Impact of the COVID-19 Pandemic on Inpatient Antibiotic Use in the United States, January 2019 Through July 2022.

Antimicrobial use data reported to the National Healthcare Safety Network's Antimicrobial Use and Resistance Module between January 2019 and July 2022 were analyzed to assess the impact of the COVID-19 pandemic on inpatient antimicrobial use.

Rethinking Clostridioides difficile infection (CDI) surveillance definitions based on changing healthcare utilisation and a more realistic incubation period: reviewing data from a tertiary-referral hospital, Ireland, 2012 to 2021.

BackgroundCommunity-associated Clostridioides difficile infections (CA-CDI) have increased worldwide. Patients with CDI-related symptoms occurring < 48 hours after hospitalisation and no inpatient stay 12 weeks prior are classified as CA-CDI, regardless of hospital day attendances 3 months before CDI onset. Healthcare-associated (HA) CDIs include those with symptom onset ≥ 48 hours post hospitalisation.AimTo consider an incubation period more reflective of CDI, and changing healthcare utilisation, we measured how varying surveillance specifications to categorise patients according to their CDI origin resulted in changes in patients' distribution among CDI origin categories.MethodsNew CDI cases between 2012-2021 from our hospital were reviewed. For patients with CA-CDI, hospital day attendances in the 3 months prior were recorded. CA-CDI patients with hospital day attendances and recently discharged CDI patients (RD-CDI; CDI onset 4-12 weeks after discharge) were combined into a new 'healthcare-exposure' category (HE-CDI). Time from hospitalisation to disease onset was varied and the midpoint between optimal and balanced cut-offs was used instead of 48 hours to categorise HA-CDI.ResultsOf 1,047 patients, 801 (76%) were HA-CDI, 205 (20%) CA-CDI and 41 (4%) were RD-CDI. Of the CA-CDI cohort, 45 (22%) met recent HE-CDI criteria and, when reassigned, reduced CA-CDI to 15%. Sensitivity analysis indicated a day 4 cut-off for assigning HA-CDI. Applying this led to 46 HA-CDI reassigned as CA-CDI. Applying both HE and day 4 criteria led to 72% HA-CDI, 20% CA-CDI, and 8% HE-CDI (previously RD-CDI).ConclusionCDI surveillance specifications reflecting healthcare exposure and an incubation period more characteristic of C. difficile may improve targeted CDI prevention interventions.

Clostridioides difficile infection in neurosurgical patients in a national centre over 10 years: less common but associated with longer hospital stays.

BACKGROUND: Clostridioides difficile infection (CDI) is a leading cause of healthcare-associated (HA) diarrhoea, contributing to patient morbidity and prolonged length-of-stay (LOS). We retrospectively assessed CDI over a decade in a national neurosurgical centre, with a multi-disciplinary approach to CDI surveillance and antimicrobial stewardship, by comparing CDI patients with other patient groups. METHODS: Data on CDI in neurosurgical inpatients between January 2012 and December 2021 were collated. Disease-specific variables were compared to other inpatients with CDI. Rates per 10,000 bed days used were calculated. Patient-specific differences were compared with neurosurgical patients without CDI. CDI rates by patient group were explored using odds ratio (OR) and χ2 analyses. Negative binomial regression was used to investigate CDI rates over time. RESULTS: Of 50 neurosurgical patients with CDI, all were HA; the average age was 53 years (standard deviation (SD) 16.3 years), 49 were first-episode CDI, and three had severe CDI. The majority (76.7%) had received recent antimicrobials. Compared with non-neurosurgical CDI patients, neurosurgical CDI rates differed significantly (1.9 versus 3.6 per 10,000 bed days used, p < 0.05), neurosurgical patients were younger (p ≤ 0.01), C. difficile testing was more likely to be requested by neurosurgeons (OR 2.4; p ≤ 0.01), and the proportion of severe CDI was higher (6% versus 2%, OR 3.0, p = 0.07, confidence interval (CI) 0.54 to 11.3). Within the neurosurgical cohort, CDI patients had an average LOS four times that of other patients (CI 15.2 to 35.1; p < 0.01) and were older (53.5 versus 47.8 years, CI 0.1 to 11 years; p < 0.05). Only one CDI outbreak was linked to neurosurgical patients. CONCLUSION: CDI in neurosurgery patients differed from the wider hospital, with greater awareness of CDI testing. Longer LOS impacted bed utilisation with limited capacity. Robust surveillance supports proactive antimicrobial stewardship programmes in this vulnerable population.

Unsuspected Clonal Spread of Methicillin-Resistant Staphylococcus aureus Causing Bloodstream Infections in Hospitalized Adults Detected Using Whole Genome Sequencing.

BACKGROUND: Though detection of transmission clusters of methicillin-resistant Staphylococcus aureus (MRSA) infections is a priority for infection control personnel in hospitals, the transmission dynamics of MRSA among hospitalized patients with bloodstream infections (BSIs) has not been thoroughly studied. Whole genome sequencing (WGS) of MRSA isolates for surveillance is valuable for detecting outbreaks in hospitals, but the bioinformatic approaches used are diverse and difficult to compare. METHODS: We combined short-read WGS with genotypic, phenotypic, and epidemiological characteristics of 106 MRSA BSI isolates collected for routine microbiological diagnosis from inpatients in 2 hospitals over 12 months. Clinical data and hospitalization history were abstracted from electronic medical records. We compared 3 genome sequence alignment strategies to assess similarity in cluster ascertainment. We conducted logistic regression to measure the probability of predicting prior hospital overlap between clustered patient isolates by the genetic distance of their isolates. RESULTS: While the 3 alignment approaches detected similar results, they showed some variation. A gene family-based alignment pipeline was most consistent across MRSA clonal complexes. We identified 9 unique clusters of closely related BSI isolates. Most BSIs were healthcare associated and community onset. Our logistic model showed that with 13 single-nucleotide polymorphisms, the likelihood that any 2 patients in a cluster had overlapped in a hospital was 50%. CONCLUSIONS: Multiple clusters of closely related MRSA isolates can be identified using WGS among strains cultured from BSI in 2 hospitals. Genomic clustering of these infections suggests that transmission resulted from a mix of community spread and healthcare exposures long before BSI diagnosis.

Impact of antimicrobial stewardship programs on antibiotic consumption and antimicrobial resistance in four Colombian healthcare institutions.

BACKGROUND: Antimicrobial stewardship programs (ASPs) have become a fundamental pillar in optimizing antimicrobial usage, improving patient care, and reducing antimicrobial resistance (AMR). Herein we evaluated the impact of an ASP on antimicrobial consumption and AMR in Colombia. METHODS: We designed a retrospective observational study and measured trends in antibiotic consumption and AMR before and after the implementation of an ASP using interrupted time series analysis over a 4-year period (24 months before and 24 months after ASP implementation). RESULTS: ASPs were implemented according to the available resources in each of the institutions. Before ASP implementation, there was a trend toward an increase in the antibiotic consumption of all measured antimicrobials selected. Afterward, an overall decrease in antibiotic consumption was observed. The use of ertapenem and meropenem decreased in hospital wards, while a decrease in the use of ceftriaxone, cefepime, piperacillin/tazobactam, meropenem, and vancomycin was observed in intensive care units. After ASP implementation, the trend toward an increase of oxacillin-resistant Staphylococcus aureus, ceftriaxone-resistant Escherichia coli, and meropenem-resistant Pseudomonas aeruginosa was reversed. CONCLUSIONS: In our study, we showed that ASPs are a key strategy in tackling the emerging threat of AMR and have a positive impact on antibiotic consumption and resistance.

Burden of multidrug and extensively drug-resistant ESKAPEE pathogens in a secondary hospital care setting in Greece.

Bacterial antibiotic resistance (AMR) is a significant threat to public health, with the sentinel 'ESKAPEE' pathogens, being of particular concern. A cohort study spanning 5.5 years (2016-2021) was conducted at a provincial general hospital in Crete, Greece, to describe the epidemiology of ESKAPEE-associated bacteraemia regarding levels of AMR and their impact on patient outcomes. In total, 239 bloodstream isolates were examined from 226 patients (0.7% of 32 996 admissions) with a median age of 75 years, 28% of whom had severe comorbidity and 46% with prior stay in ICU. Multidrug resistance (MDR) was lowest for Pseudomonas aeruginosa (30%) and Escherichia coli (33%), and highest among Acinetobacter baumannii (97%); the latter included 8 (22%) with extensive drug-resistance (XDR), half of which were resistant to all antibiotics tested. MDR bacteraemia was more likely to be healthcare-associated than community-onset (RR 1.67, 95% CI 1.04-2.65). Inpatient mortality was 22%, 35% and 63% for non-MDR, MDR and XDR episodes, respectively (P = 0.004). Competing risks survival analysis revealed increasing mortality linked to longer hospitalisation with increasing AMR levels, as well as differential pathogen-specific effects. A. baumannii bacteraemia was the most fatal (14-day death hazard ratio 3.39, 95% CI 1.74-6.63). Differences in microbiology, AMR profile and associated mortality compared to national and international data emphasise the importance of similar investigations of local epidemiology.

Trends and patterns of cause-specific hospitalizations in mainland Portugal between 2000 and 2016.

OBJECTIVES: This study aimed to describe trends and patterns of cause-specific hospitalizations in mainland Portugal between 2000 and 2016. STUDY DESIGN: This was a retrospective observational study based on hospital discharge data during the period 2000-2016 in mainland Portugal. METHODS: All inpatient hospital discharges among mainland Portuguese public hospitals were considered to evaluate trends and patterns over the years through hospitalization proportions, number of hospitalizations, age-standardized hospitalization rates (direct standardization using the European standard population), and the number of in-hospital stay days (bed-days). Health Cost and Utilization Project Clinical Classifications Software was used to categorize and cluster inpatients' principal diagnosis. RESULTS: Between 2000 and 2002 and between 2014 and 2016, age-standardized hospitalization rates decreased by 8.6%. Moreover, "liveborn," "diseases of the heart," and "respiratory infections" were the leading hospitalization causes in both periods with a variation of -8.8%, -8.3%, and 13.4% on age-standardized hospitalization rate, respectively. The age-standardized hospitalization rate due to "bacterial infection" increased by 108.7%. "Respiratory diseases" are the leading cause responsible for more in-hospital stay days in the period 2014-2016 (48.6% increase). All Portuguese regions presented decreasing overall trends in their age-standardized hospitalization rates in the study period, yet increasing trends were observed until 2004 except for the Lisbon region; in addition, the number of in-hospital stay days remained relatively stable through time. CONCLUSIONS: Hospitalizations in mainland Portugal decreased between 2000 and 2016 with heterogeneous patterns considering time, age group, and gender. "Aspiration pneumonitis; food/vomitus," "diseases of the white blood cells," "other nutritional, endocrine, and metabolic disorders," "bacterial infection," and "pathological fractures" revealed substantial increases, and further evaluations and monitoring are required.

Decreasing High-risk Exposures for Healthcare Workers Through Universal Masking and Universal Severe Acute Respiratory Syndrome Coronavirus 2 Testing on Entry to a Tertiary Care Facility.

We describe the impact of universal masking and universal testing at admission on high-risk exposures to severe acute respiratory syndrome coronavirus 2 for healthcare workers. Universal masking decreased the rate of high-risk exposures per patient-day by 68%, and universal testing further decreased those exposures by 77%.

Implementation of an automated cluster alert system into the routine work of infection control and hospital epidemiology: experiences from a tertiary care university hospital.

BACKGROUND: Early detection of clusters of pathogens is crucial for infection prevention and control (IPC) in hospitals. Conventional manual cluster detection is usually restricted to certain areas of the hospital and multidrug resistant organisms. Automation can increase the comprehensiveness of cluster surveillance without depleting human resources. We aimed to describe the application of an automated cluster alert system (CLAR) in the routine IPC work in a hospital. Additionally, we aimed to provide information on the clusters detected and their properties. METHODS: CLAR was continuously utilized during the year 2019 at Charité university hospital. CLAR analyzed microbiological and patient-related data to calculate a pathogen-baseline for every ward. Daily, this baseline was compared to data of the previous 14 days. If the baseline was exceeded, a cluster alert was generated and sent to the IPC team. From July 2019 onwards, alerts were systematically categorized as relevant or non-relevant at the discretion of the IPC physician in charge. RESULTS: In one year, CLAR detected 1,714 clusters. The median number of isolates per cluster was two. The most common cluster pathogens were Enterococcus faecium (n = 326, 19 %), Escherichia coli (n = 274, 16 %) and Enterococcus faecalis (n = 250, 15 %). The majority of clusters (n = 1,360, 79 %) comprised of susceptible organisms. For 906 alerts relevance assessment was performed, with 317 (35 %) alerts being classified as relevant. CONCLUSIONS: CLAR demonstrated the capability of detecting small clusters and clusters of susceptible organisms. Future improvements must aim to reduce the number of non-relevant alerts without impeding detection of relevant clusters. Digital solutions to IPC represent a considerable potential for improved patient care. Systems such as CLAR could be adapted to other hospitals and healthcare settings, and thereby serve as a means to fulfill these potentials.

Associations of Early COVID-19 Cases in San Francisco With Domestic and International Travel.

In early-to-mid March 2020, 20 of 46 (43%) COVID-19 cases at a tertiary care hospital in San Francisco, California were travel related. Cases were significantly associated with travel to either Europe (odds ratio, 6.1) or New York (odds ratio, 32.9). Viral genomes recovered from 9 of 12 (75%) cases co-clustered with lineages circulating in Europe.

Evaluating the ALERT algorithm for local outbreak onset detection in seasonal infectious disease surveillance data.

Estimation of epidemic onset timing is an important component of controlling the spread of seasonal infectious diseases within community healthcare sites. The Above Local Elevated Respiratory Illness Threshold (ALERT) algorithm uses a threshold-based approach to suggest incidence levels that historically have indicated the transition from endemic to epidemic activity. In this paper, we present the first detailed overview of the computational approach underlying the algorithm. In the motivating example section, we evaluate the performance of ALERT in determining the onset of increased respiratory virus incidence using laboratory testing data from the Children's Hospital of Colorado. At a threshold of 10 cases per week, ALERT-selected intervention periods performed better than the observed hospital site periods (2004/2005-2012/2013) and a CUSUM method. Additional simulation studies show how data properties may effect ALERT performance on novel data. We found that the conditions under which ALERT showed ideal performance generally included high seasonality and low off-season incidence.

Impact of maternal death reviews at a rural hospital in Zambia: a mixed methods study.

BACKGROUND: Maternal mortality in sub-Saharan Africa remains high despite programmatic efforts to improve maternal health. In 2007, the Zambian Ministry of Health mandated facility-based maternal death review (MDR) programs in line with World Health Organization recommendations. We assessed the impact of an [MDR program] at a district-level hospital in rural Zambia. METHODS: We conducted a mixed methods convergent study using hospital data on maternal mortality and audit reports of 106 maternal deaths from 2007 to 2011. To evaluate the overall impact of MDR on maternal mortality, we compared baseline (2007) to late (2010-11) post-intervention inpatient maternal mortality indicators. MDR committee reports were coded and dominant themes were extracted in a qualitative analysis. We assessed potential risk factors for maternal mortality in a before-and-after design comparing the periods 2008-09 and 2010-11. RESULTS: In-hospital maternal mortality declined from 23 per thousand live births in 2007 to 8 per thousand in 2010-11 (P < 0.01). Maternal case fatality for puerperal sepsis and uterine rupture decreased significantly from 63 and 32% in 2007 to 10 and 9% in 2010-11 (P < 0.01). No significant reduction was seen in case fatality due to postpartum hemorrhage. Qualitative analysis of risk factors for maternal mortality revealed four core themes: standards of practice, health systems, accessibility, and patient factors. Specific risk factors included delayed referral, missed diagnoses, intra-hospital delays in care, low medication inventory, and medical error. We found no statistically significant differences in the prevalence of risk factors between the before-and-after periods. CONCLUSIONS: Implementation of MDR was accompanied by a significant decrease in maternal mortality with reductions in maternal death from puerperal sepsis and uterine rupture, but not postpartum hemorrhage. Qualitative analysis of audit reports identified several modifiable risk factors within four core areas. Comparisons of potential explanatory factors did not show any differences over time. These results imply that MDR offers a means for hospitals to curtail maternal deaths, except deaths due to postpartum hemorrhage, suggesting additional interventions are needed. Documentation of MDR meetings provides an instrument to guide further quality improvements.

The Clean Care Contest: promoting hand hygiene among healthcare and medical students.

INTRODUCTION: Despite continuing efforts, compliance rates and knowledge of best practices in hand hygiene remain disappointing. Recognizing that conventional educational tools seem out of touch with young people and that the med and messages contents need refreshing, the Italian Study Group of Hospital Hygiene of the Italian Society of Hygiene, Preventive Medicine and Public Health devised a novel approach to promote the creation of innovative educational tools for improving knowledge of, and compliance with, hand hygiene rules among healthcare and medical students. METHODS: A contest in creating educational material on hand hygiene practices involved university students of nursing and medicine, and of other healthcare degrees. Students from the universities of the GISIO network were invited to create educational material (e.g., videos, posters, presentations, leaflets, and screensavers) to be presented by May 5th 2019 during the World Hand Hygiene Day / Save Lives: Clean Your Hands Global Annual Initiative of the World Health Organization). A local and a national winners were awarded. RESULTS: Three different local and national contests were performed during 2016, 2017 and 2018. During the three-year period, more than 270 educational tools have been developed: 130 (48%) were judged useful for hand hygiene promotion campaigns. The most frequent projects participating in the contests were videos (39%), posters (29%), leaflets (14%), and others (18%) submitted by more than 1,500 students of nursing (40%), medicine (31%), dentistry (7%), and of other healthcare courses in 14 universities. Products were evaluated by a local committee and, subsequently, local winners represented their University in a national contest. CONCLUSIONS: The contest provided a framework for the creation of innovative and potentially effective educational tools via an engaging approach that leveraged student creativity. Given the need to improve compliance rates, this study suggests that new ways can be advantageously explored to teach hand hygiene procedures and increase awareness of the importance of their consistent use among healthcare and medical students.

Prospective, Real-time Metagenomic Sequencing During Norovirus Outbreak Reveals Discrete Transmission Clusters.

BACKGROUND: Norovirus outbreaks in hospital settings are a common challenge for infection prevention teams. Given the high burden of norovirus in most communities, it can be difficult to distinguish between ongoing in-hospital transmission of the virus and new introductions from the community, and it is challenging to understand the long-term impacts of outbreak-associated viruses within medical systems using traditional epidemiological approaches alone. METHODS: Real-time metagenomic sequencing during an ongoing norovirus outbreak associated with a retrospective cohort study. RESULTS: We describe a hospital-associated norovirus outbreak that affected 13 patients over a 27-day period in a large, tertiary, pediatric hospital. The outbreak was chronologically associated with a spike in self-reported gastrointestinal symptoms among staff. Real-time metagenomic next-generation sequencing (mNGS) of norovirus genomes demonstrated that 10 chronologically overlapping, hospital-acquired norovirus cases were partitioned into 3 discrete transmission clusters. Sequencing data also revealed close genetic relationships between some hospital-acquired and some community-acquired cases. Finally, this data was used to demonstrate chronic viral shedding by an immunocompromised, hospital-acquired case patient. An analysis of serial samples from this patient provided novel insights into the evolution of norovirus within an immunocompromised host. CONCLUSIONS: This study documents one of the first applications of real-time mNGS during a hospital-associated viral outbreak. Given its demonstrated ability to detect transmission patterns within outbreaks and elucidate the long-term impacts of outbreak-associated viral strains on patients and medical systems, mNGS constitutes a powerful resource to help infection control teams understand, prevent, and respond to viral outbreaks.

Expansion of Vancomycin-Resistant Enterococcus faecium in an Academic Tertiary Hospital in Southwest Germany: a Large-Scale Whole-Genome-Based Outbreak Investigation.

Vancomycin-resistant Enterococcus faecium (VREfm) is a frequent cause of nosocomial outbreaks. In the second half of 2015, a sharp increase in the incidence of VREfm was observed at our university medical center. Next-generation sequencing (NGS) was used to analyze the first isolates of VREfm recovered from patients between 2010 and 2016 (n = 773) in order to decipher epidemiological change, outbreak dynamics, and possible transmission routes. VREfm isolates were analyzed using whole-genome sequencing followed by sequence type extraction and phylogenetic analysis. We examined epidemiological data, room occupancy data, and patient transferals and calculated an intensity score for patient-to-patient contact. Phylogenetic analysis revealed the presence of 38 NGS clusters and 110 single clones. The increase of VREfm was caused mainly by the expansion of two newly introduced NGS clusters, comprising VanB-type strains determined by multilocus sequence typing (MLST) as sequence type 80 (ST80) and ST117. By combining phylogenetic information with epidemiological data, intrahospital transmission could be demonstrated, however to a lesser extent than initially expected based solely on epidemiological data. The outbreak clones were continuously imported from other hospitals, suggesting a change in the epidemiological situation at a regional scale. By tracking intrahospital patient transferals, two major axes could be identified that contributed to the spread of VREfm within the hospital. NGS-based outbreak analysis revealed a dramatic change in the local and regional epidemiology of VREfm, emphasizing the role of health care networks in the spread of VREfm.

Impact of infection prevention and control training on health facilities during the Ebola virus disease outbreak in Guinea.

BACKGROUND: In 2014-2016, West Africa faced the most deadly Ebola Virus Disease (EVD) outbreak in history. A key strategy to overcome this outbreak was continual staff training in Infection Prevention and Control (IPC), with a focus on Ebola. This research aimed to evaluate the impact of IPC training and the quality of IPC performance in health care facilities of one municipality of Conakry, Guinea. METHODS: This study was conducted in February 2016. All health facilities within Ratoma municipality, Conakry, Guinea, were evaluated based on IPC performance standards developed by the Guinean Ministry of Health. The IPC performance of healthcare facilities was categorised into high or low IPC scores based on the median IPC score of the sample. The Mantel-Haenzsel method and logistic regression were used for statistical analysis. RESULTS: Twenty-five percent of health centres had one IPC-trained worker, 53% had at least two IPC-trained workers, and 22% of health centres had no IPC-trained workers. An IPC score above median was positively associated with the number of trained staff; health centres with two or more IPC-trained workers were eight times as likely to have an IPC score above median, while those with one IPC-trained worker were four times as likely, compared to centres with no trained workers. Health centres that implemented IPC cascade training to untrained medical staff were five times as likely to have an IPC score above median. CONCLUSIONS: This research highlights the importance of training healthcare staff in IPC and organising regular cascade trainings. IPC strategies implemented during the outbreak should continue to be reinforced for the better health of patients and medical staff, and be considered a key factor in any outbreak response.

Modelling two cause-specific hazards of competing risks in one cumulative proportional odds model?

Competing risks extend standard survival analysis to considering time-to-first-event and type-of-first-event, where the event types are called competing risks. The competing risks process is completely described by all cause-specific hazards, ie, the hazard marked by the event type. Separate Cox models for each cause-specific hazard are the standard approach to regression modelling, but they come with the interpretational challenge that there are as many regression coefficients as there are competing risks. An alternative approach is to directly model the cumulative event probabilities, but again, there will be as many models as there are competing risks. The aim of this paper is to investigate the usefulness of a third alternative. Proportional odds modelling of all cause-specific hazards summarizes the effect of one covariate on "opposing" competing outcomes in one regression coefficient. For instance, if the competing outcomes are hospital death and alive discharge from hospital, the modelling assumption is that a covariate affects both outcomes in opposing directions, but the effect size is of the same absolute magnitude. We will investigate the interpretational aspects of the approach analysing a data set on intensive care unit patients using parametric methods.

Estimating the impact post randomization changes in staff behavior in infection prevention trials: a mathematical modeling approach.

BACKGROUND: Randomized controlled trials (RCTs) of behavior-based interventions are particularly vulnerable to post-randomization changes between study arms. We assess the impact of such a change in a large, multicenter study of universal contact precautions to prevent infection transmission in intensive care units. METHODS: We construct a stochastic mathematical model of methicillin-resistant Staphylococcus aureus (MRSA) acquisition in a simulated 18-bed intensive care unit (ICU). Using parameters from a recent study of contact precautions that reported a post-randomization change in contact rates, with fewer visits observed in the treatment arm, we explore the impact of several possible interpretations of this change on MRSA acquisition rates. RESULTS: Scenarios where contact precautions resulted in less patient visitation resulted in a mean decrease in MRSA acquisition rate of 37%, accounting for much of the effect reported in the trial. CONCLUSIONS: Behavior changes that impact the contact rate have the potential to drastically alter the results of RCTs in infection control settings. Careful monitoring for these changes, and an assessment of which changes will likely have the greatest impact on the study before the study begins are both recommended.

Discontinuation of contact precautions with the introduction of universal daily chlorhexidine bathing.

Contact precautions are a traditional strategy to prevent transmission of methicillin-resistant Staphylococcus aureus (MRSA). Chlorhexidine bathing is increasingly used to decrease MRSA burden and transmission in intensive care units (ICUs). We sought to evaluate a hospital policy change from routine contact precautions for MRSA compared with universal chlorhexidine bathing, without contact precautions. We measured new MRSA acquisition in ICU patients and surveyed for MRSA environmental contamination in common areas and non-MRSA patient rooms before and after the policy change. During the baseline and chlorhexidine bathing periods, the number of patients (453 vs. 417), ICU days (1999 vs. 1703) and MRSA days/1000 ICU days (109 vs. 102) were similar. MRSA acquisition (2/453 vs. 2/457, P = 0·93) and environmental MRSA contamination (9/474 vs. 7/500, P = 0·53) were not significantly different between time periods. There were 58% fewer contact precaution days in the ICU during the chlorhexidine period (241/1993 vs. 102/1730, P < 0·01). We found no evidence that discontinuation of contact precautions for patients with MRSA in conjunction with adoption of daily chlorhexidine bathing in ICUs is associated with increased MRSA acquisition among ICU patients or increased MRSA contamination of ICU fomites. Although underpowered, our findings suggest this strategy, which has the potential to reduce costs and improve patient safety, should be assessed in similar but larger studies.

Triggering interventions for influenza: the ALERT algorithm.

BACKGROUND: Early, accurate predictions of the onset of influenza season enable targeted implementation of control efforts. Our objective was to develop a tool to assist public health practitioners, researchers, and clinicians in defining the community-level onset of seasonal influenza epidemics. METHODS: Using recent surveillance data on virologically confirmed infections of influenza, we developed the Above Local Elevated Respiratory Illness Threshold (ALERT) algorithm, a method to identify the period of highest seasonal influenza activity. We used data from 2 large hospitals that serve Baltimore, Maryland and Denver, Colorado, and the surrounding geographic areas. The data used by ALERT are routinely collected surveillance data: weekly case counts of laboratory-confirmed influenza A virus. The main outcome is the percentage of prospective seasonal influenza cases identified by the ALERT algorithm. RESULTS: When ALERT thresholds designed to capture 90% of all cases were applied prospectively to the 2011-2012 and 2012-2013 influenza seasons in both hospitals, 71%-91% of all reported cases fell within the ALERT period. CONCLUSIONS: The ALERT algorithm provides a simple, robust, and accurate metric for determining the onset of elevated influenza activity at the community level. This new algorithm provides valuable information that can impact infection prevention recommendations, public health practice, and healthcare delivery.