This article is more than 5 years old. Information may no longer be current.
Electronic sensors accurately identify S. aureus transmission
Click Here to Manage Email Alerts
Wireless close-contact sensors may be able to accurately map transmissions of Staphylococcus aureus within hospitals, according to recently published data.
“Contact networks have been increasingly used in modeling the spread of infectious diseases,” the researchers said in a press release. “Yet, the contacts collected were often incomplete or used proxies that were thought to capture situation at risk. In this unique experiment, the joint analysis of contact and carriage validates the use of close-proximity interactions recorded by electronic devices, and opens a new field for prevention measures in hospitals.”
Researchers examined S. aureus transmission in a 200-bed, long-term and rehabilitation hospital in France using wireless sensors. The sensors, worn throughout the 4-month study period by patients and health care workers, automatically recorded the identity of other nearby sensors every 30 seconds. Transmission events resulting from close proximity interactions (CPIs) were identified by monitoring S. aureus carriage through the weekly collection of nasal swabs, which then were screened to determine the movement of individual strains. A model transmission network created from these data was analyzed against permutated simulations to measure accuracy.
Figure 1. This image shows the network of contacts and MRSA carriage. Patients and health care workers (with a '+' on their heads) are linked by a grey line if they had contact. Methicillin-resistant S. aureus carriers are shown in red.
Source: Obadia et al.
Of the 329 patients and 261 HCWs for whom CPIs and S. aureus carriage were recorded, 201 were not colonized at admission. An average of 85,025 CPIs were recorded daily, which yielded 173 transmission events during the study period. Daily CPIs were sustained for much longer periods between patients than HCWs with patients or other HCWs.
There were 114 distinct S. aureus strains isolated in multiple participants, with each strain identified in three participants on average.
Using CPI paths to link incidents between individuals with matching strains had fewer intermediaries than predicted by chance through simulation (P < .001). Transmission paths were identified between transmitters and recipients for 97% of observed cases. In addition, the spread of S. aureus was observed most frequently when a HCW acted as an intermediary (P = .0004).
“In contrast to weekly swabbing, wireless sensors recorded interactions permanently and made it unlikely that the network of interactions was imperfectly observed,” the researchers wrote. “With the evidence we provide on the correlation between CPI paths and transmission events, this strengthens the interest of this proxy measure as a cheap, feasible and informative method for studying S. aureus transmission.”
Disclosure: The researchers report no relevant financial disclosures.
Collapse
Click Here to Manage Email Alerts