tetano
Editor, Senior Moderator
Spat Spatiotemporal Epidemiol
. 2024 Nov:51:100697.
doi: 10.1016/j.sste.2024.100697. Epub 2024 Oct 24. Spatial pattern of all cause excess mortality in Swiss districts during the pandemic years 1890, 1918 and 2020
Katarina L Matthes[SUP] 1 [/SUP], Joël Floris[SUP] 2 [/SUP], Aziza Merzouki[SUP] 3 [/SUP], Christoph Junker[SUP] 4 [/SUP], Rolf Weitkunat[SUP] 4 [/SUP], Frank Rühli[SUP] 5 [/SUP], Olivia Keiser[SUP] 6 [/SUP], Kaspar Staub[SUP] 5 [/SUP]
Affiliations
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.
Keywords: Bayesian modeling; COVID-19; Disease mapping; Pandemic 1890; Pandemic 1918; Spatial analysis.
. 2024 Nov:51:100697.
doi: 10.1016/j.sste.2024.100697. Epub 2024 Oct 24. Spatial pattern of all cause excess mortality in Swiss districts during the pandemic years 1890, 1918 and 2020
Katarina L Matthes[SUP] 1 [/SUP], Joël Floris[SUP] 2 [/SUP], Aziza Merzouki[SUP] 3 [/SUP], Christoph Junker[SUP] 4 [/SUP], Rolf Weitkunat[SUP] 4 [/SUP], Frank Rühli[SUP] 5 [/SUP], Olivia Keiser[SUP] 6 [/SUP], Kaspar Staub[SUP] 5 [/SUP]
Affiliations
- PMID: 39615976
- DOI: 10.1016/j.sste.2024.100697
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.
Keywords: Bayesian modeling; COVID-19; Disease mapping; Pandemic 1890; Pandemic 1918; Spatial analysis.