Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, California.
Am J Epidemiol. 2019 May 1;188(5):873-882. doi: 10.1093/aje/kwy264.
Much of the intellectual tradition of modern epidemiology stems from efforts to understand and combat chronic diseases persisting through the 20th century epidemiologic transition of countries such as the United States and United Kingdom. After decades of relative obscurity, infectious disease epidemiology has undergone an intellectual rebirth in recent years amid increasing recognition of the threat posed by both new and familiar pathogens. Here, we review the emerging coalescence of infectious disease epidemiology around a core set of study designs and statistical methods bearing little resemblance to the chronic disease epidemiology toolkit. We offer our outlook on challenges and opportunities facing the field, including the integration of novel molecular and digital information sources into disease surveillance, the assimilation of such data into models of pathogen spread, and the increasing contribution of models to public health practice. We next consider emerging paradigms in causal inference for infectious diseases, ranging from approaches to evaluating vaccines and antimicrobial therapies to the task of ascribing clinical syndromes to etiologic microorganisms, an age-old problem transformed by our increasing ability to characterize human-associated microbiota. These areas represent an increasingly important component of epidemiology training programs for future generations of researchers and practitioners.
现代流行病学的大部分知识传统都源于努力理解和应对 20 世纪美国和英国等国家的流行病学转型中持续存在的慢性疾病。传染病流行病学在经历了几十年的相对沉寂之后,近年来随着人们对新出现和熟悉的病原体所构成的威胁的认识不断提高,经历了一场知识上的复兴。在这里,我们回顾了传染病流行病学围绕一组核心研究设计和统计方法的新兴融合,这些方法与慢性病流行病学工具包几乎没有相似之处。我们对该领域面临的挑战和机遇提出了展望,包括将新的分子和数字信息源纳入疾病监测、将此类数据纳入病原体传播模型以及模型对公共卫生实践的贡献不断增加。我们接下来考虑了传染病因果推断方面的新兴范例,从评估疫苗和抗菌疗法的方法到将临床综合征归因于病因微生物的任务,这是一个古老的问题,由于我们越来越有能力描述与人类相关的微生物组而得到了改变。这些领域代表了未来几代研究人员和从业人员的流行病学培训计划中越来越重要的组成部分。