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Changes of Grocery Shopping Frequencies and Associations with Food Deserts during the COVID-19 Pandemic in the United States.美国 COVID-19 大流行期间杂货店购物频率的变化及其与食品荒漠的关系。
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In-person, pick up or delivery? Evolving patterns of household spending behavior through the early reopening phase of the COVID-19 pandemic.亲自前往、自取还是送货上门?新冠疫情早期解封阶段家庭消费行为的演变模式。
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利用机器学习预测新冠疫情早期的杂货店访问情况。

Predicting Grocery Store Visits During the Early Outbreak of COVID-19 with Machine Learning.

作者信息

Bian Ruijie, Murray-Tuite Pamela, Wolshon Brian

机构信息

Louisiana Transportation Research Center, Louisiana State University, Baton Rouge, LA.

Glenn Department of Civil Engineering, Clemson University, Clemson, SC.

出版信息

Transp Res Rec. 2023 Apr;2677(4):79-91. doi: 10.1177/03611981211043538. Epub 2021 Sep 22.

DOI:10.1177/03611981211043538
PMID:37153205
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10149515/
Abstract

While non-essential travel was canceled during the coronavirus infectious disease (COVID-19) pandemic, grocery shopping was essential. The objectives of this study were to: 1) examine how grocery store visits changed during the early outbreak of COVID-19, and 2) estimate a model to predict the change of grocery store visits in the future, within the same phase of the pandemic. The study period (February 15-May 31, 2020) covered the outbreak and phase-one re-opening. Six counties/states in the United States were examined. Grocery store visits (in-store or curbside pickup) increased over 20% when the national emergency was declared on March 13 and then decreased below the baseline within a week. Grocery store visits on weekends were affected more significantly than those on workdays before late April. Grocery store visits in some states (including California, Louisiana, New York, and Texas) started returning to normal by the end of May, but that was not the case for some of the counties (including those with the cities of Los Angeles and New Orleans). With data from Google Mobility Reports, this study used a long short-term memory network to predict the change of grocery store visits from the baseline in the future. The networks trained with the national data or the county data performed well in predicting the general trend of each county. The results from this study could help understand mobility patterns of grocery store visits during the pandemic and predict the process of returning to normal.

摘要

在冠状病毒感染疾病(COVID-19)大流行期间,非必要旅行被取消,但食品杂货店购物是必要的。本研究的目的是:1)研究在COVID-19早期爆发期间食品杂货店的访问量如何变化,以及2)估计一个模型以预测在大流行同一阶段未来食品杂货店访问量的变化。研究期间(2020年2月15日至5月31日)涵盖了疫情爆发和第一阶段重新开放。对美国的六个县/州进行了考察。3月13日宣布国家紧急状态时,食品杂货店的访问量(店内购物或路边提货)增加了20%以上,然后在一周内降至基线以下。在4月下旬之前,周末的食品杂货店访问量比工作日受到的影响更大。到5月底,一些州(包括加利福尼亚州、路易斯安那州、纽约州和得克萨斯州)的食品杂货店访问量开始恢复正常,但一些县(包括有洛杉矶和新奥尔良市的县)并非如此。利用谷歌移动报告的数据,本研究使用长短期记忆网络来预测未来食品杂货店访问量相对于基线的变化。用国家数据或县数据训练的网络在预测每个县的总体趋势方面表现良好。本研究结果有助于了解大流行期间食品杂货店访问的流动模式,并预测恢复正常的过程。