School of Tourism Management, Sun Yat-sen University, Guangzhou, Guangdong, China.
Institute of Advanced Studies in Humanities and Social Sciences, Beijing Normal University, Zhuhai, China.
Int J Health Plann Manage. 2022 Sep;37(5):2836-2851. doi: 10.1002/hpm.3507. Epub 2022 May 28.
As an emergent health policy response, the population mobility restriction policy was implemented to cope with the unprecedented pandemic that outbroke in early 2020, but its effectiveness showed vast disparities even within a single country. Using multisource data from Baidu mobility big data and the statistics of novel coronavirus disease in China, mobility restrictions (including restrictions on inflow-mobility, outflow-mobility, and intra-city mobility) were examined. It was found that the mobility restriction had contained the development of pandemic, but such effect would gradually recede over time. Moreover, there existed region-specific policy effectiveness. Specifically, outflow-mobility restrictions were ineffective in reducing death cases in population influx areas, and restrictions on inflow-mobility (or intra-city mobility) were ineffective in reducing confirmed cases (or death cases) in population outflow areas. It was concluded that the mobility restriction policy can be effective in epidemic prevention and control in spatial-temporal pattern. However, there was a remarkable disparity in policy effectiveness between different regions with different population mobility patterns.
作为一项紧急的卫生政策应对措施，人口流动限制政策是为了应对 2020 年初爆发的前所未有的大流行病而实施的，但即使在一个国家内部，其效果也存在巨大差异。本研究利用来自百度移动大数据的多源数据和中国新型冠状病毒病统计数据，考察了流动性限制（包括流入流动性限制、流出流动性限制和市内流动性限制）。结果发现，流动性限制确实遏制了疫情的发展，但这种效果会随着时间的推移逐渐减弱。此外，还存在特定于区域的政策效果。具体来说，流出流动性限制并不能有效减少人口流入地区的死亡病例，而对流入流动性（或市内流动性）的限制也不能有效减少人口流出地区的确诊病例（或死亡病例）。研究结论认为，流动性限制政策在时空模式下可以有效防控疫情，但不同人口流动模式的地区之间的政策效果存在显著差异。
