Kollepara Pratyush, Dey Subhrasankha, Tomko Martin, Martino Erika, Bentley Rebecca, Tizzoni Michele, Geard Nicholas, Zachreson Cameron
School of Computing and Information Systems, The University of Melbourne, Parkville, Victoria, Australia.
Department of Mathematical and Physical Sciences, La Trobe University, Melbourne, Victoria, Australia.
R Soc Open Sci. 2025 Jan 15;12(1):241463. doi: 10.1098/rsos.241463. eCollection 2025 Jan.
During the COVID-19 pandemic, both government-mandated lockdowns and discretionary changes in behaviour combined to produce dramatic and abrupt changes to human mobility patterns. To understand the socioeconomic determinants of intervention compliance and discretionary behavioural responses to epidemic threats, we investigate whether changes in human mobility showed a systematic variation by socioeconomic status during two distinct periods of the COVID-19 pandemic in Australia. We analyse mobility data from two major urban centres and compare the trends during mandated stay-at-home policies and after the full relaxation of nonpharmaceutical interventions, which coincided with a large surge of COVID-19 cases. We analyse data aggregated from de-identified global positioning system trajectories, collated from providers of mobile phone applications and aggregated to small spatial regions. Our results demonstrate systematic decreases in mobility relative to the pre-pandemic baseline with the index of education and occupation, for both pandemic periods. On the other hand, the index of economic resources was not correlated with mobility changes. This result contrasts with observations from other national contexts, where reductions in mobility typically increased strongly with indicators of wealth. Our analysis suggests that economic support policies in place during the initial period of stay-at-home orders in Australia facilitated broad reductions in mobility across the economic spectrum.
在新冠疫情期间,政府强制实施的封锁措施以及人们自主做出的行为改变共同导致了人类流动模式的急剧和突然变化。为了了解干预措施依从性的社会经济决定因素以及对疫情威胁的自主行为反应,我们调查了在澳大利亚新冠疫情的两个不同阶段,人类流动的变化是否因社会经济地位而呈现出系统性差异。我们分析了来自两个主要城市中心的流动数据,并比较了强制居家政策期间以及非药物干预全面放宽后(这一时期恰逢新冠病例大幅激增)的趋势。我们分析了从去识别化的全球定位系统轨迹汇总而来的数据,这些轨迹由手机应用程序提供商整理,并汇总到小空间区域。我们的结果表明,在两个疫情阶段,相对于疫情前的基线水平,随着教育和职业指数的变化,流动性都出现了系统性下降。另一方面,经济资源指数与流动性变化没有关联。这一结果与其他国家的观察结果形成对比,在其他国家,流动性的下降通常与财富指标密切相关。我们的分析表明,澳大利亚在居家令初期实施的经济支持政策促进了各经济阶层流动性的广泛下降。