Why Does Influenza Hit the Poor More Than the Rich? A 1931 Social Epidemiology Article That Broke New Ground in the History of Confounding, Mediation, and Interaction.

In 1931, Edgar Sydenstricker, the former statistician of the US Public Health Service, challenged the common belief that the 1918 influenza outbreak had affected "the rich and the poor alike." Using data from 112,317 participants in a 1918 US national survey, he observed that, on the contrary, both morbidity and mortality from the flu had been higher among the poor than among the rich. To explain these differences, Sydenstricker stratified the analyses by 2 measures of affluence collected in the survey: "economic status" (from "very poor" to "well-to-do") and household crowding (i.e., number of people per household room). Economic status was associated with influenza attack rates within categories of crowding, but not the opposite, suggesting that characteristics of poverty other than "household congestion" were the culprit of the poor's higher influenza burden. Attack rate ratios for influenza in infants and older adults were greater for the poor or very poor. Sydenstricker reanalyzed an already 12-year-old data set in the context of the Great Depression to build the evidence base relating poverty to ill health. For this purpose he used a stratification approach to assess confounding, mediation, and interaction before the concepts were formally named.

The US Public Health Service House-to-House Canvass Survey of the Morbidity and Mortality of the 1918 Influenza Pandemic.

Between November 20, 1918, and March 12, 1919, the US Public Health Service carried out a vast population-based survey to assess the incidence rate and mortality of the influenza pandemic among 146 203 persons in 18 localities across the United States. The survey attempted to retrospectively assess all self-reported or diagnosed cases of influenza since August 1, 1918. It indicated that the cumulative incidence of symptomatic influenza over 6 months had been 29.4% (range = 15% in Louisville, KY, to 53.3% in San Antonio, TX). The overall case fatality rate (CFR) was 1.70%, and it ranged from 0.78% in San Antonio to 3.14% in New London, Connecticut. Localities with high cumulative incidence were not necessarily those with high CFR. Overall, assuming the survey missed asymptomatic cases, between August 1, 1918, and February 21, 1919, maybe more than 50% of the population was infected, and about 1% of the infected died. Eight months into the COVID-19 pandemic, the United States has not yet launched a survey that would provide population-based estimates of incidence and CFRs analogous to those generated by the 1918 US Public Health Service house-to-house canvass survey of influenza.

A Diverse and Inclusive Academic Membership for All.

With the growing recognition that diversity and inclusion are essential for the improvement of science and innovation, we provide some perspectives on 3 findings of DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998-1010). We provide points of discussion on factors and strategies to consider when drafting diversity and inclusion programs for the Society for Epidemiologic Research.

Perspectives on the Future of Epidemiology: A Framework for Training.

Over the past century, the field of epidemiology has evolved and adapted to changing public health needs. Challenges include newly emerging public health concerns across broad and diverse content areas, new methods, and vast data sources. We recognize the need to engage and educate the next generation of epidemiologists and prepare them to tackle these issues of the 21st century. In this commentary, we suggest a skeleton framework upon which departments of epidemiology should build their curriculum. We propose domains that include applied epidemiology, biological and social determinants of health, communication, creativity and ability to collaborate and lead, statistical methods, and study design. We believe all students should gain skills across these domains to tackle the challenges posed to us. The aim is to train smart thinkers, not technicians, to embrace challenges and move the expanding field of epidemiology forward.