  Public health is the most recent of the biomedical sciences to be seduced by
the trendy moniker "precision." Advocates for "precision public health" (PPH)
call for a data-driven, computational approach to public health, leveraging
swaths of genomic "big data" to inform public health decision-making. Yet, like
precision medicine, PPH oversells the value of genomic data to determine health
outcomes, but on a population-level. A large historical literature has shown
that over-emphasizing heredity tends to disproportionately harm underserved
minorities and disadvantaged communities. By comparing and contrasting PPH with
an earlier attempt at using big data and genetics, in the Progressive era
(1890-1920), we highlight some potential risks of a genotype-driven preventive
public health. We conclude by suggesting that such risks may be avoided by
prioritizing data integration across many levels of analysis, from the
molecular to the social.
