb6043f67a68
Yang, Weizhong
156160b7-47c2-46d6-87e4-0432d1143693
Fan, Guohui
c4be26d5-992a-410e-bb63-de6db1afb927
Zhang, Ting
f6f3a882-7280-48ff-8ea2-495aa17d245a
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Feng, Luzhao
5ac76d87-7782-493e-803b-eb6043f67a68
Yang, Weizhong
156160b7-47c2-46d6-87e4-0432d1143693

Fan, Guohui, Zhang, Ting, Lai, Shengjie, Feng, Luzhao and Yang, Weizhong (2023) 传染病智慧化症状监测的进展与挑战. Chinese Journal of Epidemiology, 44 (9), 442-446. (doi:10.3760/cma.j.cn112338-20230320-00159).

Record type: Article

Abstract

Intelligent syndromic surveillance is an important part of multi-point triggering and multi-channel surveillance system of intelligent early warning of infectious diseases in China, and an inevitable development process of traditional syndromic surveillance as the constant emergence of new technologies. Intelligent syndromic surveillance collects not only the medical data of patients seeking medical care in hospitals but also massive non-medical information. However, along with its rapid development, challenges in intelligent syndromic surveillance have emerged, such as information explosion, cost-effective balance, information sharing, data security and privacy. This paper summarizes the concept and development of intelligent syndromic surveillance to provide references for the method and technique development of intelligent early warning of infectious diseases and new thought for the prevention and control of infectious diseases in China and in the world.

Text
2023-04-07-accepted manuscript - Accepted Manuscript
Restricted to Repository staff only
Request a copy

More information

Submitted date: 20 March 2023
Accepted/In Press date: 31 July 2023
e-pub ahead of print date: 10 September 2023
Published date: September 2023
Additional Information: Funding Information: Innovation Fund for Medical Sciences of Chinese Academy of Medical Sciences (2021-I2M-1-044) Publisher Copyright: © 2023 Authors. All rights reserved.
Alternative titles: Progress and challenge in intelligent syndromic surveillance for infectious diseases
Keywords: Challenge, Intelligent syndromic surveillance, Prevention and control of infectious disease, Progression

Identifiers

Local EPrints ID: 484829
URI: http://eprints.soton.ac.uk/id/eprint/484829
PURE UUID: 8ca3cd40-c1ae-4799-b712-d50393f09ea5
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148

Catalogue record

Date deposited: 22 Nov 2023 17:45
Last modified: 06 Jun 2024 02:03

Export record

Altmetrics

Contributors

Author: Guohui Fan
Author: Ting Zhang
Author: Shengjie Lai ORCID iD
Author: Luzhao Feng
Author: Weizhong Yang

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×