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:“精密公共卫生”倡导者呼吁对公共卫生采取由数据驱动的计算方法,利用基因组“大数据”的一阵子来为公共卫生决策提供信息。然而,像精密医学一样,PPH将基因组数据的价值过度出售,以决定健康结果,但在人口层面。一大批历史文献表明,过度强调遗传往往对得不到充分服务的少数群体和处境不利社区造成过分的伤害。在进步时代(1890-1920年),我们通过比较和对比PPHPH与早先试图使用大数据和遗传学的对比,强调了基因组“大数据”对公共卫生决策的潜在风险。我们的结论是,通过将数据纳入从分子到社会等许多层面的分析,可以避免这类风险。