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Monitoring approach spots warning signs of Legionella outbreaks

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Monitoring approach could help snuff out Legionella outbreaks
Graphical abstract. Credit: Water Research (2024). DOI: 10.1016/j.watres.2024.122510

Routine, relatively low-cost monitoring of several factors influencing water safety could ward off Legionnaires’ disease outbreaks in hospitals, nursing homes and other health care settings, a new study suggests.

Legionella bacteria occur naturally in freshwater environments, like lakes and streams, and are usually harmless in those settings. But Legionella threatens human health when it gets into building water systems and increases in numbers, and is especially deadly among the elderly and other medically vulnerable people. Outbreaks are notoriously difficult to pin down and contain.

Using easy-to-measure water quality data, the researchers built a model they hoped would allow for rapid, accurate assessment of the water ecosystem to allow for speedy responses to situations that increased the likelihood of Legionella growth. Based on an analysis of water samples from a large New York building, the machine learning method, called statistical learning theory, proved reliable—and more accurate than conventional statistical methods—in predicting threats.

The study appears in Water Research.

In health care and other settings, efforts to keep the bacteria at bay vary and there’s no consensus on best practices, said Mark Weir, an associate professor of environmental health sciences at The Ohio State University College of Public Health and part of the university’s Sustainability Institute.

“Water is never going to be sterile and we continue to have a misguided view that we can eradicate Legionella,” Weir said. “Bacteria will always be there, so instead of trying to eliminate that, my lab is looking for answers by examining the entire microbial community and other influences within water systems.”

As soon as a pipe has water running through it, a slimy layer of bacteria and amoeba, known as biofilm, begins to grow. Weir’s approach includes analyzing microorganism activity alongside factors including the pH and temperature of the water, electrical conductivity, chlorine concentration and oxidation reduction potential, a measure of the capacity of a solution to give or receive electrons.

“All of these can be measured in real time and on a regular basis for cheap, or at least much cheaper than some of the other alternatives,” Weir said.

It’s important to look for solutions to water safety that low-resource health care providers can afford to use, he said.

“Outside of a large health system, many of the places that face threats from Legionella can’t afford expensive solutions. They might have to decide between maintaining an MRI machine or doing more complex water sampling,” Weir said.

He said he’s hopeful this work could lead to a clearer blueprint of what makes for an effective water safety plan and more consistency in approaches to protecting people from deadly pathogens.

More information:
Juan Xu et al, Development of a machine learning model to support low cost real-time Legionella monitoring in premise plumbing systems, Water Research (2024). DOI: 10.1016/j.watres.2024.122510

Provided by
The Ohio State University


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Monitoring approach spots warning signs of Legionella outbreaks (2025, February 17)
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