Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918

Abstract

Social factors have been shown to create differential burden of influenza across different geographic areas. We explored the relationship between potential aggregate-level social determinants and mortality during the 1918 influenza pandemic in Chicago using a historical dataset of 7,971 influenza and pneumonia deaths. Census tract-level social factors, including rates of illiteracy, homeownership, population, and unemployment, were assessed as predictors of pandemic mortality in Chicago. Poisson models fit with generalized estimating equations (GEEs) were used to estimate the association between social factors and the risk of influenza and pneumonia mortality. The Poisson model showed that influenza and pneumonia mortality increased, on average, by 32.2% for every 10% increase in illiteracy rate adjusted for population density, homeownership, unemployment, and age. We also found a significant association between transmissibility and population density, illiteracy, and unemployment but not homeownership. Lastly, analysis of the point locations of reported influenza and pneumonia deaths revealed fine-scale spatiotemporal clustering. This study shows that living in census tracts with higher illiteracy rates increased the risk of influenza and pneumonia mortality during the 1918 influenza pandemic in Chicago. Our observation that disparities in structural determinants of neighborhood-level health lead to disparities in influenza incidence in this pandemic suggests that disparities and their determinants should remain targets of research and control in future pandemics.

Pandemic influenza and socioeconomic disparities: Lessons from 1918 Chicago

“…In another study, latitude, population density, and the proportion of children explained about 40% of between-province variation in cumulative excess death rates in Spain (11). Very little, however, has been done to understand the drivers of pandemic-related mortality rates at the fine scale of households or census tracts, an issue tackled by Grantz et al (6).…”

“…2-5). In PNAS, Grantz et al (6) contribute to the growing interest in applying modern analytical tools to epidemiological archives, through the lens of socioeconomic disparities affecting the 1918 influenza pandemic.…”

“…Grantz et al (6) painstakingly pieced together historical maps of pneumonia and influenza deaths reported during the lethal wave of the pandemic in Chicago in October-November 1918, together with archival census tract data, to analyze the relationship between pandemic mortality and sociodemographic variables (including illiteracy rate, homeownership, unemployment, population density, and age). Pneumonia and influenza mortality rates were found to increase on average by 32% for every 10% increase in illiteracy rates, after controlling for other sociodemographic variables that had a lesser effect.…”

“…1) (3, 5, 13). Whether the relationship between illiteracy and influenza-related mortality evidenced by Grantz et al (6) holds across age groups whose experience with the 1918 pandemic virus differed profoundly remains a crucial question. The authors note the role of population size over 45 y of age as a predictor of mortality rates in multivariate analyses, and the potential for residual confounding between the demographic and socioeconomic structure of Chicago's neighborhoods at the time.…”

Reply to Alonso et al. “Bangladesh and Rwanda: Cases of high burden of influenza in tropical countries?”

“…Additionally, the population density of Bangladesh is among the highest in the world (1252 people per square kilometer in Bangladesh) and Rwanda has the second highest population density in Africa (440 people per square kilometer) compared with Brazil, which has one of the lowest population densities among all countries of the world (25 people per square kilometer) 17. Population density may influence influenza virus transmission dynamics and burden of influenza virus infections 18. Given the important differences in public health systems, and sociodemographic factors between Brazil, Bangladesh, and Rwanda, disparities in the influenza virus disease burden in these countries are entirely possible.…”