Dataset Information

Estimating R ₀ from early exponential growth: parallels between 1918 influenza and 2020 SARS-CoV-2 pandemics.

ABSTRACT: The large spatial scale, geographical overlap, and similarities in transmission mode between the 1918 H1N1 influenza and 2020 SARS-CoV-2 pandemics together provide a novel opportunity to investigate relationships between transmission of two different diseases in the same location. To this end, we use initial exponential growth rates in a Bayesian hierarchical framework to estimate the basic reproductive number, R ₀, of both disease outbreaks in a common set of 43 cities in the United States. By leveraging multiple epidemic time series across a large spatial area, we are able to better characterize the variation in R ₀ across the United States. Additionally, we provide one of the first city-level comparisons of R ₀ between these two pandemics and explore how demography and outbreak timing are related to R ₀. Despite similarities in transmission modes and a common set of locations, R ₀ estimates for COVID-19 were uncorrelated with estimates of pandemic influenza R ₀ in the same cities. Also, the relationships between R ₀ and key population or epidemic traits differed between diseases. For example, epidemics that started later tended to be less severe for COVID-19, while influenza epidemics exhibited an opposite pattern. Our results suggest that despite similarities between diseases, epidemics starting in the same location may differ markedly in their initial progression.

SUBMITTER: Foster G

PROVIDER: S-EPMC9802102 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Estimating R 0 from early exponential growth: parallels between 1918 influenza and 2020 SARS-CoV-2 pandemics.

Foster Grant G Elderd Bret D BD Richards Robert L RL Dallas Tad T

PNAS nexus 20220917 4

The large spatial scale, geographical overlap, and similarities in transmission mode between the 1918 H1N1 influenza and 2020 SARS-CoV-2 pandemics together provide a novel opportunity to investigate relationships between transmission of two different diseases in the same location. To this end, we use initial exponential growth rates in a Bayesian hierarchical framework to estimate the basic reproductive number, R 0, of both disease outbreaks in a common set of 43 cities in the ...[more]

PMID: 36714850

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Project description:During historical and contemporary crises in the U.S., Blacks and other marginalized groups experience an increased risk for adverse health, social, and economic outcomes. These outcomes are driven by structural factors, such as poverty, racial residential segregation, and racial discrimination. These factors affect communities' exposure to risk and ability to recover from disasters, such as pandemics. This study examines whether areas where descendants of enslaved Africans and other Blacks lived in Chicago were vulnerable to excess death during the 1918 influenza pandemic and whether these disparities persisted in the same areas during the COVID-19 pandemic. To examine disparities, demographic data and influenza and pneumonia deaths were digitized from historic weekly paper maps from the week ending on 5 October 1918 to the week ending on 16 November 1918. Census tracts were labeled predominantly Black or white if the population threshold for the group in a census tract was 40% or higher for only one group. Historic neighborhood boundaries were used to aggregate census tract data. The 1918 spatial distribution of influenza and pneumonia mortality rates and cases in Chicago was then compared to the spatial distribution of COVID-19 mortality rates and cases using publicly available datasets. The results show that during the 1918 pandemic, mortality rates in white, immigrant and Black neighborhoods near industrial areas were highest. Pneumonia mortality rates in both Black and immigrant white neighborhoods near industrial areas were approximately double the rates of neighborhoods with predominantly US-born whites. Pneumonia mortality in Black and immigrant white neighborhoods, far away from industrial areas, was also higher (40% more) than in US-born white neighborhoods. Around 100 years later, COVID-19 mortality was high in areas with high concentrations of Blacks based on zip code analysis, even though the proportion of the Black population with COVID was similar or lower than other racial and immigrant groups. These findings highlight the continued cost of racial disparities in American society in the form of avoidable high rates of Black death during pandemics.

Project description:This study compares pandemic experiences of Missouri's 115 counties based on rurality and sociodemographic characteristics during the 1918-20 influenza and 2020-21 COVID-19 pandemics. The state's counties and overall population distribution have remained relatively stable over the last century, which enables identification of long-lasting pandemic attributes. Sociodemographic data available at the county level for both time periods were taken from U.S. census data and used to create clusters of similar counties. Counties were also grouped by rural status (RSU), including fully (100%) rural, semirural (1-49% living in urban areas), and urban (>50% of the population living in urban areas). Deaths from 1918 through 1920 were collated from the Missouri Digital Heritage database and COVID-19 cases and deaths were downloaded from the Missouri COVID-19 dashboard. Results from sociodemographic analyses indicate that, during both time periods, average farm value, proportion White, and literacy were the most important determinants of sociodemographic clusters. Furthermore, the Urban/Central and Southeastern regions experienced higher mortality during both pandemics than did the North and South. Analyses comparing county groups by rurality indicated that throughout the 1918-20 influenza pandemic, urban counties had the highest and rural had the lowest mortality rates. Early in the 2020-21 COVID-19 pandemic, urban counties saw the most extensive epidemic spread and highest mortality, but as the epidemic progressed, cumulative mortality became highest in semirural counties. Additional results highlight the greater effects both pandemics had on county groups with lower rates of education and a lower proportion of Whites in the population. This was especially true for the far southeastern counties of Missouri ("the Bootheel") during the COVID-19 pandemic. These results indicate that rural-urban and socioeconomic differences in health outcomes are long-standing problems that continue to be of significant importance, even though the overall quality of health care is substantially better in the 21st century.

Dataset Information

Estimating R ₀ from early exponential growth: parallels between 1918 influenza and 2020 SARS-CoV-2 pandemics.

Publications

Estimating <i>R</i> <sub>0</sub> from early exponential growth: parallels between 1918 influenza and 2020 SARS-CoV-2 pandemics.

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