Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Am J Epidemiol. 2019 Aug 1;188(8):1410-1419. doi: 10.1093/aje/kwz064.
In the last third of the 20th century, etiological epidemiology within academia in high-income countries shifted its primary concern from attempting to tackle the apparent epidemic of noncommunicable diseases to an increasing focus on developing statistical and causal inference methodologies. This move was mutually constitutive with the failure of applied epidemiology to make major progress, with many of the advances in understanding the causes of noncommunicable diseases coming from outside the discipline, while ironically revealing the infectious origins of several major conditions. Conversely, there were many examples of epidemiologic studies promoting ineffective interventions and little evident attempt to account for such failure. Major advances in concrete understanding of disease etiology have been driven by a willingness to learn about and incorporate into epidemiology developments in biology and cognate data science disciplines. If fundamental epidemiologic principles regarding the rooting of disease risk within populations are retained, recent methodological developments combined with increased biological understanding and data sciences capability should herald a fruitful post-Modern Epidemiology world.
在 20 世纪的最后三分之一时间里，高收入国家学术界的病因流行病学将其主要关注点从试图解决明显的非传染性疾病流行转移到越来越关注发展统计和因果推理方法上。这种转变与应用流行病学未能取得重大进展是相互构成的，许多对非传染性疾病原因的理解进展来自该学科之外，而具有讽刺意味的是，这揭示了几种主要疾病的传染性起源。相反，有许多流行病学研究促进了无效干预的例子，而很少有明显的尝试来解释这种失败。对疾病病因学的具体理解的重大进展是由于愿意了解和将生物学和相关数据科学学科的发展纳入流行病学。如果保留关于疾病风险在人群中根源的基本流行病学原则，那么最近的方法发展结合了对生物和数据科学能力的增强，应该预示着一个富有成效的后现代流行病学世界的到来。
