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Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis
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논문 기본 정보

Type
Academic journal
Author
U Venkatesh (Vardhman Mahavir Medical College (VMMC) and Safdarjung Hospital) Periyasamy Aravind Gandhi (Postgraduate Institute of Medical Education and Research)
Journal
대한의료정보학회 Healthcare Informatics Research Healthcare Informatics Research 제26권 제3호 KCI Accredited Journals
Published
2020.1
Pages
175 - 184 (10page)

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Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis
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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.
#Public Health Surveillance #Information Technology #COVID-19 #Trends #Severe Acute Respiratory Syndrome

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World Health Organization / Coronavirus disease (COVID-19) situation report 169 google schola Gandhi P A / 2020 / Epidemiological studies on COVID-19 pandemic in India: too little and too late? / Med J Armed Forces India Crossref Government of India, Ministry of Health & Family Welfare / Integrated Disease Surveillance Programme (IDSP) google schola Seo DW / 2014 / Cumulative query method for influenza surveillance using search engine data / J Med Internet Res 16(12):e289 google schola Shin SY / 2016 / High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea / Sci Rep 6:32920 google schola

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