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Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India.

ABSTRACT: The factors that drive spatial heterogeneity and diffusion of pandemic influenza remain debated. We characterized the spatiotemporal mortality patterns of the 1918 influenza pandemic in British India and studied the role of demographic factors, environmental variables, and mobility processes on the observed patterns of spread. Fever-related and all-cause excess mortality data across 206 districts in India from January 1916 to December 1920 were analyzed while controlling for variation in seasonality particular to India. Aspects of the 1918 autumn wave in India matched signature features of influenza pandemics, with high disease burden among young adults, (moderate) spatial heterogeneity in burden, and highly synchronized outbreaks across the country deviating from annual seasonality. Importantly, we found population density and rainfall explained the spatial variation in excess mortality, and long-distance travel via railroad was predictive of the observed spatial diffusion of disease. A spatiotemporal analysis of mortality patterns during the 1918 influenza pandemic in India was integrated in this study with data on underlying factors and processes to reveal transmission mechanisms in a large, intensely connected setting with significant climatic variability. The characterization of such heterogeneity during historical pandemics is crucial to prepare for future pandemics.

SUBMITTER: Reyes O

PROVIDER: S-EPMC6269240 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India.

Reyes Olivia O Lee Elizabeth C EC Sah Pratha P Viboud Cécile C Chandra Siddharth S Bansal Shweta S

American journal of epidemiology 20181201 12

The factors that drive spatial heterogeneity and diffusion of pandemic influenza remain debated. We characterized the spatiotemporal mortality patterns of the 1918 influenza pandemic in British India and studied the role of demographic factors, environmental variables, and mobility processes on the observed patterns of spread. Fever-related and all-cause excess mortality data across 206 districts in India from January 1916 to December 1920 were analyzed while controlling for variation in seasona ...[more]

PMID: 30252017

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Project description:BACKGROUND: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden. METHODS: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization. RESULTS: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave. CONCLUSIONS: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

Project description:BACKGROUND:Increasing our knowledge of past influenza pandemic patterns in different regions of the world is crucial to guide preparedness plans against future influenza pandemics. Here, we undertook extensive archival collection efforts from three representative cities of Peru-Lima in the central coast, Iquitos in the northeastern Amazon region, Ica in the southern coast-to characterize the temporal, age and geographic patterns of the 1918-1920 influenza pandemic in this country. MATERIALS AND METHODS:We analyzed historical documents describing the 1918-1920 influenza pandemic in Peru and retrieved individual mortality records from local provincial archives for quantitative analysis. We applied seasonal excess mortality models to daily and monthly respiratory mortality rates for 1917-1920 and quantified transmissibility estimates based on the daily growth rate in respiratory deaths. RESULTS:A total of 52,739 individual mortality records were inspected from local provincial archives. We found evidence for an initial mild pandemic wave during July-September 1918 in Lima, identified a synchronized severe pandemic wave of respiratory mortality in all three locations during November 1918-February 1919, and a severe pandemic wave during January 1920-March 1920 in Lima and July-October 1920 in Ica. There was no recrudescent pandemic wave in 1920 in Iquitos. Remarkably, Lima experienced the brunt of the 1918-1920 excess mortality impact during the 1920 recrudescent wave, with all age groups experiencing an increase in all cause excess mortality from 1918-1919 to 1920. Middle age groups experienced the highest excess mortality impact, relative to baseline levels, in the 1918-1919 and 1920 pandemic waves. Cumulative excess mortality rates for the 1918-1920 pandemic period were higher in Iquitos (2.9%) than Lima (1.6%). The mean reproduction number for Lima was estimated in the range 1.3-1.5. CONCLUSIONS:We identified synchronized pandemic waves of intense excess respiratory mortality during November 1918-February 1919 in Lima, Iquitos, Ica, followed by asynchronous recrudescent waves in 1920. Cumulative data from quantitative studies of the 1918 influenza pandemic in Latin American settings have confirmed the high mortality impact associated with this pandemic. Further historical studies in lesser studied regions of Latin America, Africa, and Asia are warranted for a full understanding of the global impact of the 1918 pandemic virus.

Project description:2018 marks the 100-year anniversary of the 1918 influenza pandemic, which killed ~50 million people worldwide. The severity of this pandemic resulted from a complex interplay between viral, host, and societal factors. Here, we review the viral, genetic and immune factors that contributed to the severity of the 1918 pandemic and discuss the implications for modern pandemic preparedness. We address unresolved questions of why the 1918 influenza H1N1 virus was more virulent than other influenza pandemics and why some people survived the 1918 pandemic and others succumbed to the infection. While current studies suggest that viral factors such as haemagglutinin and polymerase gene segments most likely contributed to a potent, dysregulated pro-inflammatory cytokine storm in victims of the pandemic, a shift in case-fatality for the 1918 pandemic toward young adults was most likely associated with the host's immune status. Lack of pre-existing virus-specific and/or cross-reactive antibodies and cellular immunity in children and young adults likely contributed to the high attack rate and rapid spread of the 1918 H1N1 virus. In contrast, lower mortality rate in in the older (>30 years) adult population points toward the beneficial effects of pre-existing cross-reactive immunity. In addition to the role of humoral and cellular immunity, there is a growing body of evidence to suggest that individual genetic differences, especially involving single-nucleotide polymorphisms (SNPs), contribute to differences in the severity of influenza virus infections. Co-infections with bacterial pathogens, and possibly measles and malaria, co-morbidities, malnutrition or obesity are also known to affect the severity of influenza disease, and likely influenced 1918 H1N1 disease severity and outcomes. Additionally, we also discuss the new challenges, such as changing population demographics, antibiotic resistance and climate change, which we will face in the context of any future influenza virus pandemic. In the last decade there has been a dramatic increase in the number of severe influenza virus strains entering the human population from animal reservoirs (including highly pathogenic H7N9 and H5N1 viruses). An understanding of past influenza virus pandemics and the lessons that we have learnt from them has therefore never been more pertinent.

Dataset Information

Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India.

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Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India.

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