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利用优势分析方法识别加拿大新斯科舍省流感样疾病的区域驱动因素。

Identifying the regional drivers of influenza-like illness in Nova Scotia, Canada, with dominance analysis.

机构信息

Saint Mary's University, Halifax, Canada.

Free University of Bolzano, Bolzano, Italy.

出版信息

Sci Rep. 2023 Jun 21;13(1):10114. doi: 10.1038/s41598-023-37184-z.

Abstract

The spread of viral pathogens is inherently a spatial process. While the temporal aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread are still understudied due to a striking absence of theoretical expectations of how spatial dynamics may impact the temporal dynamics of viral populations. Characterizing the spatial transmission and understanding the factors driving it are important for anticipating local timing of disease incidence and for guiding more informed control strategies. Using a unique data set from Nova Scotia, Canada, the objective of this study is to apply a new novel method that recovers a spatial network of the influenza-like viral spread where the regions in their dominance are identified and ranked. We, then, focus on identifying regional predictors of those dominant regions. Our analysis uncovers 18 key regional drivers among 112 regions, each distinguished by unique community-level vulnerability factors such as demographic and economic characteristics. These findings offer valuable insights for implementing targeted public health interventions and allocating resources effectively.

摘要

病毒病原体的传播本质上是一个空间过程。虽然病毒在流行病学层面上的传播的时间方面已经得到了越来越充分的描述,但由于缺乏关于空间动态如何影响病毒群体的时间动态的理论预期,病毒传播的空间方面仍未得到充分研究。描述空间传播并理解驱动因素对于预测疾病发生的局部时间以及指导更明智的控制策略非常重要。本研究利用来自加拿大新斯科舍省的独特数据集,旨在应用一种新的新颖方法来恢复流感样病毒传播的空间网络,其中确定并排名主导区域。然后,我们专注于识别那些主导区域的区域预测因素。我们的分析揭示了 112 个区域中的 18 个关键区域驱动因素,每个区域都有独特的社区层面脆弱性因素,如人口和经济特征。这些发现为实施有针对性的公共卫生干预措施和有效分配资源提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92cf/10284866/693dc6601c7a/41598_2023_37184_Fig1_HTML.jpg

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