Transmission of hospital acquired infections like the 鈥渟uperbug鈥� MRSA could be cut using the method that Google uses to rank search results, say UK researchers.
Crunching data from wards using Google鈥檚 PageRank algorithm could help focus preventative measures more accurately by identifying key routes of infection and transmission, they say.
PageRank judges the relative importance of a web page in search results based on how many other pages link to it.
Advertisement
The first response of policymakers faced with rising incidence of hospital-acquired infections, including super-bugs like MRSA (methicillin-resistant Staphylococcus aureus), has been to enforce stricter washing of hands to stem the spread.
But while that has been shown to help, infections in the UK at least are not falling, says Clive Beggs, who leads studying prevention and control of hospital-acquired infections at Bradford University, UK.
Infection networks
鈥淭he question is, how do bugs get from A to B?鈥� says Beggs. 鈥淲e don鈥檛 really know that much about the epidemiology of these infections.鈥� The extent to which infections are carried by hands, are airborne, or travel by other routes is largely unknown, he adds.
While studies have taken samples to discover how particular objects, like doctors鈥� neckties, can harbour infection, little is known about the network routes by which bugs spread across patients, staff, and the hospital environment.
Beggs鈥� colleague, mathematician , thinks the behind Google鈥檚 search engine can help, by ranking routes of infection in the same way it ranks search results.
鈥淪omething isn鈥檛 working,鈥� Shepherd told 快猫短视频. 鈥淭he hand-borne route is the major route, but there are others and we need to know what they are.鈥�
鈥淥ur new model is based very much on the way Google has achieved number one status among search engines,鈥� he explains. 鈥淲hen [Google鈥檚] spiders crawl the web they build up a connectivity matrix of links between pages.鈥�
Node search
Shepherd鈥檚 idea is to build a similar matrix describing all interactions between people and objects in a hospital ward, based on observing normal daily activity.
鈥淥bviously nurses move among patients and that can spread infection, but they also touch light switches and lots of other surfaces too,鈥� he says., 鈥淚f you observe a network of all those interactions you can build a matrix of which nodes in the network are in contact with which other nodes.鈥�
Shepherd has started testing the technique using data gathered for another study. 鈥淲e sussed out in one ward that the chief node was a light switch,鈥� he says. 鈥淚t could potentially distribute infection to the rest of the ward very quickly.鈥�
The PageRank technique will become most useful, however, after the completion of studies estimating the extent to which different interactions transfer bacteria.
Combining that information with the strength of different interactions within a ward makes it possible to calculate which ties to cut 鈥� by, perhaps, tougher cleaning 鈥� to maximally disrupt the network and cut infections.
鈥淯ltimately, we would like to produce a software tool so managers of wards can carry out the analysis for themselves,鈥� says Shepherd.
Shepherd presented preliminary results of the technique at the , September 2007
