Small Interactions and Big Consequences: Transmission of ESBLs


A new study looks at ESBL transmission and close proximity interactions.

How large of a role does human contact play in the spread of multidrug-resistant organisms? Moreover, do close-proximity interactions increase the chance for nosocomial transmission of such infections? These very questions inspired French investigators to study interactions and transmission of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae, including Escherichia coli (ESBL-EC) and Klebsiella pneumoniae (ESBL-KP).

Armed with the power of technology and laboratory capacity, the research team was able to truly study the role of close-proximity interactions (CPI) within a health care environment and how these interactions play into the transmission of ESBL-KP and ESBL-EC. Investigators used data collected from i-Bird (Individual-Based Investigation of Resistance Dissemination) from a 200-bed long-term care facility over the course of 4 months. CPIs between staff and patients were recorded every 30 seconds through wireless sensors (ie, RFID tags). Since CPIs are considered to be a prime source for transmission of microorganisms, tracking interactions via wireless sensors allowed the researchers to truly understand the volume between staff and patients, but also then track the transmission of ESBL- producing organisms.

Since the World Health Organization (WHO) reports that E coli is the most common pathogen detected in health care-associated infections (HAIs) and it, along with K pneumoniae, are considered to be responsible for 20% of HAIs in the United States and 50% of HAI urinary tract infections, it’s not surprising that these organisms were studied for CPIs. In addition to tracking CPIs via wireless sensors, the investigators also initiated testing patients for Enterobacteriaceae via weekly rectal swabs.

Among the 329 patients included in the i-Bird study, the investigators found that “the weekly average carriage prevalence of ESBL-producing Enterobacteriaceae was 16.8%. The predominant species were E coli and K pneumoniae, with on average 11.5% of patients colonized weekly by an ESBL-EC, and 3.7% by an ESBL-KP.”

To test CPIs as a potential source for transmission, the investigators “tested whether observed distances along the CPI-network between a case and their closest potential infectors were comparable to distances expected under the null hypothesis of independence between CPIs and carriage data. Expected distances were computed as the average of distances obtained from 200 simulations using randomly permutated carriage data.”

The data demonstrate that 90% of the ESBL-KP transmission to new patients was a result of direct or indirect contact with patients who had tested positive for the microorganism within the previous 2 months. Interestingly, when investigators looked at ESBL-EC, the transmission rate was only 60%. Ultimately, the research team found that by integrating technology and microbiology, we can start to understand the role of these small interactions that might seem fleeting in the moment but can have serious consequences.

As investigator Audrey Duval, PhD student, noted: “By combining digital epidemiology and rapid microbiological diagnostic tools, we may be entering a new era to understand and control the risk of hospital-acquired infection with multidrug-resistant bacteria.”

From the infection prevention perspective, this study gives us proof of what many have suspected for a long time—CPIs can lead to transmission of pathogens through both direct and indirect exposures. Understanding how these occur and where we can incorporate infection prevention efforts to disrupt the chain of transmission is critical to halt HAIs. Hand hygiene and environmental disinfection are all ways we can disrupt this chain of transmission with multidrug-resistant organisms in the health care environment, and this study allows us to truly understand the significance of these easily forgotten interactions.

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