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10.23750/abm.v91i3.10030 http://scihub22266oqcxt.onion/10.23750/abm.v91i3.10030 32921704!7716951!32921704     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32921704&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 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       Acta+Biomed 2020 ; 91 (3): e2020006 Nephropedia Template TP {{tp|p=32921704|t=2020. Google search volume predicts the emergence of COVID-19 outbreaks |pdf=|usr=}}{{32921704}} gab.com Text Google search volume predicts the emergence of COVID-19 outbreaks JO: Acta Biomed http://www.kidney.de/pget.php?&tw=1&pmid=32921704 #FOAvip BACKGROUND AND AIM: Digital epidemiology is increasingly used for supporting traditional epidemiology. This study was hence aimed to explore whether the Google search volume may have been useful to predict the trajectory of coronavirus disease 2019 (COVID-19) outbreak in Italy. MATERIALS AND METHODS: We accessed Google Trends for collecting data on weekly Google searches for the keywords "tosse" (i.e., cough), "febbre" (i.e., fever) and "dispnea" (dyspnea) in Italy, between February and May 2020. The number of new weekly cases of COVID-19 in Italy was also obtained from the website of the National Institute of Health. RESULTS: The peaks of Google searches for the three terms predicted by 3 weeks that of newly diagnosed COVID-19 cases. The peaks of weekly Google searches for "febbre" (fever), "tosse"( cough) and "dispnea" (dyspnea) were 1.7-, 2.2- and 7.7-fold higher compared to the week before the diagnosis of the first national case. No significant correlation was found between the number of newly diagnosed COVID-19 cases and Google search volumes of "tosse" (cough) and "febbre" (fever), whilst "dyspnea" (dyspnea) was significantly correlated (r= 0.50; p=0.034). The correlation between newly diagnosed COVID-19 cases and "tosse" (cough; r=0.65; p=0.008) or "febbre" (fever; 0.69; p=0.004) become statistically significant with a 3-week delay. All symptoms were also significantly inter-correlated. Conclusions; Continuously monitoring the volume of Google searches and mapping their origin can be a potentially valuable instrument to help predicting and identifying local recrudescence of COVID-19. Twit Text FOAVip Google search volume predicts the emergence of COVID-19 outbreaks ????Acta Biomed http://www.kidney.de/pget.php?&tw=1&pmid=32921704 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32921704 #FOAvip English Wikipedia <ref>{{Cite pmid|32921704}}</ref> Google search volume predicts the emergence of COVID-19 outbreaks #MMPMID32921704 Lippi G; Mattiuzzi C; Cervellin G Acta Biomed 2020[Sep]; 91 (3): e2020006 PMID32921704show ga BACKGROUND AND AIM: Digital epidemiology is increasingly used for supporting traditional epidemiology. This study was hence aimed to explore whether the Google search volume may have been useful to predict the trajectory of coronavirus disease 2019 (COVID-19) outbreak in Italy. MATERIALS AND METHODS: We accessed Google Trends for collecting data on weekly Google searches for the keywords "tosse" (i.e., cough), "febbre" (i.e., fever) and "dispnea" (dyspnea) in Italy, between February and May 2020. The number of new weekly cases of COVID-19 in Italy was also obtained from the website of the National Institute of Health. RESULTS: The peaks of Google searches for the three terms predicted by 3 weeks that of newly diagnosed COVID-19 cases. The peaks of weekly Google searches for "febbre" (fever), "tosse"( cough) and "dispnea" (dyspnea) were 1.7-, 2.2- and 7.7-fold higher compared to the week before the diagnosis of the first national case. No significant correlation was found between the number of newly diagnosed COVID-19 cases and Google search volumes of "tosse" (cough) and "febbre" (fever), whilst "dyspnea" (dyspnea) was significantly correlated (r= 0.50; p=0.034). The correlation between newly diagnosed COVID-19 cases and "tosse" (cough; r=0.65; p=0.008) or "febbre" (fever; 0.69; p=0.004) become statistically significant with a 3-week delay. All symptoms were also significantly inter-correlated. Conclusions; Continuously monitoring the volume of Google searches and mapping their origin can be a potentially valuable instrument to help predicting and identifying local recrudescence of COVID-19. |*Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology[MESH] |Disease Outbreaks/*statistics & numerical data[MESH] |Humans[MESH] |Italy/epidemiology[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH] |Predictive Value of Tests[MESH] |SARS-CoV-2[MESH]Google search volume predicts the emergence of COVID-19 outbreaks (epmc).pdf DeepDyve Pubget Overpricing