Delay in the Effect of Restricting Community Mobility on the Spread of COVID-19 During the First Wave in the United States
- Authors
- He, Shan; Lee, Jooyoung; Langworthy, Benjamin; Xin, Junyi; James, Peter; Yang, Yang; Wang, Molin
- Issue Date
- Jan-2022
- Publisher
- OXFORD UNIV PRESS INC
- Keywords
- community mobility; COVID-19; infectious diseases; spatio-temporal models; statistical modeling
- Citation
- OPEN FORUM INFECTIOUS DISEASES, v.9, no.1
- Journal Title
- OPEN FORUM INFECTIOUS DISEASES
- Volume
- 9
- Number
- 1
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/61769
- DOI
- 10.1093/ofid/ofab586
- ISSN
- 2328-8957
- Abstract
- Background. It remains unclear how changes in human mobility shaped the transmission dynamic of coronavirus disease 2019 (COVID-19) during its first wave in the United States. Methods. By coupling a Bayesian hierarchical spatiotemporal model with reported case data and Google mobility data at the county level, we found that changes in movement were associated with notable changes in reported COVID-19 incidence rates about 5 to 7 weeks later. Results. Among all movement types, residential stay was the most influential driver of COVID-19 incidence rate, with a 10% increase 7 weeks ago reducing the disease incidence rate by 13% (95% credible interval, 6%-20%). A 10% increase in movement from home to workplaces, retail and recreation stores, public transit, grocery stores, and pharmacies 7 weeks ago was associated with an increase of 5%-8% in the COVID-10 incidence rate. In contrast, parks-related movement showed minimal impact. Conclusions. Policy-makers should anticipate such a delay when planning intervention strategies restricting human movement.
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Collections - College of Business & Economics > Department of Applied Statistics > 1. Journal Articles
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