Integration of Genomic and Epidemiologic Data to Detect Hospital Transmission of Carbapenem-resistant Enterobacteriaceae

Carbapenem-resistant Enterobacteriaceae (CRE) are multi-drug resistant organisms (MDROs) that are resistant to nearly all antibiotics and are estimated to be responsible for 8,500 infections and 1,100 deaths in the U.S. annually. CRE have been labeled an urgent public health threat for over a decade, but despite wide-spread attention, infections with CRE have not decreased. It is established that the burden of CRE is concentrated in healthcare settings where it causes difficult to treat healthcare associated infections (HAIs), however, the burden of CRE is disproportionately distributed in different types of healthcare facilities: acute care hospitals primarily have sporadic cases of CRE, while post-acute care facilities like long-term acute care hospitals (LTACHs) have a disproportionately high prevalence and likely contribute to transmission across regions through transfer of colonized and infected patients. To reduce CRE transmission and prevent at-risk patients we must improve our knowledge of how CRE spreads in hospitals. Detection of CRE transmission, particularly in high-prevalence settings like LTACHs, is complicated by closely related strains that are difficult to distinguish by conventional molecular typing methods, as well as multiple epidemiologically plausible exposures among patients that could have led to transmission. Whole-genome sequencing (WGS) is a method that has demonstrated promise to improve detection of transmission by providing the resolution to distinguish closely related strains, however, there remains a need for studies that realize the potential of WGS to improve infection prevention practices. This dissertation develops and applies combined genomic and epidemiological methods to identify how transmission occurs to the level needed to discern whether additional infection interventions are needed and identify new ways to prevent transmission. Chapter two focuses on specific areas in which genomics has already made a significant impact, including outbreak investigations, regional epidemiology, clinical diagnostics, resistance evolution and the study of epidemic lineages. While highlighting early successes, I also highlight the next steps needed to translate this technology into strategies to improve public health and clinical medicine. Chapter three is a genomic epidemiological investigation of a putative CRE outbreak at the University of Michigan hospital. Our investigation revealed few plausible instances of nosocomial transmission, highlighting instead the frequent importation of CRE into our hospital, thereby informing infection prevention practitioners that additional precautions were unnecessary. Next, I delve into infection prevention improvement in LTACHs. Chapter four tackles detecting patients linked by transmission in a high-prevalence LTACH where patients harbor closely related strains. I present a method based on robust patient sampling and WGS data to detect clusters of patients linked by transmission to patients who imported CRE into the LTACH. Analysis of patient location data in transmission clusters revealed routes of transmission in the facility and highlighted exposures to patients that may increase vulnerability to transmission. Chapter five investigates the practice of cohorting CRE+ patients to prevent spread. Here I find evidence of multiple strain acquisition among CRE+ patients linked to cohorting, highlighting potential patient harms occurring during cohorting, and the importance of staff adherence to infection prevention protocols while caring for cohorted patients. In summary, this dissertation moves forward the field of genomic epidemiology by demonstrating the power of combining WGS data and epidemiological methods to inform infection prevention practices, reveal new insights into routes of transmission, and illuminate new strategies to alleviate the burden of MRDOs.PhDMicrobiology & ImmunologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/155327/1/swhitefi_1.pdfDescription of swhitefi_1.pdf : Restricted to UM users only