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10.1016/j.ipm.2020.102486 http://scihub22266oqcxt.onion/10.1016/j.ipm.2020.102486 33519039!7836698!33519039     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Inf+Process+Manag 2021 ; 58 (3): 102486 Nephropedia Template TP {{tp|p=33519039|t=2021. Turn to the Internet First? Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend |pdf=|usr=}}{{33519039}} gab.com Text Turn to the Internet First Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend JO: Inf Process Manag http://www.kidney.de/pget.php?&tw=1&pmid=33519039 #FOAvip The surveillance and forecast of newly confirmed cases are important to mobilize medical resources and facilitate policymaking during a public health emergency. Digital surveillance using data available online has increasingly become a trend with the advancement of the Internet. In this study, we assessed the predictive value of multiple online medical behavioral data, including online medical consultation (OMC), online medical appointment (OMA), and online medical search (OMS) for the regional outbreak of coronavirus disease 2019 in Shenzhen, China during January 1, 2020 to March 5, 2020. Multivariate vector autoregression models were used for the prediction. The results identified a novel predictor, OMC, which can forecast the disease trend up to 2 days ahead of the official reports of confirmed cases from the local health department. OMS data had relatively weaker predictive power than OMC in our model, and OMA data failed to predict the confirmed cases. This study highlights the importance of OMC data and has implication in providing evidence-based guidelines for local authorities to evaluate risks and allocate resources during the pandemic. Twit Text FOAVip Turn to the Internet First Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend ????Inf Process Manag http://www.kidney.de/pget.php?&tw=1&pmid=33519039 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33519039 #FOAvip English Wikipedia <ref>{{Cite pmid|33519039}}</ref> Turn to the Internet First? Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend #MMPMID33519039 Huang W; Cao B; Yang G; Luo N; Chao N Inf Process Manag 2021[May]; 58 (3): 102486 PMID33519039show ga The surveillance and forecast of newly confirmed cases are important to mobilize medical resources and facilitate policymaking during a public health emergency. Digital surveillance using data available online has increasingly become a trend with the advancement of the Internet. In this study, we assessed the predictive value of multiple online medical behavioral data, including online medical consultation (OMC), online medical appointment (OMA), and online medical search (OMS) for the regional outbreak of coronavirus disease 2019 in Shenzhen, China during January 1, 2020 to March 5, 2020. Multivariate vector autoregression models were used for the prediction. The results identified a novel predictor, OMC, which can forecast the disease trend up to 2 days ahead of the official reports of confirmed cases from the local health department. OMS data had relatively weaker predictive power than OMC in our model, and OMA data failed to predict the confirmed cases. This study highlights the importance of OMC data and has implication in providing evidence-based guidelines for local authorities to evaluate risks and allocate resources during the pandemic. äTurn to the Internet First? Using Online Medical Behavioral Data to Fo(epmc).pdf DeepDyve Pubget Overpricing