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구글트렌드를 이용한 감염병 관심 동향 2004-2017년

Trends of Infectious Diseases with Google Trends, 2004-2017

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초록

Since 2000, South Korea has had seven cases of infectious diseases. The study used Google Trends to analyze public interest in infectious diseases. The Google Trend data was set up from January 2004 to July 2017. We selected keywords related to 5 infectious diseases(H1N1, Ebola-virus, H7N9, MERS-CoV, ZIKA-virus) and suggested trends and distribution in Korea and around the world. We found two results. The first, the worldwide pattern of infectious disease search (peak) and Korea's pattern (peak) were the same. The second, since the end of the epidemic, the world and Korea have seen a sharp drop in interest in the epidemic. We found that in the case of MERS-CoV or 2019-nCoV, we need to value social safety and maker sustainable preparations. Building trust with the people is also important in times of crisis and require communication strategies between the media and the government.

Abstract

Since 2000, South Korea has had seven cases of infectious diseases. The study used Google Trends to analyze public interest in infectious diseases. The Google Trend data was set up from January 2004 to July 2017. We selected keywords related to 5 infectious diseases(H1N1, Ebola-virus, H7N9, MERS-CoV, ZIKA-virus) and suggested trends and distribution in Korea and around the world. We found two results. The first, the worldwide pattern of infectious disease search (peak) and Korea's pattern (peak) were the same. The second, since the end of the epidemic, the world and Korea have seen a sharp drop in interest in the epidemic. We found that in the case of MERS-CoV or 2019-nCoV, we need to value social safety and maker sustainable preparations. Building trust with the people is also important in times of crisis and require communication strategies between the media and the government.

참고문헌 (21)

  1. 권준옥, "환자안전과 관련된 정부의 정책방향", 한국의료 QA학회지, 15(1), pp.19~25 (2009)
  2. 송태민, "소셜 빅데이터 분석과 활용 방안: 메르스 정보 확산과 위험예측 중심으로", 보건복지포럼, 9(227), pp.49~ (2015)
  3. 윤익준, "인수공통감염병 예방 및 관리의 법적 문제", 법과정책연구, 18(3), pp.99~122 (2018), 한국법정책학회[DOI]
  4. 이미애, "신종·재출현 해외유입 감염병의 진단", The Ewha Medical Journal, 39(2), pp.37~44 (2016)
  5. 전병율, "중동호흡기증후군 사태와 우리나라를 위한 감염병 관리체계", 대한의사협회지, 58(7), pp.590~593 (2015), 대한의사협회[DOI]
  6. 질병관리본부, "감염병 감시연보" (2017), 보건복지부 질병관리본부
  7. 최재욱, "한국 메르스 감염의 역학현황과 공중보건학적 대응조치 방향", 대한의사협회지, 58(6), pp.487~497 (2015), 대한의사협회[DOI]
  8. Alicino, C., "Assessing ebola-related web search behaviour: insights and implications from an analytical study of Google trends-based query volumes", Infectious Diseases of Poverty, 4, pp.54~ (2015)
  9. Beaumont, J., "Introduction: Faith-based organisations and urban social issues", Urban Studies, 45(10), pp.2011~2017 (2008)
  10. Bragazzi, N. L., "Global reaction to the recent outbreaks of Zika virus: Insights from a big data analysis", PloS One, 12(9), pp.e0185263~ (2017)
  11. Luis Fernández-Luque, "Health and Social Media: Perfect Storm of Information", Healthcare Informatics Research, 21(2), pp.67~73 (2015), 대한의료정보학회[DOI]
  12. Ginsberg, J., "Detecting influenza epidemics using search engine query data", Nature, 457(7232), pp.1012~1014 (2009)
  13. "Google Trends" (2020)[URL]
  14. KI, M., "2015 MERS outbreak in Korea: hospital-to-hospital transmission", Epidemiology and Health, 37, pp.e2015033~ (2015)
  15. 기모란, "Epidemiologic characteristics of early cases with 2019 novel coronavirus (2019-nCoV) disease in Korea", Epidemiology and Health, 42, pp.1~7 (2020), 한국역학회[DOI]
  16. Lazer, D., "The parable of Google flu: Traps in big data analysis", Science, 343(6176), pp.1203~1205 (2014)
  17. Milinovich, G. J., "Using internet search queries for infectious disease serveillance: Screening diseases for suitability", BMC Infectious Diseases, 14(1), pp.690~ (2014)
  18. "Naver datalab" (2020)[URL]
  19. Olson, D. R., "Reassessing Google flu trends data for detection of seasonal and pandemic influenza: A comparative epidemiological study at three geographic scales", PLoS Computational Biology, 9(10), pp.e1003256~ (2013)
  20. Shaw, K. A., "The GP's response to pandemic influenza: A qualitative study", Family Practice, 23(3), pp.267~272 (2006)
  21. Wong, Z. S., "Artificial intelligence for infectious disease big data analytics", Infection & Disease & Health, 24(1), pp.44~48 (2019)

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