Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006-2011.

BACKGROUND: In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. METHODS: Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. RESULTS: Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007-2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). CONCLUSIONS: Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems.

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

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.

Effectiveness of Methicillin-resistant Staphylococcus aureus surveillance among exposed roommates in community hospitals: Conventional culture vs direct PCR.

BACKGROUND: Roommates of unrecognized nosocomial Methicillin-Resistant Staphylococcus aureus (MRSA) cases are at higher acquisition risk; however, optimal surveillance strategies are unknown. METHODS: Using simulation, we analyzed surveillance testing and isolation strategies for MRSA among exposed hospital roommates. We compared isolating exposed roommates until conventional culture testing on day six (Cult6) and a nasal polymerase chain reaction (PCR) test on day three (PCR3) with/without day zero culture testing (Cult0). The model represents MRSA transmission in medium-sized hospitals using data and recommended best practices from the literature and Ontario community hospitals. RESULTS: Cult0+PCR3 incurred a slightly lower number of MRSA colonizations and 38.9% lower annual cost in the base case compared to Cult0+Cult6 because the reduced isolation cost compensated for the increased testing cost. The reduction in MRSA colonizations was due to 54.5% drop in MRSA transmissions during isolation as PCR3 reduced exposure of MRSA-free roommates to new MRSA carriers. Removing the day zero culture test from Cult0+PCR3 increased total cost, the number of MRSA colonization, and missed cases by $1,631, 4.3%, and 50.9%, respectively. Improvements were higher under aggressive MRSA transmission scenarios. DISCUSSION AND CONCLUSIONS: Adopting direct nasal PCR testing for determining post-exposure MRSA status reduces transmission risk and costs. Day zero culture would still be beneficial.

A prospective study to examine the epidemiology of methicillin-resistant Staphylococcus aureus and Clostridium difficile contamination in the general environment of three community hospitals in southern Ontario, Canada.

BACKGROUND: The hospital environment has been suggested as playing an important role in the transmission of hospital-associated (HA) pathogens. However, studies investigating the contamination of the hospital environment with methicillin-resistant Staphylococcus aureus (MRSA) or Clostridium difficile have generally focused on point prevalence studies of only a single pathogen. Research evaluating the roles of these two pathogens, concurrently, in the general hospital environment has not been conducted. The objectives of this study were to determine the prevalence and identify risk factors associated with MRSA and C. difficile contamination in the general environment of three community hospitals, prospectively. METHODS: Sampling of environmental surfaces distributed over the medicine and surgical wards at each hospital was conducted once a week for four consecutive weeks. Sterile electrostatic cloths were used for environmental sampling and information regarding the surface sampled was recorded. For MRSA, air sampling was also conducted. Enrichment culture was performed and spa typing was performed for all MRSA isolates. For C. difficile, isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. Using logistic regression, the following risk factors were examined for MRSA or C. difficile contamination: type of surface sampled, surface material, surface location, and the presence/absence of the other HA pathogen under investigation. RESULTS: Overall, 11.8% (n=612) and 2.4% (n=552) of surfaces were positive for MRSA and C. difficile, respectively. Based on molecular typing, five different MRSA strains and eight different C. difficile ribotypes, including ribotypes 027 (15.4%) and 078 (7.7%), were identified in the hospital environment. Results from the logistic regression model indicate that compared to computer keyboards, the following surfaces had increased odds of being contaminated with MRSA: chair backs, hand rails, isolation carts, and sofas. CONCLUSIONS: MRSA and C. difficile were identified from a variety of surfaces in the general hospital environment.Several surfaces had an increased risk of being contaminated with MRSA but further studies regarding contact rates, type of surface material, and the populations using these surfaces are warranted.

Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model.

Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models.