Y Fujikura1, T Hamamoto2, A Kanayama3, K Kaku3, J Yamagishi4, A Kawana5. 1. Department of Medical Risk Management and Infection Control, National Defense Medical College Hospital, Saitama, Japan; Division of Infectious Diseases and Respiratory Medicine, Department of Internal Medicine, National Defense Medical College, Saitama, Japan. Electronic address: fujikura@ndmc.ac.jp. 2. Department of Clinical Laboratory, National Defense Medical College Hospital, Saitama, Japan. 3. Division of Infectious Diseases Epidemiology and Control, National Defense Medical College Research Institute, Saitama, Japan. 4. Research Center for Zoonosis Control, Hokkaido University, Sapporo, Japan. 5. Division of Infectious Diseases and Respiratory Medicine, Department of Internal Medicine, National Defense Medical College, Saitama, Japan.
Abstract
BACKGROUND: Outbreaks of vancomycin-resistant enterococcus (VRE) are a serious problem in hospitals. Inferring the transmission route is an important factor to institute appropriate infection control measures; however, the methodology has not been fully established. AIM: To reconstruct and evaluate the transmission model using sequence variants extracted from whole genome sequencing (WGS) data and epidemiological information from patients involved in a VRE outbreak. METHODS: During a VRE outbreak in our hospital, 23 samples were collected from patients and environmental surfaces and analysed using WGS. By combining genome alignment information with patient epidemiological data, the VRE transmission route was reconstructed using a Bayesian approach. With the transmission model, evaluation and further analyses were performed to identify risk factors that contributed to the outbreak. FINDINGS: All VREs were identified as Enterococcus faecium belonging to sequence type 17, which consisted of two VRE genotypes: vanA (N = 8, including one environmental sample) and vanB (N = 15). The reconstruction model using the Bayesian approach showed the transmission direction with posterior probability and revealed transmission through an environmental surface. In addition, some cases acting as VRE spreaders were identified, which can interfere with appropriate infection control. Vancomycin administration was identified as a significant risk factor for spreaders. CONCLUSION: A Bayesian approach for transmission route reconstruction using epidemiologic data and genomic variants from WGS can be applied in actual VRE outbreaks. This may contribute to the design and implementation of effective infection control measures.
BACKGROUND: Outbreaks of vancomycin-resistant enterococcus (VRE) are a serious problem in hospitals. Inferring the transmission route is an important factor to institute appropriate infection control measures; however, the methodology has not been fully established. AIM: To reconstruct and evaluate the transmission model using sequence variants extracted from whole genome sequencing (WGS) data and epidemiological information from patients involved in a VRE outbreak. METHODS: During a VRE outbreak in our hospital, 23 samples were collected from patients and environmental surfaces and analysed using WGS. By combining genome alignment information with patient epidemiological data, the VRE transmission route was reconstructed using a Bayesian approach. With the transmission model, evaluation and further analyses were performed to identify risk factors that contributed to the outbreak. FINDINGS: All VREs were identified as Enterococcus faecium belonging to sequence type 17, which consisted of two VRE genotypes: vanA (N = 8, including one environmental sample) and vanB (N = 15). The reconstruction model using the Bayesian approach showed the transmission direction with posterior probability and revealed transmission through an environmental surface. In addition, some cases acting as VRE spreaders were identified, which can interfere with appropriate infection control. Vancomycin administration was identified as a significant risk factor for spreaders. CONCLUSION: A Bayesian approach for transmission route reconstruction using epidemiologic data and genomic variants from WGS can be applied in actual VRE outbreaks. This may contribute to the design and implementation of effective infection control measures.
Authors: Thomas M Elliott; Patrick N Harris; Leah W Roberts; Michelle Doidge; Trish Hurst; Krispin Hajkowicz; Brian Forde; David L Paterson; Louisa G Gordon Journal: Antimicrob Steward Healthc Epidemiol Date: 2021-12-13