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.

翻译：公共卫生是近期最受“精准”这一时髦术语诱惑的生物医学领域。“精准公共卫生”的倡导者呼吁采用数据驱动、计算化的公共卫生方法，利用海量基因组“大数据”为公共卫生决策提供信息。然而，如同精准医学一样，精准公共卫生在人群层面上过度渲染了基因组数据对健康结果的预测价值。大量历史文献表明，过度强调遗传因素往往会不成比例地伤害服务不足的少数族裔及弱势群体。通过将精准公共卫生与进步时代（1890-1920年）早期利用大数据和遗传学的尝试进行对比，我们揭示了以基因型为导向的预防性公共卫生的潜在风险。我们最后指出，通过优先整合从分子到社会等多层次分析的数据，或许可以规避此类风险。