Development of effective strategies to limit the proliferation of multidrug-resistant organisms requires a thorough understanding of how such organisms spread among health care facilities. We sought to uncover the chains of transmission underlying a 2008 U.S. regional outbreak of carbapenem-resistant Klebsiella pneumoniae by performing an integrated analysis of genomic and interfacility patient-transfer data. Genomic analysis yielded a high-resolution transmission network that assigned directionality to regional transmission events and discriminated between intra- and interfacility transmission when epidemiologic data were ambiguous or misleading. Examining the genomic transmission network in the context of interfacility patient transfers (patient-sharing networks) supported the role of patient transfers in driving the outbreak, with genomic analysis revealing that a small subset of patient-transfer events was sufficient to explain regional spread. Further integration of the genomic and patient-sharing networks identified one nursing home as an important bridge facility early in the outbreak—a role that was not apparent from analysis of genomic or patient-transfer data alone. Last, we found that when simulating a real-time regional outbreak, our methodology was able to accurately infer the facility at which patients acquired their infections. This approach has the potential to identify facilities with high rates of intra- or interfacility transmission, data that will be useful for triggering targeted interventions to prevent further spread of multidrug-resistant organisms.

制定有效策略以限制耐多药生物的扩散，需要对这种生物如何在医疗机构中传播的方法有透彻的了解。我们试图揭示2008年美国地区对碳青霉烯耐药的肺炎克雷伯菌的爆发所引起的传播链通过对基因组和设施间患者转移数据进行综合分析。基因组学分析产生了一个高分辨率的传播网络，该网络将流行病学数据含糊不清或误导性的区域性传播事件确定了方向，并区分了设施内传播和设施间传播。在机构间患者转移的背景下检查基因组传播网络（患者共享网络）支持了患者转移在爆发中的作用，而基因组分析表明，一小部分患者转移事件足以解释区域性传播。基因组和患者共享网络的进一步整合确定了一个疗养院是疫情爆发初期的重要桥梁设施-仅从对基因组或患者转移数据的分析中就看不到这一作用。最后，我们发现在模拟实时区域性疫情时，我们的方法能够准确地推断出患者获得感染的设施。这种方法有可能确定设施内或设施间传播率很高的设施，这些数据将有助于触发针对性干预措施，以防止耐多药生物的进一步传播。