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| Research on Crisis Detection in Infectious Disease Surveillance Data |
| Wang Ping, Mu Dongmei, Gao Hexuan, Fa Hui |
| School of Public Health, Jilin University, Changchun 130021 |
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Abstract As China s informatization process continues to accelerate, infectious disease surveillance systems have accumulated large amounts of accurate data. According to the theories and methods of information science, we can fully mine the intelligence value of information from infectious disease surveillance data. Analysis of this material can provide decision support services for public health management and prevention departments. In particular, this study focused on data from the China Statistical Yearbook of Infectious Diseases, and the China National Bureau Statistics monthly report on infectious disease prevention and control. The process of monitoring and identifying infectious disease crisis events is summarized as “one goal, three objects, three levels of analysis, and three cores.” Another aspect of infectious disease control is building crisis detection/decision support service systems. Theoretical level, this study assesses data integration, information analysis, and crisis detection in infectious disease events. On a practical level, it integrates methods of statistical information analysis with machine learning to establish a forecasting model of epidemic over time. Its aim is promoting theoretical research and practical innovation related to the monitoring, identification, and crisis detection of infectious diseases.
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Received: 19 June 2018
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