Impact of meteorological factors on the incidence of influenza in Beijing: A 35-year retrospective study based on Yunqi theory

Abstract

Objective: To analyze the impact of meteorological factors on the incidence of influenza based on the Yunqi theory in Beijing area, and to establish an effective forecast model. Methods: Monthly data on the incidence of influenza from 1970 to 2004 and daily data on the meteorological factors (including daily averages of temperature, wind speed, relative humidity, vapor pressure, and daily total precipitation) from 1966 to 2004 were collected and processed under the traditional Chinese medicine (TCM) theory of six qi. A back-propagation artificial neural network was then performed to analyze the data. Results: The highest incidence of influenza occurs in the sixth qi (the period of December and January), which is characterized by dryness and coldness. Altogether six models were successfully established. Climatic data used were of the same year, one year prior, two years prior, and three years prior to the influenza data respectively. The last two models involve climatic data of the previous three years plus the current year and of the past four years plus the current year. Finally, we determined the fifth model has the highest forecast accuracy (49%). Conclusions: Meteorological factors can exert an influence on the incidence of influenza, which corresponds to TCM theory that “the pestilence occurred three years after the abnormal climatic changes”. This study may generate interest among the public health community and other TCM theories can be applied so that public health measures can be taken to prevent and control influenza, particularly during the winter months. Keywords: Incidence of influenza, Meteorological factors, Yunqi theory, Back-propagation artificial neural network