Kevin A Brown1, Jean-Paul R Soucy2, Sarah A Buchan2, Shelby L Sturrock2, Isha Berry2, Nathan M Stall2, Peter Jüni2, Amir Ghasemi2, Nicholas Gibb2, Derek R MacFadden2, Nick Daneman1. 1. Public Health Ontario (Brown, Buchan, Daneman); Dalla Lana School of Public Health (Brown, Soucy, Buchan, Sturrock, Berry), and The Institute for Health Policy, Management, and Evaluation (Stall, Jüni, Daneman), University of Toronto; Applied Health Research Centre, St. Michael's Hospital (Jüni); Sinai Health System and the University Health Network (Stall); Women's College Hospital (Stall); Department of Medicine (Stall, Daneman), University of Toronto, Toronto, Ont.; Communications Research Centre Canada (Ghasemi); Public Health Agency of Canada (Gibb); Ottawa Hospital Research Institute (MacFadden), Ottawa, Ont.; Division of Infectious Diseases (Daneman), Sunnybrook Research Institute, Toronto, Ont. kevin.brown@utoronto.ca nick.daneman@sunnybrook.ca. 2. Public Health Ontario (Brown, Buchan, Daneman); Dalla Lana School of Public Health (Brown, Soucy, Buchan, Sturrock, Berry), and The Institute for Health Policy, Management, and Evaluation (Stall, Jüni, Daneman), University of Toronto; Applied Health Research Centre, St. Michael's Hospital (Jüni); Sinai Health System and the University Health Network (Stall); Women's College Hospital (Stall); Department of Medicine (Stall, Daneman), University of Toronto, Toronto, Ont.; Communications Research Centre Canada (Ghasemi); Public Health Agency of Canada (Gibb); Ottawa Hospital Research Institute (MacFadden), Ottawa, Ont.; Division of Infectious Diseases (Daneman), Sunnybrook Research Institute, Toronto, Ont.
Abstract
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.
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.
Authors: Eric Lavigne; Niilo Ryti; Antonio Gasparrini; Francesco Sera; Scott Weichenthal; Hong Chen; Teresa To; Greg J Evans; Liu Sun; Aman Dheri; Lionnel Lemogo; Serge Olivier Kotchi; Dave Stieb Journal: Thorax Date: 2022-03-31 Impact factor: 9.139
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