Google algorithm may help identify key routes of hospital superbugs

January 5th, 2008 - 3:50 pm ICT by admin  


London, January 5 (ANI): A method used by search engine Google to rank search results may help reduce the transmission of hospital acquired infections like the superbug MRSA, say researchers.

Clive Beggs, a Bradford University researcher who is studying prevention and control of hospital acquired infections, says that Google’s PageRank algorithm may help identify key routes of infection and transmission by analysing data from wards. He says that his may in turn help focus preventive measures more accurately.

As for the web world, PageRank ranks web pages in terms of importance by analysing how many other pages link to them.

Policymakers recommend enforcing stricter washing of hands to stem hospital-acquired infections, including MRSA.

Beggs says that though this measure has been shown to help, infections in the UK are not falling.

“The question is, how do bugs get from A to B? We don’t really know that much about the epidemiology of these infections,” New Scientist journal quoted Beggs as saying.

He says that even experts have scant knowledge about the route from where most infections come, be it hands, air or other sources.

There is also very little information about the network routes by which bugs spread across patients, staff and the hospital environment, he adds.

Beggs colleague, mathematician named Simon Shepherd, feels that the PageRank algorithm may help rank routes of infection in the same way it ranks search results in the web world.

“Something isn’t working. The hand-borne route is the major route, but there are others and we need to know what they are,” Shepherd said.

“Our new model is based very much on the way Google has achieved number one status among search engines. When (Google’s) spiders crawl the web they build up a connectivity matrix of links between pages,” he added.

Shepherd is now working on a similar matrix to observe normal daily activity in hospital wards, and to understand all interactions occurring between people and objects.

He has already begun testing the technique using data gathered for another study.

“We sussed out in one ward that the chief node was a light switch. It could potentially distribute infection to the rest of the ward very quickly,” he said. (ANI)

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