Identifying more epidemic clones during a hospital outbreak of multidrug-resistant Acinetobacter baumannii
Matthieu Domenech de Cellès1, Jérôme Salomon, Anne Marinier
1Unité de Pharmacoépidémiologie et Maladies Infectieuses, Institut Pasteur, Paris, France. domenech@pasteur.fr
Abstract:
Infections caused by multidrug-resistant bacteria are a major concern in hospitals. Current infection-control practices legitimately focus on hygiene and appropriate use of antibiotics. However, little is known about the intrinsic abilities of some bacterial strains to cause outbreaks. They can be measured at a population level by the pathogen's transmission rate, i.e. the rate at which the pathogen is transmitted from colonized hosts to susceptible hosts, or its reproduction number, counting the number of secondary cases per infected/colonized host. We collected data covering a 20-month surveillance period for carriage of multidrug-resistant Acinetobacter baumannii (MDRAB) in a surgery ward. All isolates were subjected to molecular fingerprinting, and a cluster analysis of profiles was performed to identify clonal groups. We then applied stochastic transmission models to infer transmission rates of MDRAB and each MDRAB clone. Molecular fingerprinting indicated that 3 clonal complexes spread in the ward. A first model, not accounting for different clones, quantified the level of in-ward cross-transmission, with an estimated transmission rate of 0.03/day (95% credible interval [0.012-0.049]) and a single-admission reproduction number of 0.61 [0.30-1.02]. The second model, accounting for different clones, suggested an enhanced transmissibility of clone 3 (transmission rate 0.047/day [0.018-0.091], with a single-admission reproduction number of 0.81 [0.30-1.56]). Clones 1 and 2 had comparable transmission rates (respectively, 0.016 [0.001-0.045], 0.014 [0.001-0.045]). The method used is broadly applicable to other nosocomial pathogens, as long as surveillance data and genotyping information are available. Building on these results, more epidemic clones could be identified, and could lead to follow-up studies dissecting the functional basis for variation in transmissibility of MDRAB lineages.
Insights
Multidrug-resistant Acinetobacter baumannii (MDRAB) outbreaks in hospitals are concerning. This study quantified MDRAB transmission rates, finding one clone (clone 3) was significantly more transmissible, highlighting the need to identify epidemic clones for better control.
Area of Science:
- Infectious Diseases
- Epidemiology
- Microbiology
Background:
- Multidrug-resistant bacteria (MDRB) pose a significant threat in healthcare settings.
- Understanding bacterial intrinsic abilities to cause outbreaks, measured by transmission rates and reproduction numbers, is crucial for infection control.
- Current practices focus on hygiene and antibiotic stewardship, but pathogen-specific transmission dynamics require further investigation.
Purpose of the Study:
- To quantify the transmission rates of multidrug-resistant Acinetobacter baumannii (MDRAB) and its specific clones within a hospital surgery ward.
- To identify if certain MDRAB clones possess enhanced transmissibility.
- To demonstrate a broadly applicable method for inferring transmission dynamics of nosocomial pathogens.
Main Methods:
- Collected 20-month surveillance data for MDRAB carriage in a surgery ward.
- Utilized molecular fingerprinting (e.g., PFGE) and cluster analysis to identify MDRAB clonal groups.
- Applied stochastic transmission models to estimate transmission rates and reproduction numbers for MDRAB and its clones.
Main Results:
- Identified three main clonal complexes of MDRAB circulating in the ward.
- Estimated an overall MDRAB transmission rate of 0.03/day and a reproduction number of 0.61.
- Revealed significantly enhanced transmissibility for clone 3 (transmission rate 0.047/day, reproduction number 0.81), while clones 1 and 2 showed lower, comparable rates.
Conclusions:
- Specific MDRAB clones exhibit varying transmissibility, with clone 3 being a potential driver of outbreaks.
- The applied modeling approach effectively quantifies transmission dynamics and can identify hyper-virulent clones.
- This methodology is adaptable for surveillance and control of other nosocomial pathogens, aiding in targeted infection prevention strategies.

