Spatial pattern of all cause excess mortality in Swiss districts during the pandemic years 1890, 1918 and 2020

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Spatial and Spatio-Temporal Epidemiology Pub Date : 2024-11-01 DOI:10.1016/j.sste.2024.100697
Katarina L Matthes , Joël Floris , Aziza Merzouki , Christoph Junker , Rolf Weitkunat , Frank Rühli , Olivia Keiser , Kaspar Staub
{"title":"Spatial pattern of all cause excess mortality in Swiss districts during the pandemic years 1890, 1918 and 2020","authors":"Katarina L Matthes ,&nbsp;Joël Floris ,&nbsp;Aziza Merzouki ,&nbsp;Christoph Junker ,&nbsp;Rolf Weitkunat ,&nbsp;Frank Rühli ,&nbsp;Olivia Keiser ,&nbsp;Kaspar Staub","doi":"10.1016/j.sste.2024.100697","DOIUrl":null,"url":null,"abstract":"<div><div>Every pandemic is embedded in specific spatial and temporal context. However, spatial patterns have almost always only been considered in the context of one individual pandemic. Until now, there has been limited consideration of spatial similarities or differences between pandemics. In this study, Bayesian spatial models for disease mapping were used to estimate excess mortality for the pandemics of 1890, 1918 and 2020. A robust linear regression was used to assess the association between ecological determinants and excess mortality. Spatial variations of excess mortality across Switzerland were observed in each pandemic, but the spatial patterns differ between the pandemics. Different determinants contribute to excess mortality, and these factors vary between COVID-19 and the previous pandemics. Spatial excess mortality from COVID-19 is most likely due to cultural and SEP differences, whereas in historical pandemics, mobility, pre-existing tuberculosis or remote mountain living likely contributed to spatial excess mortality.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"51 ","pages":"Article 100697"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial and Spatio-Temporal Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877584524000649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

Abstract

Every pandemic is embedded in specific spatial and temporal context. However, spatial patterns have almost always only been considered in the context of one individual pandemic. Until now, there has been limited consideration of spatial similarities or differences between pandemics. In this study, Bayesian spatial models for disease mapping were used to estimate excess mortality for the pandemics of 1890, 1918 and 2020. A robust linear regression was used to assess the association between ecological determinants and excess mortality. Spatial variations of excess mortality across Switzerland were observed in each pandemic, but the spatial patterns differ between the pandemics. Different determinants contribute to excess mortality, and these factors vary between COVID-19 and the previous pandemics. Spatial excess mortality from COVID-19 is most likely due to cultural and SEP differences, whereas in historical pandemics, mobility, pre-existing tuberculosis or remote mountain living likely contributed to spatial excess mortality.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
1890 年、1918 年和 2020 年大流行期间瑞士各地区各种原因超额死亡率的空间模式
每一种大流行病都有其特定的时空背景。然而,空间模式几乎总是只在单个大流行的背景下被考虑。到目前为止,对不同大流行之间空间相似性或差异性的考虑还很有限。本研究采用贝叶斯疾病绘图空间模型来估算 1890 年、1918 年和 2020 年大流行的超额死亡率。采用稳健线性回归评估生态决定因素与超额死亡率之间的关联。在每一次大流行中,都观察到瑞士各地超额死亡率的空间变化,但不同大流行的空间模式有所不同。不同的决定因素导致了超额死亡率,而这些因素在 COVID-19 和之前的大流行中各不相同。COVID-19 造成的空间死亡率过高很可能是由于文化和公共教育部的差异造成的,而在以往的大流行中,流动性、原有肺结核或偏远山区生活很可能是造成空间死亡率过高的原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Spatial and Spatio-Temporal Epidemiology
Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
5.10
自引率
8.80%
发文量
63
期刊最新文献
Spatial pattern of all cause excess mortality in Swiss districts during the pandemic years 1890, 1918 and 2020 Multiple “spaces”: Using wildlife surveillance, climatic variables, and spatial statistics to identify and map a climatic niche for endemic plague in California, U.S.A. Investigating interaction effects of social risk factors and exposure to air pollution on pediatric lymphoma cancer in Georgia, United States Road traffic deaths caused by at-fault drivers and drinking-driving in China: A spatiotemporal analysis of the 2017–2020 period Spatio-temporal modeling to identify factors associated with stunting in Indonesia using a Modified Generalized Lasso
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1