Journal of Integrative Natural Science (통합자연과학논문집)

The Basic Science Institute Chosun University (조선대학교 기초과학연구원)
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Estimation and Classification of COVID-19 through Climate Change: Focusing on Weather Data since 2018

기후변화를 통한 코로나바이러스감염증-19 추정 및 분류: 2018년도 이후 기상데이터를 중심으로

  • Kim, Youn-Su (Department of Computer Science and Statistic, Chosun University) ;
  • Chang, In-Hong (Department of Computer Science and Statistic, Chosun University) ;
  • Song, Kwang-Yoon (Department of Computer Science and Statistic, Chosun University)
  • 김윤수 (조선대학교 전산통계학과) ;
  • 장인홍 (조선대학교 컴퓨터통계학과) ;
  • 송광윤 (조선대학교 컴퓨터통계학과)
  • Received : 2021.05.24
  • Accepted : 2021.06.24
  • Published : 2021.06.30
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Abstract

The causes of climate change are natural and artificial. Natural causes include changes in temperature and sunspot activities caused by changes in solar radiation due to large-scale volcanic activities, while artificial causes include increased greenhouse gas concentrations and land use changes. Studies have shown that excessive carbon use among artificial causes has accelerated global warming. Climate change is rapidly under way because of this. Due to climate change, the frequency and cycle of infectious disease viruses are greater and faster than before. Currently, the world is suffering greatly from coronavirus infection-19 (COVID-19). Korea is no exception. The first confirmed case occurred on January 20, 2020, and the number of infected people has steadily increased due to several waves since then, and many confirmed cases are occurring in 2021. In this study, we conduct a study on climate change before and after COVID-19 using weather data from Korea to determine whether climate change affects infectious disease viruses through logistic regression analysis. Based on this, we want to classify before and after COVID-19 through a logistic regression model to see how much classification rate we have. In addition, we compare monthly classification rates to see if there are seasonal classification differences.

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Acknowledgement

이 논문은 2019년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임(NRF-2019S1A6A3A01059888).

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