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利用移动设备在新冠疫情期间进行全国范围的人口流动监测产生了(大量)数据。

Countrywide population movement monitoring using mobile devices generated (big) data during the COVID-19 crisis.

机构信息

Digital Health and Data Utilisation Team, Health Services Management Training Centre, Faculty of Health and Public Administration, Semmelweis University, Budapest, Hungary.

MTA-ELTE Statistical and Biological Physics Research Group, Eotvos Lorand Research Network (ELKH), Department of Biological Physics, Eotvos Lorand University, Budapest, Hungary.

出版信息

Sci Rep. 2021 Mar 15;11(1):5943. doi: 10.1038/s41598-021-81873-6.

Abstract

Mobile phones have been used to monitor mobility changes during the COVID-19 pandemic but surprisingly few studies addressed in detail the implementation of practical applications involving whole populations. We report a method of generating a "mobility-index" and a "stay-at-home/resting-index" based on aggregated anonymous Call Detail Records of almost all subscribers in Hungary, which tracks all phones, examining their strengths and weaknesses, comparing it with Community Mobility Reports from Google, limited to smartphone data. The impact of policy changes, such as school closures, could be identified with sufficient granularity to capture a rush to shops prior to imposition of restrictions. Anecdotal reports of large scale movement of Hungarians to holiday homes were confirmed. At the national level, our results correlated well with Google mobility data, but there were some differences at weekends and national holidays, which can be explained by methodological differences. Mobile phones offer a means to analyse population movement but there are several technical and privacy issues. Overcoming these, our method is a practical and inexpensive way forward, achieving high levels of accuracy and resolution, especially where uptake of smartphones is modest, although it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring.

摘要

手机已被用于监测 COVID-19 大流行期间的流动性变化,但令人惊讶的是,很少有研究详细探讨涉及整个人口的实际应用的实施情况。我们报告了一种基于匈牙利几乎所有用户匿名通话记录汇总来生成“流动性指数”和“居家/休息指数”的方法,该方法可以跟踪所有手机,检查其优缺点,并将其与谷歌的社区流动性报告进行比较,后者仅适用于智能手机数据。通过足够的粒度来识别政策变化(例如学校关闭)的影响,以捕捉在实施限制之前对商店的抢购。关于大量匈牙利人前往度假屋的传闻得到了证实。在国家层面上,我们的结果与谷歌的移动数据相关性良好,但周末和节假日存在一些差异,这可以用方法上的差异来解释。手机提供了一种分析人口流动的方法,但存在一些技术和隐私问题。克服这些问题后,我们的方法是一种实用且廉价的前进方式,可实现高精度和高分辨率,尤其是在智能手机使用率适中的情况下,尽管它不能替代用于接触者追踪和隔离监测的基于智能手机的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4933/7961025/f75921a70638/41598_2021_81873_Fig1_HTML.jpg

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