主 办:北 京 中 医 药 大 学
ISSN 1006-2157 CN 11-3574/R

JOURNAL OF BEIJIGN UNIVERSITY OF TRADITIONAL CHINE ›› 2015, Vol. 38 ›› Issue (1): 8-13.doi: 10.3969/j.issn.1006-2157.2015.01.002

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Correlation between incidence of Japanese encephalitis and meteorological factors and establishment of forecast model based on theory of five circuits and six qi

ZHANG Xuan, HE Juan   

  1. School of Preclinical Medicine, Beijing University of Chinese Medicine, Beijing 100029
  • Received:2014-10-20 Online:2015-01-30 Published:2015-01-30

Abstract: Objective To study the correlation between high incidence of Japanese encephalitis and meteorological factors in the same year and three years ago based on TCM theory of five circuits and six qi, and establish a medical meteorological forecast model of BP artificial neural network. Methods The data of the monthly incidence of Japanese encephalitis and meteorological factors were collected from 1970 to 2004 (altogether 35 years) in Beijing, from which the period of high incidence of Japanese encephalitis was extracted. Then the forecast model of Japanese encephalitis was established by applying BP artificial neural network analysis to meteorological factors recorded in the same year, one year ago, two years ago and three years ago. Results Fourth qi was the peak period of outbreak of Japanese encephalitis (P<0.01). All forecast models based on recorded meteorological factors yearly were successfully established with forecast accuracy higher than 80%. Additionally, the most important meteorological factors calculated were average wind speed in first qi in the same year, average relative humidity in third qi in the one year ago, average wind speed in first qi in the two years ago, and average wind speed in second qi in the three years ago. Conclusion The high incidence of Japanese encephalitis in Beijing is related to meteorological factors in the year and the three years ago. Furthermore, the forecast model established based on the meteorological factors of the three years ago is evaluated as the best one.

Key words: Japanese encephalitis, BP artificial neural network, meteorological factors, pestilence occurring after three years, theory of five circuits and six qi

CLC Number: 

  • R226