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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.

Background In the presence of non-adherence and lost to follow up, results of an Intention to Treat (ITT) analysis may be biased as it is measuring the effect of assignment rather than the effect of treatment. Given that Marginal Structural Models (MSMs) adjust for such issues, this study examines the use of MSMs to assess the validity of ITT analyses in the presence of non-adherence and lost to follow up in an existing randomized clinical trial on asthma treatment. Methods Inverse probability weights were obtained from a pooled logistic regression assessing the probability of staying on assigned treatment (adherence) and of remaining uncensored (censored) for subjects at each visit by treatment arm. Weights were then pooled into a MSM analysis using a Poisson generalized estimating equation with an independent correlation matrix. Results Out of 488 participants, 174 (36%) did not adhere to the baseline assignment and 85 (17%) were lost to follow up by the end of the study. The adjusted relative risks (RR), and 95% confidence intervals (CI), obtained from the MSMs (theophylline vs. montelukast; RR=1.24; 95% CI: 0.83,1.84; theophylline vs. placebo: RR=1.01; 95% CI: 0.70,1.48; and montelukast vs. placebo: RR=0.83; 95% CI: 0.57,1.19) were nearly identical to that of the ITT analysis (theophylline vs. montelukast: RR=1.22; 95% CI: 0.82,1.86; theophylline vs. placebo: RR=0.99; 95% CI: 0.67,1.50; and montelukast vs. placebo: RR=0.82; 95% CI: 0.55,1.21). Conclusion Concordance between the results of ITT and MSMs indicate adherence and censoring may not invalidate ITT analysis. However, no adherence or censorship thresholds currently exist to assist researchers in determining when MSMs may be superior to ITT in the analysis of clinical trials with non-adherence or censorship issues, and therefore, MSMs should be conducted as a sensitivity analysis to the ITT approach in clinical trials.

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. Published online ahead of print December 8, 2020: 1-8. https://doi.org/10.2105/AJPH.2020.306025).