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比较德尔塔和奥密克戎变异株对大悉尼(澳大利亚)郊区 COVID-19 严重程度的影响:一项基于大悉尼(澳大利亚)郊区的研究。

Comparing the Impact of Road Networks on COVID-19 Severity between Delta and Omicron Variants: A Study Based on Greater Sydney (Australia) Suburbs.

机构信息

School of Project Management, Faculty of Engineering, The University of Sydney, Forest Lodge, Sydney, NSW 2037, Australia.

出版信息

Int J Environ Res Public Health. 2022 May 27;19(11):6551. doi: 10.3390/ijerph19116551.

Abstract

The Omicron and Delta variants of COVID-19 have recently become the most dominant virus strains worldwide. A recent study on the Delta variant found that a suburban road network provides a reliable proxy for human mobility to explore COVID-19 severity. This study first examines the impact of road networks on COVID-19 severity for the Omicron variant using the infection and road connections data from Greater Sydney, Australia. We then compare the findings of this study with a recent study that used the infection data of the Delta variant for the same region. In analysing the road network, we used four centrality measures (degree, closeness, betweenness and eigenvector) and the coreness measure. We developed two multiple linear regression models for Delta and Omicron variants using the same set of independent and dependent variables. Only eigenvector is a statistically significant predictor for COVID-19 severity for the Omicron variant. On the other hand, both degree and eigenvector are statistically significant predictors for the Delta variant, as found in a recent study considered for comparison. We further found a statistical difference (p < 0.05) between the R-squared values for these two multiple linear regression models. Our findings point to an important difference in the transmission nature of Delta and Omicron variants, which could provide practical insights into understanding their infectious nature and developing appropriate control strategies accordingly.

摘要

新冠病毒的奥密克戎和德尔塔变体最近已成为全球最主要的病毒株。最近一项关于德尔塔变体的研究发现,城市郊区道路网络可以作为人类流动性的可靠替代指标,用以探索新冠病毒的严重程度。本研究首先使用来自澳大利亚大悉尼地区的感染和道路连接数据,检验道路网络对奥密克戎变体的新冠病毒严重程度的影响。然后,我们将本研究的结果与最近一项使用同一地区德尔塔变体感染数据的研究进行了比较。在分析道路网络时,我们使用了四个中心性度量(度、接近度、中间中心度和特征向量)和核心度度量。我们使用相同的一组独立和因变量为德尔塔和奥密克戎变体开发了两个多元线性回归模型。只有特征向量是奥密克戎变体新冠病毒严重程度的一个统计学上显著的预测因子。另一方面,度和特征向量都是德尔塔变体的统计学上显著的预测因子,正如我们考虑的比较研究中所发现的那样。我们还发现这两个多元线性回归模型的 R 平方值之间存在统计学差异(p < 0.05)。我们的研究结果表明,德尔塔和奥密克戎变体的传播性质存在重要差异,这可能为理解它们的传染性和相应地制定适当的控制策略提供实用的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77a0/9180306/08c2e32007a0/ijerph-19-06551-g001.jpg

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