Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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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
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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.

본 연구는 2011년 1월1일부터 2014년 12월 31일까지의 기상변이에 관한 빅 데이터와 보건의료의 빅 데이터를 융합하여 식중독 발병률 변이에 기상요인이 어떤 영향을 주는지에 대한 분석을 시도하여 국민건강예방에 도움을 주고자한다. 분석도구 R을 이용하여 로지스틱 회귀와 Lasso 로지스틱 회귀 총 2가지 분석을 하였고, 식중독을 발생시키는 주 원인균을 분류하여 세균성 원인균과 바이러스성 원인균에 의한 식중독 발병률 변이를 확인하였다. 로지스틱 회귀 분석결과, 세균성 원인균에 의한 식중독 발병률에는 평균기온, 일조량편차, 기온편차가 유의미한 영향을 미치고, 바이러스성 원인균에 의한 식중독 발병률에 영향을 미치는 기상요인은 최소증기압, 일조량편차, 기온편차로 나타났다. 본 연구는 기상요인과 식중독 발병률이 상관성이 있음을 확인하였고, 두 가지 원인균에 의한 식중독 발병률이 같은 기상요인에 영향을 받더라도 원인균들의 특성에 따라 식중독 발병률에 반대의 영향을 미치는 것을 확인하였다.

Keywords

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