Fu Z O, Bao C J, Li Z J, Wang L P, Li Y, Leng H B, Peng Z H
School of Public Health, Nanjing Medical University, Nanjing 211166, China; Binxian Municipal Health Commission, Haerbin 150400, China.
Jiangsu Center for Disease Control and Prevention, Nanjing 210009, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2020 Jun 10;41(6):975-980. doi: 10.3760/cma.j.cn112338-20190908-00657.
Shortcomings have been inherited in the traditional influenza early warning system, often expressed through the scope, accuracy on prediction and real-time performance of the monitor related programs. With the new round of scientific and technological revolution and the increasingly maturity of modern information system, related technology on influenza early warning has become the focus of research in this field, based on big data analysis technology. Using the traditional influenza surveillance and early warning system as reference, this paper summarizes the progress of influenza early warning research, based on the Internet, influencing factors, time and space trends, and risk assessment ., to summarize the trends on the advantages, shortcomings and future development of big data, used in the early warning system on influenza.
传统流感预警系统存在一些不足之处，通常体现在监测相关程序的范围、预测准确性和实时性能方面。随着新一轮科技革命以及现代信息系统的日益成熟，基于大数据分析技术的流感预警相关技术已成为该领域的研究热点。本文以传统流感监测与预警系统为参考，总结了基于互联网、影响因素、时空趋势和风险评估的流感预警研究进展，以归纳大数据在流感预警系统中的优势、不足及未来发展趋势。
