Lyu Zeyu, Takikawa Hiroki
Graduate School, Faculty of Arts and Letters, Tohoku University, Sendai, Japan.
JMIR Med Inform. 2022 Mar 22;10(3):e31557. doi: 10.2196/31557.
The availability of large-scale and fine-grained aggregated mobility data has allowed researchers to observe the dynamics of social distancing behaviors at high spatial and temporal resolutions. Despite the increasing attention paid to this research agenda, limited studies have focused on the demographic factors related to mobility, and the dynamics of social distancing behaviors have not been fully investigated.
This study aims to assist in designing and implementing public health policies by exploring how social distancing behaviors varied among various demographic groups over time.
We combined several data sources, including mobile tracking mobility data and geographical statistics, to estimate the visiting population of entertainment venues across demographic groups, which can be considered the proxy of social distancing behaviors. Next, we used time series analysis methods to investigate how voluntary and policy-induced social distancing behaviors shifted over time across demographic groups.
Our findings demonstrate distinct patterns of social distancing behaviors and their dynamics across age groups. On the one hand, although entertainment venues' population comprises mainly individuals aged 20-40 years, a more significant proportion of the youth has adopted social distancing behaviors and complied with policy implementations compared to older age groups. From this perspective, the increasing contribution to infections by the youth should be more likely to be attributed to their number rather than their violation of social distancing behaviors. On the other hand, although risk perception and self-restriction recommendations can induce social distancing behaviors, their impact and effectiveness appear to be largely weakened during Japan's second state of emergency.
This study provides a timely reference for policymakers about the current situation on how different demographic groups adopt social distancing behaviors over time. On the one hand, the age-dependent disparity requires more nuanced and targeted mitigation strategies to increase the intention of elderly individuals to adopt mobility restriction behaviors. On the other hand, considering that the effectiveness of policy implementations requesting social distancing behaviors appears to decline over time, in extreme cases, the government should consider imposing stricter social distancing interventions, as they are necessary to promote social distancing behaviors and mitigate the transmission of COVID-19.
大规模且细粒度的聚合移动性数据的可用性使研究人员能够在高空间和时间分辨率下观察社会疏远行为的动态。尽管对这一研究议程的关注日益增加，但关注与移动性相关的人口因素的研究有限，且社会疏远行为的动态尚未得到充分研究。
本研究旨在通过探索不同人口群体的社会疏远行为如何随时间变化，协助设计和实施公共卫生政策。
我们结合了多个数据源，包括移动跟踪移动性数据和地理统计数据，以估计不同人口群体中娱乐场所的访客数量，这可被视为社会疏远行为的代理指标。接下来，我们使用时间序列分析方法来研究自愿和政策诱导的社会疏远行为如何随时间在不同人口群体中发生变化。
我们的研究结果表明了不同年龄组社会疏远行为及其动态的明显模式。一方面，尽管娱乐场所的人群主要由20至40岁的个体组成，但与老年群体相比，有更大比例的年轻人采取了社会疏远行为并遵守政策实施。从这个角度来看，年轻人对感染的贡献增加更可能归因于他们的数量，而不是他们违反社会疏远行为。另一方面，尽管风险感知和自我限制建议可以诱导社会疏远行为，但在日本第二次紧急状态期间，它们的影响和有效性似乎大大减弱。
本研究为政策制定者提供了关于不同人口群体如何随时间采取社会疏远行为的当前情况的及时参考。一方面，年龄相关的差异需要更细致和有针对性的缓解策略，以增加老年人采取移动限制行为的意愿。另一方面，考虑到要求社会疏远行为的政策实施效果似乎会随着时间而下降，在极端情况下，政府应考虑实施更严格的社会疏远干预措施，因为这些措施对于促进社会疏远行为和减轻COVID-19的传播是必要的。
