Health Organization, Policy and Economics (HOPE) Group, Centre for Primary Care and Health Services Research, University of Manchester, Manchester, UK.
Eur J Public Health. 2021 Oct 11;31(4):901-907. doi: 10.1093/eurpub/ckab072.
The COVID-19 pandemic forced governments to implement lockdown policies to curb the spread of the disease. These policies explicitly encouraged homeworking, hence reducing the number of commuters with the implicit assumption that restricting peoples' movement reduces risk of infection for travellers and other people in their areas of residence and work. Yet, the spatial interrelation of different areas has been rarely addressed both in the public discourse and in early accounts of the various consequences of COVID-19.
Our study proposes a spatial analysis of the association between commuting flows and COVID-19 mortality in England between March and June 2020, using a range of publicly available area-level data. To account for spatial correlation, we used a structural mobility gravity model to analyze commuting flows between Local Authority Districts. By accounting for these spatial dependencies, we temper concerns of bias and inefficiency affecting simple linear estimates. Additionally, we disentangle the direct and indirect (from other areas) influence of commuting on COVID-19 mortality.
The results of our spatial regression models suggest that higher commuting flows-in general and particularly by public transport-are associated with higher COVID-19 mortality. Our results are consistent with a reduction in COVID-related mortality after the introduction of a national lockdown in March. The spatial-lag term is statistically significant, highlighting the importance of accounting for spatial dependencies.
We suggest that considering spatial interactions through commuting or travel motivations may offer interesting perspectives on the trade-off between health and economic activity during lockdowns.
COVID-19 大流行迫使各国政府实施封锁政策以遏制疾病传播。这些政策明确鼓励在家工作，从而减少了通勤者的数量，其隐含假设是限制人们的流动会降低旅行者和居住及工作区域其他人的感染风险。然而，在公众话语和对 COVID-19 各种后果的早期描述中，不同地区之间的空间相互关系都很少被提及。
我们的研究提出了一种对 2020 年 3 月至 6 月期间英格兰通勤流量与 COVID-19 死亡率之间关联的空间分析，使用了一系列可公开获得的地区层面数据。为了考虑空间相关性，我们使用了结构移动引力模型来分析地方行政区之间的通勤流量。通过考虑这些空间依赖性，我们缓解了影响简单线性估计的偏差和效率问题。此外，我们还分解了通勤对 COVID-19 死亡率的直接和间接（来自其他地区）影响。
我们的空间回归模型结果表明，较高的通勤流量——总体上特别是通过公共交通——与更高的 COVID-19 死亡率相关。我们的结果与 3 月全国封锁后 COVID 相关死亡率降低的情况一致。空间滞后项在统计上具有显著性，突出了考虑空间依赖性的重要性。
我们建议，通过通勤或旅行动机考虑空间相互作用，可能会为封锁期间健康和经济活动之间的权衡提供有趣的视角。
