The Intelligent Infectious Disease Active Surveillance and early warning system in China: An application of dengue prevention and control

Q1 Social Sciences Global Transitions Pub Date : 2024-01-01 DOI:10.1016/j.glt.2024.10.004
Liangyu Kang , Jian Hu , Kangning Cai , Wenzhan Jing , Min Liu , Wannian Liang
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Abstract

Utilizing advanced information technologies such as big data and artificial intelligence (AI), China has established and implemented the Intelligent Infectious Disease Active Surveillance and Early Warning System. It provides new tools for the surveillance, early warning, and response to infectious diseases, enhancing the timeliness, scientific basis, and efficiency of epidemic control efforts. The system comprises four functional modules including multi-channel active surveillance, intelligent early warning, data-driven risk assessment, and smart emergency response. This paper provides a detailed overview of the structure and functions of the Intelligent Infectious Disease Active Surveillance and Early Warning System in China, with a specific focus on its application in dengue prevention and control in Hainan Province from February to May 2024. Firstly, the system can proactively capture and integrate heterogeneous surveillance data from multiple sources. Based on these multi-channel data, users can select appropriate warning indicators and AI models to automatically trigger early warnings. Using vast amounts of surveillance data, the system can construct machine learning models to accurately assess the transmission risk of infectious diseases. In terms of emergency response, the system offers powerful tools for early diagnosis, smart epidemiological investigation, digital contact tracing, vaccine and drug development, and evaluation of intervention measures. This system facilitates early detection, reporting, and management of outbreaks, serving as a valuable reference for other countries and regions. Nevertheless, continuous efforts are needed to strengthen scientific research and multidisciplinary collaboration, establish reliable data collection mechanisms, enhance continuous model monitoring and adjustments, and leverage the latest large language models. In the future, the system will be further optimized to help control emerging and major infectious diseases more effectively.
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中国的智能传染病主动监测和预警系统:登革热防控的应用
中国利用大数据、人工智能等先进信息技术,建立并实施了 "传染病智能主动监测预警系统"。该系统为传染病监测、预警和应对提供了新工具,提高了疫情防控工作的及时性、科学性和高效性。该系统由四个功能模块组成,包括多渠道主动监测、智能预警、数据驱动的风险评估和智能应急响应。本文详细介绍了中国传染病智能主动监测预警系统的结构和功能,并重点介绍了该系统在海南省2024年2月至5月登革热防控工作中的应用。首先,该系统可以主动捕捉和整合来自多个来源的异构监测数据。基于这些多渠道数据,用户可以选择适当的预警指标和人工智能模型,自动触发预警。利用海量监测数据,系统可以构建机器学习模型,准确评估传染病的传播风险。在应急响应方面,该系统为早期诊断、智能流行病学调查、数字接触者追踪、疫苗和药物开发以及干预措施评估提供了强大的工具。该系统有助于及早发现、报告和管理疫情,为其他国家和地区提供了宝贵的参考。然而,在加强科学研究和多学科合作、建立可靠的数据收集机制、加强对模型的持续监测和调整、利用最新的大型语言模型等方面仍需继续努力。未来,该系统将进一步优化,以帮助更有效地控制新发传染病和重大传染病。
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来源期刊
Global Transitions
Global Transitions Social Sciences-Development
CiteScore
18.90
自引率
0.00%
发文量
1
审稿时长
20 weeks
期刊最新文献
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