The ‘Spanish’ #influenza #pandemic: new #evidence for influenza #outbreaks in #England and #France prior to 1918

 

Abstract

The Spanish influenza pandemic of 1918 caused well over fifty million deaths. The epicentre undoubtedly was China, where gene mixing of different virus strains occurred amongst aquatic, migrant birds. But where and when did the virus first infect (or spill over to) a human being? We take, as our starting point, a paper demonstrating that an infection causing the same symptoms as the influenza virus was widespread in New York during the winter of 1917–1918. The authors of that paper went on to suggest that the virus had probably reached North America from Europe, in the context of troop movement during World War I. Our own researches have focussed on this point. We show that outbreaks of serious respiratory disease, local in nature but causing unusual patterns of mortality, were indeed reported by scientists and doctors in army hospitals in England and in France, well before the first wave of the pandemic had arrived. We use the records of these hospitals, now held in the National Archives, to trace the progress of this disease amongst the individuals who fell ill. We examine contemporary reactions to this minor epidemic – an epidemic, we suggest, which acted as a herald wave of the pandemic yet to come. The latter part of our paper addresses the second question, as to how troop movement across the North Atlantic, once the United States had entered into war, may well have enabled the virus to spread from Europe to North America.

Source: 

Link: https://www.cambridge.org/core/journals/medical-history/article/spanish-influenza-pandemic-new-evidence-for-influenza-outbreaks-in-england-and-france-prior-to-1918/8BC01CCE54683ED7A4DD1DFF0C3AE7EA

____

An ancient #influenza #genome from #Switzerland allows deeper #insights into host #adaptation during the 1918 flu #pandemic in #Europe

Abstract

Background

From 1918 to 1920, the largest influenza A virus (IAV) pandemic known to date spread globally causing between 20 to 100 million deaths. Historical records have captured critical aspects of the disease dynamics, such as the occurrence and severity of the pandemic waves. Yet, other important pieces of information such as the mutations that allowed the virus to adapt to its new host can only be obtained from IAV genomes. The analysis of specimens collected during the pandemic and still preserved in historical pathology collections can significantly contribute to a better understanding of its course. However, efficient RNA processing protocols are required to work with such specimens.

Results

Here, we describe an alternative protocol for efficient ancient RNA sequencing and evaluate its performance on historical samples, including a published positive control. The phenol/chloroform-free protocol efficiently recovers ancient viral RNA, especially small fragments, and maintains information about RNA fragment directionality through incorporating fragments by a ligation-based approach. One of the assessed historical samples allowed for the recovery of the first 1918 IAV genome from Switzerland. This genome, derived from a patient deceased during the beginning of the first pandemic wave in Switzerland, already harbours mutations linked to human adaptation.

Conclusion

We introduce an alternative, efficient workflow for ancient RNA recovery from formalin-fixed wet specimens. We also present the first precisely dated and complete influenza genome from Europe, highlighting the early occurrence of mutations associated with adaptation to humans during the first European wave of the 1918 pandemic.

Source: BMC Biology, https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-025-02282-z

____

Role of Nonpharmaceutical #Interventions during 1918–1920 #Influenza #Pandemic, #Alaska, #USA

Abstract

Previous studies investigating the 1918–1920 influenza pandemic have provided a comprehensive overview of the spread of the pandemic and possible explanations for high mortality rates in Alaska, USA. Our understanding of the role of nonpharmaceutical interventions (NPIs) is limited, however. To gain an overview of various agencies’ efforts to protect communities during the pandemic, we conducted a mixed-method assessment of a large pool of digitized historical newspapers and archival materials covering Alaska’s local and territorial responses to the pandemic. The study encompassed 14 local units of Alaska that implemented NPIs during October 1918–January 1919. Analyses indicated that 8 local units avoided the outbreak by implementing NPIs and that the other 6 units controlled the spread of influenza by implementing NPIs after the virus was introduced. In addition, some Indigenous communities escaped the pandemic by implementing mandatory and voluntary restrictions. Information on NPI effects of could guide future influenza pandemic preparedness and response.

Source: US Centers for Disease Control and Prevention, https://wwwnc.cdc.gov/eid/article/31/7/24-1048_article

____

Did #horses act as intermediate #hosts that facilitated the emergence of 1918 #pandemic #influenza?

Abstract

The ecological factors that led to the 1918 influenza pandemic remain unknown. We hypothesise that horses acted as intermediate hosts spreading a pre-pandemic avian-origin virus before 1918. This is supported by reports describing a large epizootic of unusually severe equine influenza beginning in 1915. Furthermore, the high horse demand during WWI resulted in one of the biggest equine mobilisations in North America between 1914 and 1918. This extensive movement of horses provided abundant opportunities for virus reassortment between pre-pandemic avian and human influenza viruses. Archived equine tissues or serum samples will be needed to test this hypothesis.

Source: Journal of Infectious Diseases, https://academic.oup.com/jid/advance-article-abstract/doi/10.1093/infdis/jiaf197/8115353?redirectedFrom=fulltext&login=false

____

Retrospective #modelling of the #disease and #mortality burden of the 1918–1920 #influenza #pandemic in #Zurich, #Switzerland

Abstract

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.

Source: Epidemics, https://www.sciencedirect.com/science/article/pii/S1755436525000015?via%3Dihub

_____