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

Background: Our 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 methods: We use newly digitized weekly aggregated epidemic/pandemic time series (inci-dence, hospitalisations, mortality and sickness absences from work) to re-model the 1918-1920 pan-demic 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. Results: In 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, ab-sence from work and hospitalisations, but to a lesser extent to increased mortality. In contrast, the sec-ond, 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 as-sociated 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 in-crease of reported cases. Discussion: Our 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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the Foundation for Research in Science and the Humanities at the University of Zurich (Grantee Kaspar Staub, Grant-No. STWF-21-011); University of Geneva & University of Zurich Strategic Partnership Cofunds (call-2020#5, Grantees Kaspar Staub, Olivia Keiser, Frank Ruehli, Antoine Flahault); and the Digitalization Initiative of the Zurich Higher Education Institutions (DIZH, Grant-No 2021.1\_RC\_ID_15, Grantees Kaspar Staub and Wibke Weber). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study reused aggregated (not individual) and published mortality and morbidity data that are over 100 years old. No ethics approval is required for this study in the Canton of Zurich. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced and used are available online at https://zenodo.org/records/7986584