Reinfections and Cross-Protection in the 1918/19 Influenza Pandemic: Revisiting a Survey Among Male and Female Factory Workers

Retrospective 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 (incidence, hospitalisations, mortality and sickness absences from work) to retrospectively 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.

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, 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.

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.

The health and demographic impacts of the "Russian flu" pandemic in Switzerland in 1889/1890 and in the years thereafter

Our study aims to enhance future pandemic preparedness by leveraging insights from historical pandemics, focusing on the multidimensional analysis of past outbreaks. In this study, we digitised and analysed for the first time aggregated mortality and morbidity data series from the Russian flu in Switzerland in 1889/1890 and subsequent years to assess its comprehensive impact. The strongest effects were observed in January 1890, showing significant monthly excess mortality from all causes compared to the preceding five years (58.9%, 95% CI 36.6 to 81.0). Even though the whole of Switzerland was affected, the impact varied regionally due to ecological variations. Deaths from other conditions such as tuberculosis and heart disease also increased during this period. A significant drop in birth occurred 9 months later, in the autumn of 1890. Morbidity estimates by physicians suggest that around 60% of the Swiss population fell ill, with regional discrepancies and earlier outbreaks among postal workers (1-2 weeks earlier than the rest of the population). A subsequent spike in all-cause excess and influenza mortality was recorded in January 1894 but more localized than in 1890. Our findings show no cross-protection between the 1890 and 1894 outbreaks.

Role of Vaccination Strategies to Host-Pathogen Dynamics in Social Interactions

This study presents extended Immunity Agent-Based Model (IABM) simulations to evaluate vaccination strategies in controlling the spread of infectious diseases. The application of IABM in the analysis of vaccination configurations is innovative, as a vaccinated individual can be infected depending on how their immune system acts against the invading pathogen, without a pre-established infection rate. Analysis at the microscopic level demonstrates the impact of vaccination on individual immune responses and infection outcomes, providing a more realistic representation of how the humoral response caused by vaccination affects the individual's immune defense. At the macroscopic level, the effects of different population-wide vaccination strategies are explored, including random vaccination, targeted vaccination of specific demographic groups, and spatially focused vaccination. The results indicate that increased vaccination rates are correlated with decreased infection and mortality rates, highlighting the importance of achieving herd immunity. Furthermore, strategies focused on vulnerable populations or densely populated regions prove to be more effective in reducing disease transmission compared to randomly distributed vaccination. The results presented in this work show that vaccination strategies focused on highly crowded regions are more efficient in controlling epidemics and outbreaks. Results suggest that applying vaccination only in the densest region resulted in the suppression of infection in that region, with less intense viral spread in areas with lower population densities. Strategies focused on specific regions, in addition to being more efficient in reducing the number of infected and dead people, reduce costs related to transportation, storage, and distribution of doses compared to the random vaccination strategy. Considering that, despite scientific efforts to consolidate the use of mass vaccination, the accessibility, affordability, and acceptability of vaccines are problems that persist, investing in the study of strategies that mitigate such issues is crucial in the development and application of government policies that make immunization systems more efficient and robust.

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

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.

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

In pandemics, past and present, there is no textbook definition of when a pandemic is over, and how and when exactly a respiratory virus transitions from pandemic to endemic spread. In this paper we have compared the 1918/19 influenza pandemic and the subsequent spread of seasonal flu until 1924. We analysed 14,125 reports of newly stated 32,198 influenza-like illnesses from the Swiss canton of Bern. We analysed the temporal and spatial spread at the level of 497 municipalities, 9 regions, and the entire canton. We calculated incidence rates per 1000 inhabitants of newly registered cases per calendar week. Further, we illustrated the incidences of each municipality for each wave (first wave in summer 1918, second wave in fall/winter 1918/19, the strong later wave in early 1920, as well as the two seasonal waves in 1922 and 1924) on a choropleth map. We performed a spatial hotspot analysis to identify spatial clusters in each wave, using the Gi* statistic. Furthermore, we applied a robust negative binomial regression to estimate the association between selected explanatory variables and incidence on the ecological level. We show that the pandemic transitioned to endemic spread in several waves (including another strong wave in February 1920) with lower incidence and rather local spread until 1924 at least. At the municipality and regional levels, there were different patterns of spread both between pandemic and seasonal waves. In the first pandemic wave in summer 1918 the probability of higher incidence was increased in municipalities with a higher proportion of factories (OR 2.60, 95%CI 1.42-4.96), as well as in municipalities that had access to a railway station (OR 1.50, 95%CI 1.16-1.96). In contrast, the strong fall/winter wave 1918 was very widespread throughout the canton. In general, municipalities at higher altitude showed lower incidence. Our study adds to the sparse literature on incidence in the 1918/19 pandemic and subsequent years. Before Covid-19, the last pandemic that occurred in several waves and then became endemic was the 1918-19 pandemic. Such scenarios from the past can inform pandemic planning and preparedness in future outbreaks.