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10.4258/hir.2020.26.3.175 http://scihub22266oqcxt.onion/10.4258/hir.2020.26.3.175 32819035!7438693!32819035     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Healthc+Inform+Res 2020 ; 26 (3): 175-184 Nephropedia Template TP {{tp|p=32819035|t=2020. Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis |pdf=|usr=}}{{32819035}} gab.com Text Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis JO: Healthc Inform Res http://www.kidney.de/pget.php?&tw=1&pmid=32819035 #FOAvip OBJECTIVE: Considering the rising menace of coronavirus disease 2019 (COVID-19), it is essential to explore the methods and resources that might predict the case numbers expected and identify the locations of outbreaks. Hence, we have done the following 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 these terms in Google Web, News, and YouTube, and the data on COVID-19 case numbers were obtained. Spearman correlation and 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 of the search terms "coronavirus" and "corona" was high (r > 0.7) with the daily cumulative and new COVID-19 cases for a lag period ranging from 9 to 21 days. The maximum lag period for predicting COVID-19 cases was found to be with the News search for the term "coronavirus", with 21 days, i.e., the search volume for "coronavirus" peaked 21 days before the peak number of cases reported by the disease surveillance system. CONCLUSION: Our study revealed that GTs may predict outbreaks of COVID-19, 2 to 3 weeks earlier than the routine disease surveillance, in India. Google search data may be considered as a supplementary tool in COVID-19 monitoring and planning in India. Twit Text FOAVip Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis ????Healthc Inform Res http://www.kidney.de/pget.php?&tw=1&pmid=32819035 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32819035 #FOAvip English Wikipedia <ref>{{Cite pmid|32819035}}</ref> Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis #MMPMID32819035 Venkatesh U; Gandhi PA Healthc Inform Res 2020[Jul]; 26 (3): 175-184 PMID32819035show ga OBJECTIVE: Considering the rising menace of coronavirus disease 2019 (COVID-19), it is essential to explore the methods and resources that might predict the case numbers expected and identify the locations of outbreaks. Hence, we have done the following 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 these terms in Google Web, News, and YouTube, and the data on COVID-19 case numbers were obtained. Spearman correlation and 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 of the search terms "coronavirus" and "corona" was high (r > 0.7) with the daily cumulative and new COVID-19 cases for a lag period ranging from 9 to 21 days. The maximum lag period for predicting COVID-19 cases was found to be with the News search for the term "coronavirus", with 21 days, i.e., the search volume for "coronavirus" peaked 21 days before the peak number of cases reported by the disease surveillance system. CONCLUSION: Our study revealed that GTs may predict outbreaks of COVID-19, 2 to 3 weeks earlier than the routine disease surveillance, in India. Google search data may be considered as a supplementary tool in COVID-19 monitoring and planning in India. äPrediction of COVID-19 Outbreaks Using Google Trends in India: A Retro(epmc).pdf DeepDyve Pubget Overpricing