Research Progress of the Infectious Disease Prediction Models Based on Internet Data
10.3969/j.issn.1673-6036.2024.02.006
- VernacularTitle:基于互联网数据的传染病预测模型研究进展
- Author:
Qile HE
1
;
Jinyao ZHANG
;
Zhuocun WU
;
Yuqing YANG
;
Wei ZHAO
;
Hongpu HU
Author Information
1. 中国医学科学院/北京协和医学院医学信息研究所 北京 100020
- Keywords:
infectious disease surveillance and early warning;
epidemic intelligence;
prediction model;
search engine;
internet
- From:
Journal of Medical Informatics
2024;45(2):32-37
- CountryChina
- Language:Chinese
-
Abstract:
Purpose/Significance The paper systematically reviews relevant research on infectious disease prediction models based on internet data,helps to realize the advancement of infectious disease surveillance,and provides references for the construction of intelli-gent three-dimensional prevention and treatment system of infectious diseases.Method/Process The development history and research direction of infectious disease surveillance and early warning based on internet data collected in the core database of Web of Science and CNKI in the past 20 years are reviewed,major existing problems and challenges are analyzed,and common prediction models and their optimization directions are summarized.Result/Conclusion The study on internet infectious disease surveillance shows the trend of diver-sification of monitoring diseases,refinement and specialization of data sources.Due to the complexity and uncertainty of internet data,most of the existing models are only suitable for short-term or real-time prediction.By constructing a combination model,strengthening multi-source data fusion,improving the selection of keywords and influencing factors,the model can be further optimized and the fitting effect and prediction capacity can be strengthened.
