Reopening businesses and risk of COVID-19 transmission
Abstract The true risk of a COVID-19 resurgence as states reopen businesses is unknown. In this paper, we used anonymized cell-phone data to quantify the potential risk of COVID-19 transmission in business establishments by building a Business Risk Index that measures transmission risk over time. Th...
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doaj-f64fc81b13a444f28595c17b6e05605a2021-03-21T12:44:43ZengNature Publishing Groupnpj Digital Medicine2398-63522021-03-01411510.1038/s41746-021-00420-9Reopening businesses and risk of COVID-19 transmissionAshley O’Donoghue0Tenzin Dechen1Whitney Pavlova2Michael Boals3Garba Moussa4Manvi Madan5Aalok Thakkar6Frank J. DeFalco7Jennifer P. Stevens8Center for Healthcare Delivery Science, Beth Israel Deaconess Medical CenterCenter for Healthcare Delivery Science, Beth Israel Deaconess Medical CenterDepartment of Statistics, Pennsylvania State UniversityRequisite AnalyticsOpen-ClassroomRequisite AnalyticsUniversity of PennsylvaniaJanssen Research & DevelopmentCenter for Healthcare Delivery Science, Beth Israel Deaconess Medical CenterAbstract The true risk of a COVID-19 resurgence as states reopen businesses is unknown. In this paper, we used anonymized cell-phone data to quantify the potential risk of COVID-19 transmission in business establishments by building a Business Risk Index that measures transmission risk over time. The index was built using two metrics, visits per square foot and the average duration of visits, to account for both density of visits and length of time visitors linger in the business. We analyzed trends in traffic patterns to 1,272,260 businesses across eight states from January 2020 to June 2020. We found that potentially risky traffic behaviors at businesses decreased by 30% by April. Since the end of April, the risk index has been increasing as states reopen. There are some notable differences in trends across states and industries. Finally, we showed that the time series of the average Business Risk Index is useful for forecasting future COVID-19 cases at the county-level (P < 0.001). We found that an increase in a county’s average Business Risk Index is associated with an increase in positive COVID-19 cases in 1 week (IRR: 1.16, 95% CI: (1.1–1.26)). Our risk index provides a way for policymakers and hospital decision-makers to monitor the potential risk of COVID-19 transmission from businesses based on the frequency and density of visits to businesses. This can serve as an important metric as states monitor and evaluate their reopening strategies.https://doi.org/10.1038/s41746-021-00420-9 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ashley O’Donoghue Tenzin Dechen Whitney Pavlova Michael Boals Garba Moussa Manvi Madan Aalok Thakkar Frank J. DeFalco Jennifer P. Stevens |
spellingShingle |
Ashley O’Donoghue Tenzin Dechen Whitney Pavlova Michael Boals Garba Moussa Manvi Madan Aalok Thakkar Frank J. DeFalco Jennifer P. Stevens Reopening businesses and risk of COVID-19 transmission npj Digital Medicine |
author_facet |
Ashley O’Donoghue Tenzin Dechen Whitney Pavlova Michael Boals Garba Moussa Manvi Madan Aalok Thakkar Frank J. DeFalco Jennifer P. Stevens |
author_sort |
Ashley O’Donoghue |
title |
Reopening businesses and risk of COVID-19 transmission |
title_short |
Reopening businesses and risk of COVID-19 transmission |
title_full |
Reopening businesses and risk of COVID-19 transmission |
title_fullStr |
Reopening businesses and risk of COVID-19 transmission |
title_full_unstemmed |
Reopening businesses and risk of COVID-19 transmission |
title_sort |
reopening businesses and risk of covid-19 transmission |
publisher |
Nature Publishing Group |
series |
npj Digital Medicine |
issn |
2398-6352 |
publishDate |
2021-03-01 |
description |
Abstract The true risk of a COVID-19 resurgence as states reopen businesses is unknown. In this paper, we used anonymized cell-phone data to quantify the potential risk of COVID-19 transmission in business establishments by building a Business Risk Index that measures transmission risk over time. The index was built using two metrics, visits per square foot and the average duration of visits, to account for both density of visits and length of time visitors linger in the business. We analyzed trends in traffic patterns to 1,272,260 businesses across eight states from January 2020 to June 2020. We found that potentially risky traffic behaviors at businesses decreased by 30% by April. Since the end of April, the risk index has been increasing as states reopen. There are some notable differences in trends across states and industries. Finally, we showed that the time series of the average Business Risk Index is useful for forecasting future COVID-19 cases at the county-level (P < 0.001). We found that an increase in a county’s average Business Risk Index is associated with an increase in positive COVID-19 cases in 1 week (IRR: 1.16, 95% CI: (1.1–1.26)). Our risk index provides a way for policymakers and hospital decision-makers to monitor the potential risk of COVID-19 transmission from businesses based on the frequency and density of visits to businesses. This can serve as an important metric as states monitor and evaluate their reopening strategies. |
url |
https://doi.org/10.1038/s41746-021-00420-9 |
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