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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.1
- 수록면
- 175 - 184 (10page)
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초록· 키워드
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Objectives: Considering the rising menace of coronavirus disease 2019 (COVID-19), it is essential to explore the methodsand resources that might predict the case numbers expected and identify the locations of outbreaks. Hence, we have done thefollowing study to explore the potential use of Google Trends (GT) in predicting the COVID-19 outbreak in India. Methods:The Google search terms used for the analysis were “coronavirus”, “COVID”, “COVID 19”, “corona”, and “virus”. GTs for theseterms in Google Web, News, and YouTube, and the data on COVID-19 case numbers were obtained. Spearman correlationand lag correlation were used to determine the correlation between COVID-19 cases and the Google search terms. Results:“Coronavirus” and “corona” were the terms most commonly used by Internet surfers in India. Correlation for the GTs ofthe search terms “coronavirus” and “corona” was high (r > 0.7) with the daily cumulative and new COVID-19 cases for a lagperiod ranging from 9 to 21 days. The maximum lag period for predicting COVID-19 cases was found to be with the Newssearch for the term “coronavirus”, with 21 days, i.e., the search volume for “coronavirus” peaked 21 days before the peak numberof cases reported by the disease surveillance system. Conclusions: Our study revealed that GTs may predict outbreaks ofCOVID-19, 2 to 3 weeks earlier than the routine disease surveillance, in India. Google search data may be considered as asupplementary tool in COVID-19 monitoring and planning in India.
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참고문헌 (24)
참고문헌 신청
World Health Organization / Coronavirus disease (COVID-19) situation report 169
Gandhi P A / 2020 / Epidemiological studies on COVID-19 pandemic in India: too little and too late? / Med J Armed Forces India
Government of India, Ministry of Health & Family Welfare / Integrated Disease Surveillance Programme (IDSP)
Seo DW / 2014 / Cumulative query method for influenza surveillance using search engine data / J Med Internet Res 16(12):e289
Shin SY / 2016 / High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea / Sci Rep 6:32920
Gandhi P A / 2020 / Epidemiological studies on COVID-19 pandemic in India: too little and too late? / Med J Armed Forces India
Government of India, Ministry of Health & Family Welfare / Integrated Disease Surveillance Programme (IDSP)
Seo DW / 2014 / Cumulative query method for influenza surveillance using search engine data / J Med Internet Res 16(12):e289
Shin SY / 2016 / High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea / Sci Rep 6:32920
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