From pandemic to endemic: Spatial-temporal patterns of influenza-like illness incidence in a Swiss canton, 1918–1924

Bernhard, Marco; Leuch, Corina; Kordi, Maryam; Gruebner, Oliver; Matthes, Katarina L.; Floris, Joël; Staub, Kaspar

doi:10.1016/j.ehb.2023.101271

Cited by 5 publications

(9 citation statements)

References 66 publications

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“…On the other hand, the summer wave was also stronger west of the Central Plateau, which could be another reason. In Bern, the small wave in the spring of 1919 was much more pronounced than in Zurich, but the later wave at the beginning of 1920 was equally strong in both Bern and Zurich 27 . Reproduction numbers were already estimated almost 20 years ago for the canton of Geneva, where a higher reproduction number (3.8) was estimated for the second wave than for the first wave (1.5) in 1918 25,26,43 .…”

Section: Discussionmentioning

confidence: 86%

“…Therefore, the 1918 influenza pandemic is considered the greatest demographic catastrophe of the 20th century in Switzerland 19,20 . Recent research on Switzerland can be divided into a) national descriptions based on mortality figures 19,20 , b) qualitative reconstructions of the epidemic in selected member states (cantons) 19,[21][22][23][24] , and c) a growing number of quantitative studies modelling the pandemic based on hospitalisation data in Geneva 25,26 and incidence data from Bern 27,28 .…”

Section: Introductionmentioning

confidence: 99%

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(Re-)modelling of the disease and mortality burden of the 1918-1920 influenza pandemic in Zurich, Switzerland

Ziegler,

Matthes,

Middelkamp

et al. 2024

Preprint

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BackgroundOur study aims to enhance future pandemic preparedness by integrating lessons from historical pandemics, focusing on the multidimensional analysis of past outbreaks. It addresses the gap in existing modelling studies by combining various pandemic parameters in a comprehensive setting. Using Zurich as a case study, we seek a deeper understanding of pandemic dynamics to inform future scenarios.Data and methodsWe use newly digitized weekly aggregated epidemic/pandemic time series (incidence, hospitalisations, mortality and sickness absences from work) to re-model the 1918-1920 pandemic in Zurich and investigate how different parameters correspond, how transmissibility changed during the different waves, and how public health interventions were associated with changes in these pandemic parameters.ResultsIn general, the various time series show a good temporal correspondence, but differences in their expression can also be observed. The first wave in the summer of 1918 did lead to illness, absence from work and hospitalisations, but to a lesser extent to increased mortality. In contrast, the second, longest and strongest wave in the autumn/winter of 1918 also led to greatly increased (excess) mortality in addition to the burden of illness. The later wave in the first months of 1920 was again associated with an increase in all pandemic parameters. Furthermore, we can see that public health measures such as bans on gatherings and school closures were associated with a decrease in the course of the pandemic, while the lifting or non-compliance with these measures was associated with an increase of reported cases.DiscussionOur study emphasizes the need to analyse a pandemic’s disease burden comprehensively, beyond mortality. It highlights the importance of considering incidence, hospitalizations, and work absences as distinct but related aspects of disease impact. This approach reveals the nuanced dynamics of a pandemic, especially crucial during multi-wave outbreaks.

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Section: Discussionmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

(Re-)modelling of the disease and mortality burden of the 1918-1920 influenza pandemic in Zurich, Switzerland

Ziegler,

Matthes,

Middelkamp

et al. 2024

Preprint

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“…Although deaths were highest in this pandemic, especially among young adults, the majority of those who fell ill survived. Switzerland was hit by a total of four waves between the summer of 1918 and the spring of 1920, before the virus adopted a seasonal pattern [ 43 , 44 ]. At least two-thirds of the Swiss population have fallen ill, in some cases several times, with reinfections often at least as severe as the initial illness [ 45 ].…”

Section: Resultsmentioning

confidence: 99%

An Unwanted but Long-Known Company: Post-Viral Symptoms in the Context of Past Pandemics in Switzerland (and Beyond)

Staub,

Ballouz,

Puhan

2024

Public Health Rev

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Objectives: Some people do not fully recover from an acute viral infection and experience persistent symptoms or incomplete recovery for months or even years. This is not unique to the SARS-CoV-2 virus and history shows that post-viral conditions like post COVID-19 condition, also referred to as Long Covid, are not new. In particular, during and after pandemics caused by respiratory viruses in which large parts of the population were infected or exposed, professional and public attention was increased, not least because of the large number of people affected.Methods: Given the current relevance of the topic, this article aims to narratively review and summarize the literature on post-viral symptoms during past pandemics and to supplement and illustrate it with Swiss examples from the pandemics of 1890, 1918–1920 and later.Results: Post-viral diseases were an increasingly emphasised health topic during and after past pandemics triggered by respiratory infections over the last 150 years.Conclusion: In the next pandemic, it should not be surprising that post-viral conditions will again play a role, and pandemic plans should reflect this.

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“…This could confirm the hypothesis that in historical pandemics, cities with a higher mobility were the first to be affected. In addition, a higher proportion of industry occupational sector leads also to a higher incidence rate 5 . Unfortunately, we did not have information about the number of factories for each district in Switzerland, in this study.…”

Section: Discussionmentioning

confidence: 99%

“…Rather, by contrasting and comparing past pandemics, the aim is to highlight the specificities of each pandemic and to offer the possibility of approaching current problems differently. Two studies from Switzerland have analyzed in detail the spatial spread of the "Spanish flu" 5 and related public health interventions 6 at the regional level (Canton of Bern), and have also made some comparison with the public health intervention during COVID-19.…”

Section: Introductionmentioning

confidence: 99%

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

Matthes,

Floris,

Merzouki

et al. 2024

Preprint

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Background: 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. Objective: The aim of this study was to examine spatial pattern of excess mortality in Swiss districts during the pandemic years 1890, 1918 and 2020. In addition, determinants that could explain the difference between districts were analyzed. Methods: Excess mortality rate was estimated using a Bayesian spatial model for disease mapping. A robust linear regression was used to assess the association between ecological determinants and excess mortality. Results: The highest excess mortality rate in all districts occurred during the 1918 pandemic, the lowest excess mortality rate was seen for the 1890 pandemic. Moreover, this analysis revealed heterogeneous spatial patterns of excess mortality in each pandemic year. Different socio-demographic determinants, in each pandemic, might have favored excess mortality. While the age composition, cultural and area-based socio-economic position differences and the proximity to France and Italy were the main determinants of excess mortality during the Covid-19 pandemic, the mobility, preexisting health issues (i.e. TB) or the remoteness location in the mountains played crucial roles during the historical pandemics. Contribution: The analysis of spatial patterns in pandemics is important for public health interventions in future pandemics or outbreaks since it helps to identifying patterns of transmission. Identifying and understanding geographic hotspots informs precise interventions, aids in public health implementation, and contributes to tailored health policies for the region.

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From pandemic to endemic: Spatial-temporal patterns of influenza-like illness incidence in a Swiss canton, 1918–1924

Cited by 5 publications

References 66 publications

(Re-)modelling of the disease and mortality burden of the 1918-1920 influenza pandemic in Zurich, Switzerland

(Re-)modelling of the disease and mortality burden of the 1918-1920 influenza pandemic in Zurich, Switzerland

An Unwanted but Long-Known Company: Post-Viral Symptoms in the Context of Past Pandemics in Switzerland (and Beyond)

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

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