Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, USA.
Yahoo Japan Corporation, Tokyo, Japan.
Sci Rep. 2020 Oct 22;10(1):18053. doi: 10.1038/s41598-020-75033-5.
While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease.
虽然大规模移动数据已成为监测 COVID-19 大流行期间流动性模式的流行工具,但日本东京非强制性措施对人类流动模式的影响仍未得到充分研究。在这里,我们使用从东京 20 多万名匿名手机用户收集的移动数据,分析了人类流动行为、社会接触率及其与 COVID-19 传染性的相关性的时间变化。分析得出的结论是,到 4 月 15 日(进入紧急状态后的第一周),人类流动行为减少了约 50%,导致东京的社会接触减少了 70%,这表明与非强制性措施之间存在很强的关系。此外,数据驱动的人类流动指标的减少与东京 COVID-19 估计有效繁殖数的减少呈相关性。这些经验性的见解可以为决策者提供信息,决定减少流动性的足够水平以控制疾病。