Integrated genomic and interfacility patient-transfer data reveal the transmission pathways of multidrug-resistant Klebsiella pneumoniae in a regional outbreak

• Published in: Science translational medicine 2017-11, Vol.9 (417)
• Main Authors: Snitkin, Evan S, Won, Sarah, Pirani, Ali, Lapp, Zena, Weinstein, Robert A, Lolans, Karen, Hayden, Mary K
• Format: Article
• Language: English
• Subjects: Anti-Bacterial Agents - pharmacology; Bacterial Proteins - genetics; Bacterial Proteins - metabolism; Disease Outbreaks; Drug Resistance, Multiple, Bacterial - genetics; Genome, Bacterial - genetics; Humans; Klebsiella Infections - microbiology; Klebsiella pneumoniae - drug effects; Klebsiella pneumoniae - genetics; Microbial Sensitivity Tests
• ISSN: 1946-6234; 1946-6242
• DOI: 10.1126/scitranslmed.aan0093

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 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.