Influenza early warning model based on Yunqi theory

OBJECTIVE: To establish an early warning model to simulate the outbreak of influenza based on weather conditions and Yunqi theory, an ancient calendar theory of Chinese medicine (CM). METHODS: Tianjin, a northeastern city in China, was chosen as the region of research and applied the influenza-like illness attack rate (ILI)% as the baseline and warning line to determine the severity of influenza epidemic. Then, an influenza early warning model was constructed based on the theory of rough set and support vector machines (RS-SVM), and the relationship between influenza and meteorology was explored through analyzing the monitoring data. RESULTS: The predictive performance of the model was good, which had achieved 81.8% accuracy when grouping the obtained data into three levels that represent no danger, danger of a light epidemic, and danger of a severe epidemic. The test results showed that if the host qi and guest qi were not balanced, this kind of situation was more likely to cause influenza outbreaks. CONCLUSIONS: The outbreak of influenza closely relates to temperature, humidity, visibility, and wind speed and is consistent with some part of CM doctrine. The result also indicates that there is some reasonable evidence in the Yunqi theory.