在COVID-19爆发期间,从住宿预订数据中推断个人流动性决定的时间
Koichi Ito1, Shunsuke Kanemitsu2, Ryusuke Kimura3
1Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto 610-0394, Japan.
Royal Society open science
|July 31, 2025
概括
了解疫情期间人类流动性的变化是控制的关键. 这项研究使用住宿数据来揭示人们何时决定改变他们的旅行,改进疫情应对策略.
科学领域:
- 流行病学 流行病学
- 行为科学 行为科学
- 数据科学数据科学数据科学
背景情况:
- 控制传染病爆发需要了解人类流动性转移和决策时间.
- 现有的移动数据往往缺乏对决策过程的洞察力,只关注执行的旅行.
- 对流行病的行为反应的时间方面仍未得到充分探索.
研究的目的:
- 提取和分析人类的决策过程,关于在流行病情况下的移动性变化.
- 将来自住宿数据的决策时间与实际的流动模式进行比较.
- 为了确定个人何时做出移动决策,以应对不断变化的流行病状况.
主要方法:
- 利用住宿预订数据推断出与流动性有关的决定的时间.
- 将推断的决策数据与执行的移动数据进行比较,包括工作场所和其他地点的"逗留时间".
- 采用定量分析来将决策过程与观察到的人类流动性相关联.
主要成果:
- 住宿预订数据准确地预测了人类流动模式.
- 推断的决策过程显示,与与工作场所相比,与在非工作场所的地点度过的时间有更强的相关性.
- 发现流动性决策整合了最近 (2-5周) 和过去几周的信息.
结论:
- 住宿预订数据为了解疫情期间人类流动性决定的时间提供了有价值的代理.
- 移动性决定的时间受短期和长期考虑的影响.
- 这项研究为分析对流行病的行为反应提供了一种新的方法,对公共卫生干预至关重要.
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