Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Jul 8:14:375.
doi: 10.1186/1471-2334-14-375.

The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital

Affiliations

The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital

Meredith C Faires et al. BMC Infect Dis. .

Abstract

Background: In healthcare facilities, conventional surveillance techniques using rule-based guidelines may result in under- or over-reporting of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, as these guidelines are generally unvalidated. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting MRSA clusters, validate clusters using molecular techniques and hospital records, and determine significant differences in the rate of MRSA cases using regression models.

Methods: Patients admitted to a community hospital between August 2006 and February 2011, and identified with MRSA>48 hours following hospital admission, were included in this study. Between March 2010 and February 2011, MRSA specimens were obtained for spa typing. MRSA clusters were investigated using a retrospective temporal scan statistic. Tests were conducted on a monthly scale and significant clusters were compared to MRSA outbreaks identified by hospital personnel. Associations between the rate of MRSA cases and the variables year, month, and season were investigated using a negative binomial regression model.

Results: During the study period, 735 MRSA cases were identified and 167 MRSA isolates were spa typed. Nine different spa types were identified with spa type 2/t002 (88.6%) the most prevalent. The temporal scan statistic identified significant MRSA clusters at the hospital (n=2), service (n=16), and ward (n=10) levels (P ≤ 0.05). Seven clusters were concordant with nine MRSA outbreaks identified by hospital staff. For the remaining clusters, seven events may have been equivalent to true outbreaks and six clusters demonstrated possible transmission events. The regression analysis indicated years 2009-2011, compared to 2006, and months March and April, compared to January, were associated with an increase in the rate of MRSA cases (P ≤ 0.05).

Conclusions: The application of the temporal scan statistic identified several MRSA clusters that were not detected by hospital personnel. The identification of specific years and months with increased MRSA rates may be attributable to several hospital level factors including the presence of other pathogens. Within hospitals, the incorporation of the temporal scan statistic to standard surveillance techniques is a valuable tool for healthcare workers to evaluate surveillance strategies and aid in the identification of MRSA clusters.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Incidence rate of methicillin-resistant Staphylococcus aureus infections and colonization per month in a community hospital.
Figure 2
Figure 2
Minimum spanning tree analysis of 167 methicillin-resistant Staphylococcus aureus (MRSA) patient isolates. The size of each circle is proportional to the number of isolates. Ridom spa types are presented in each circle. Numbers intersecting the black lines indicate the difference in the number of repeats between connecting circles. Colours refer to the number of MRSA isolates: red > 20, dark blue ≤ 5, light blue ≤ 2.

Similar articles

Cited by

References

    1. Köser CU, Holden MT, Ellington MJ, Cartwright EJ, Brown NM, Ogilvy-Stuart AL, Hsu LY, Chewapreecha C, Croucher NJ, Harris SR, Sanders M, Enright MC, Dougan G, Bentley SD, Parkhill J, Fraser LJ, Betley JR, Schulz-Trieglaff OB, Smith GP, Peacock SJ. Rapid whole-genome sequencing for investigation of a neonatal MRSA outbreak. N Engl J Med. 2012;14:2267–2275. - PMC - PubMed
    1. Huang SS, Yokoe DS, Stelling J, Placzek H, Kulldorff M, Kleinman K, O’Brien TF, Calderwood MS, Vostok J, Dunn J, Platt R. Automated detection of infectious disease outbreaks in hospitals: a retrospective cohort study. PLoS Med. 2010;14:e1000238. - PMC - PubMed
    1. Craven DE, Shapiro DS. Staphylococcus aureus: times, they are a-changin’. Clin Infect Dis. 2006;14:179–180. - PubMed
    1. Mellmann A, Friedrich AW, Rosenkötter N, Rothgänger J, Karch H, Reintjes R, Harmsen D. Automated DNA sequence-based early warning system for the detection of methicillin-resistant Staphylococcus aureus outbreaks. PLoS Med. 2006;14:e33. - PMC - PubMed
    1. SaTScan software for the spatial and space-time scan statistic. http://www.satscan.org/

Publication types

MeSH terms