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Big Data Study about the Effects of Weather Factors on Food Poisoning Incidence

기상요인과 식중독 발병의 연관성에 대한 빅 데이터 분석

  • Park, Ji-Ae (Dept. of Data Science, Kookmin University) ;
  • Kim, Jang-Mook (Dept. of Health Administration, College of Health Science, Dankook University) ;
  • Lee, Ho-Sung (NowDream Co., Ltd.) ;
  • Lee, He-Jin (National Institute of Meteorological Research, KMA)
  • 박지애 (국민대학교 데이터사이언스학과) ;
  • 김장묵 (단국대학교 보건행정학과) ;
  • 이호성 ((주)나우드림) ;
  • 이해진 (기상청 서비스기반국 기상기술융합팀)
  • Received : 2016.01.15
  • Accepted : 2016.03.20
  • Published : 2016.03.28

Abstract

This research attempts an analysis that fuses the big data concerning weather variation and health care from January 1, 2011 to December 31, 2014; it gives the weather factor as to what kind of influence there is for the incidence of food poisoning, and also endeavors to be helpful regarding national health prevention. By using R, the Logistic and Lasso Logistic Regression were analyzed. The main factor germ generating the food poisoning was classified and the incidence was confirmed for the germ of bacteria and virus. According to the result of the analysis of Logistic Regression, we found that the incidence of bacterial food poisoning was affected by the following influences: the average temperature, amount of sunshine deviation, and deviation of temperature. Furthermore, the weather factors, having an effect on the incidence of viral food poisoning, were: the minimum vapor pressure, amount of sunshine deviation and deviation of temperature. This study confirmed the correlation of meteorological factors and incidence of food poisoning. It was also found out that even if the incidence from two causes were influenced by the same weather factor, the incidence might be oppositely affected by the characteristic of the germs.

Keywords

Big Data;Meteorological Data;Bacterial Food Poisoning;Viral Food Poisoning;Incidence

Acknowledgement

Supported by : Korea Meteorological Administration, KMIPA

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