Torres Laura Marcela, Johnson Jared, Valentine Audrey, Brezak Audrey, Schneider Emily C, D'Angeli Marisa, Morgan Jennifer, Brostrom-Smith Claire, Hua Chi N, Tran Michael, Lucas Darren, De Leon Joenice Gonzalez, MacKellar Drew, Dykema Philip, Kauber Kelly J, Black Allison
Emerg Infect Dis. 2025 May;31(13):25-34. doi: 10.3201/eid3113.241227.
Mitigating antimicrobial resistance (AMR) is a public health priority to preserve antimicrobial treatment options. The Washington State Department of Health in Washington, USA, piloted a process to leverage longitudinal genomic surveillance on the basis of whole-genome sequencing (WGS) and a genomics-first cluster definition to enhance AMR surveillance. Here, we outline the approach to collaborative surveillance and describe the pilot using 6 carbapenemase-producing organism outbreaks of 3 species: Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae. We also highlight how we applied the approach to an emerging outbreak. We found that genomic and epidemiologic data define highly congruent outbreaks. By layering genomic and epidemiologic data, we refined linkage hypotheses and addressed gaps in traditional epidemiologic surveillance. With the accessibility of WGS, public health agencies must leverage new approaches to modernize surveillance for communicable diseases.
减轻抗菌药物耐药性(AMR)是维护抗菌治疗选择的一项公共卫生优先事项。美国华盛顿州卫生部开展了一个试点项目,该项目基于全基因组测序(WGS)和以基因组学优先的聚类定义来利用纵向基因组监测,以加强AMR监测。在此,我们概述了协作监测方法,并描述了利用3种碳青霉烯酶产生菌爆发事件(分别为铜绿假单胞菌、鲍曼不动杆菌和肺炎克雷伯菌)进行的试点项目。我们还强调了如何将该方法应用于一次新出现的疫情。我们发现基因组数据和流行病学数据确定了高度一致的疫情。通过叠加基因组数据和流行病学数据,我们完善了关联假设并填补了传统流行病学监测中的空白。随着WGS的普及,公共卫生机构必须利用新方法实现传染病监测的现代化。