Racial Disparities in Mortality During the 1918 Influenza Pandemic in United States Cities.

Against a backdrop of extreme racial health inequality, the 1918 influenza pandemic resulted in a striking reduction of non-White to White influenza and pneumonia mortality disparities in United States cities. We provide the most complete account to date of these reduced racial disparities, showing that they were unexpectedly uniform across cities. Linking data from multiple sources, we then examine potential explanations for this finding, including city-level sociodemographic factors such as segregation, implementation of nonpharmaceutical interventions, racial differences in exposure to the milder spring 1918 "herald wave," and racial differences in early-life influenza exposures, resulting in differential immunological vulnerability to the 1918 flu. While we find little evidence for the first three explanations, we offer suggestive evidence that racial variation in childhood exposure to the 1889-1892 influenza pandemic may have shrunk racial disparities in 1918. We also highlight the possibility that differential behavioral responses to the herald wave may have protected non-White urban populations. By providing a comprehensive description and examination of racial inequality in mortality during the 1918 pandemic, we offer a framework for understanding disparities in infectious disease mortality that considers interactions between the natural histories of particular microbial agents and the social histories of those they infect.

The Impact of Data Suppression Rules on Data Access and Re-Identification Risk in Adoption and Foster Care Analysis and Reporting System Annual Files.

One of the most widely used data sources for research on foster care and adoption is the Adoption and Foster Care Analysis and Reporting System (AFCARS). County identifiers in AFCARS are suppressed for all counties with fewer than 1000 cases to prevent the re-identification of vulnerable children, but this also impacts researchers' ability to study smaller communities and analyze how local environments may affect out-of-home placements. This study uses non-public AFCARS datasets to assess, for the first time, how data suppression rules impact data access and re-identification risk. It compares the long-standing 1000-case threshold against a wide range of potential alternatives and finds substantial data access gains coupled with moderate risk increases for thresholds between 400 and 700. Adopting a 700-case threshold leads to a 50% increase in the number of identifiable counties while also keeping the percentage of fostered children who face an elevated risk of re-identification below 1%. Making data from a substantial number of rural counties available to researchers requires much larger threshold changes, which in turn increases re-identification risks.