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10.1503/cmaj.210132 http://scihub22266oqcxt.onion/10.1503/cmaj.210132 33827852!8101979!33827852     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       CMAJ 2021 ; 193 (17): E592-E600 Nephropedia Template TP {{tp|p=33827852|t=2021. The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada |pdf=|usr=}}{{33827852}} gab.com Text The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada JO: CMAJ http://www.kidney.de/pget.php?&tw=1&pmid=33827852 #FOAvip BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures. Twit Text FOAVip The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada ????CMAJ http://www.kidney.de/pget.php?&tw=1&pmid=33827852 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33827852 #FOAvip English Wikipedia <ref>{{Cite pmid|33827852}}</ref> The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada #MMPMID33827852 Brown KA; Soucy JR; Buchan SA; Sturrock SL; Berry I; Stall NM; Juni P; Ghasemi A; Gibb N; MacFadden DR; Daneman N CMAJ 2021[Apr]; 193 (17): E592-E600 PMID33827852show ga BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures. |COVID-19 Testing/*trends[MESH] |COVID-19/epidemiology/*prevention & control[MESH] |Canada/epidemiology[MESH] |Disease Transmission, Infectious/*prevention & control[MESH] |Female[MESH] |Forecasting[MESH] |Humans[MESH] |Incidence[MESH] |Interrupted Time Series Analysis[MESH] |Male[MESH] |Physical Distancing[MESH] |Public Health[MESH]The mobility gap: estimating mobility thresholds required to control S(epmc).pdf DeepDyve Pubget Overpricing