Automated DNA Sequence-Based Early Warning System for the Detection of Methicillin-Resistant Staphylococcus aureus Outbreaks

Alexander Mellmann, Alexander W Friedrich, Nicole Rosenkötter, Jörg Rothgänger, Helge Karch, Ralf Reintjes and Dag Harmsen

PLOS Medicine, 2006, vol. 3, issue 3, 1-

Abstract: Background: The detection of methicillin-resistant Staphylococcus aureus (MRSA) usually requires the implementation of often rigorous infection-control measures. Prompt identification of an MRSA epidemic is crucial for the control of an outbreak. In this study we evaluated various early warning algorithms for the detection of an MRSA cluster. Methods and Findings: Between 1998 and 2003, 557 non-replicate MRSA strains were collected from staff and patients admitted to a German tertiary-care university hospital. The repeat region of the S. aureus protein A (spa) gene in each of these strains was sequenced. Using epidemiological and typing information for the period 1998–2002 as reference data, clusters in 2003 were determined by temporal-scan test statistics. Various early warning algorithms (frequency, clonal, and infection control professionals [ICP] alerts) were tested in a prospective analysis for the year 2003. In addition, a newly implemented automated clonal alert system of the Ridom StaphType software was evaluated. Conclusions: Rapid MRSA outbreak detection, based on epidemiological and spa typing data, is a suitable alternative for classical approaches and can assist in the identification of potential sources of infection. Harmsen and colleagues show that an early warning algorithm based on epidemiological and DNA typing is a feasible approach for detection of clusters of MRSA infection. Background: Everyone carries many types of bacteria on or in their bodies; Staphylococcus aureus is a normal bacteria for people to carry. About 25% to 30% of people have it, usually in the nose. It is usually harmless; however, this bacterium can also cause infections—especially in people who are otherwise unwell, or who have surgery. These infections need to be treated with antibiotics. Methicillin-resistant S. aureus (MRSA) is an increasing problem in much of the developed world because, unlike other types of these bacteria, MRSA cannot be killed by most of the usual antibiotics that are used, such as methicillin. Without treatment, staphylococcal infection can become very severe. Why Was This Study Done?: MRSA is a particular problem in hospitals, where there is a need to be able to identify infected and colonized people quickly and isolate and treat them. These researchers wanted to test for the best way of identifying early clusters of MRSA outbreaks, which are more serious than just single cases and are an indication of hygiene deficiencies. What Did the Researchers Do and Find?: Between 1998 and 2003 the researchers analysed 557 MRSA strains from staff and patients admitted to one German university hospital. They collected information about the characteristics (in space and time) of these people, and genetically identified each of the strains. They then looked for the most efficient way to identify an outbreak, including assessment of the risk by specially trained hospital staff, with and without genetic analysis. They also assessed a specially designed computer programme (developed by some of the authors), which combined the genetic type of the MRSA as well as details about the outbreak, such as the characteristics of the patients infected. They found that the most efficient and reliable method to identify outbreaks was to combine the genetic type of the MRSA with details about the outbreak, using the computer programme tested. What Do These Findings Mean?: The computer programme seems to be more efficient than other methods tested here in identifying when an outbreak is likely to occur. However, this is the first test of this method, and before being adopted more widely, further testing is needed in different settings and by other researchers. Where Can I Get More Information Online?: Medline Plus has many links to pages of information on different staphylococcal infections:

Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pmed00:0030033

DOI: 10.1371/journal.pmed.0030033

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