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10.1126/sciadv.abd6989 http://scihub22266oqcxt.onion/10.1126/sciadv.abd6989 33674304!7935356!33674304     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Adv 2021 ; 7 (10): ä Nephropedia Template TP {{tp|p=33674304|t=2021. An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time |pdf=|usr=}}{{33674304}} gab.com Text An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time JO: Sci Adv http://www.kidney.de/pget.php?&tw=1&pmid=33674304 #FOAvip Given still-high levels of coronavirus disease 2019 (COVID-19) susceptibility and inconsistent transmission-containing strategies, outbreaks have continued to emerge across the United States. Until effective vaccines are widely deployed, curbing COVID-19 will require carefully timed nonpharmaceutical interventions (NPIs). A COVID-19 early warning system is vital for this. Here, we evaluate digital data streams as early indicators of state-level COVID-19 activity from 1 March to 30 September 2020. We observe that increases in digital data stream activity anticipate increases in confirmed cases and deaths by 2 to 3 weeks. Confirmed cases and deaths also decrease 2 to 4 weeks after NPI implementation, as measured by anonymized, phone-derived human mobility data. We propose a means of harmonizing these data streams to identify future COVID-19 outbreaks. Our results suggest that combining disparate health and behavioral data may help identify disease activity changes weeks before observation using traditional epidemiological monitoring. Twit Text FOAVip An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time ????Sci Adv http://www.kidney.de/pget.php?&tw=1&pmid=33674304 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33674304 #FOAvip English Wikipedia <ref>{{Cite pmid|33674304}}</ref> An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time #MMPMID33674304 Kogan NE; Clemente L; Liautaud P; Kaashoek J; Link NB; Nguyen AT; Lu FS; Huybers P; Resch B; Havas C; Petutschnig A; Davis J; Chinazzi M; Mustafa B; Hanage WP; Vespignani A; Santillana M Sci Adv 2021[Mar]; 7 (10): ä PMID33674304show ga Given still-high levels of coronavirus disease 2019 (COVID-19) susceptibility and inconsistent transmission-containing strategies, outbreaks have continued to emerge across the United States. Until effective vaccines are widely deployed, curbing COVID-19 will require carefully timed nonpharmaceutical interventions (NPIs). A COVID-19 early warning system is vital for this. Here, we evaluate digital data streams as early indicators of state-level COVID-19 activity from 1 March to 30 September 2020. We observe that increases in digital data stream activity anticipate increases in confirmed cases and deaths by 2 to 3 weeks. Confirmed cases and deaths also decrease 2 to 4 weeks after NPI implementation, as measured by anonymized, phone-derived human mobility data. We propose a means of harmonizing these data streams to identify future COVID-19 outbreaks. Our results suggest that combining disparate health and behavioral data may help identify disease activity changes weeks before observation using traditional epidemiological monitoring. |*Epidemiological Monitoring[MESH] |COVID-19/*diagnosis/*epidemiology/virology[MESH] |Disease Outbreaks[MESH] |Humans[MESH] |Probability[MESH] |SARS-CoV-2/*physiology[MESH] |Time Factors[MESH]An early warning approach to monitor COVID-19 activity with multiple d(epmc).pdf DeepDyve Pubget Overpricing