Influence of Antibiotic Exposure Intensity on the Risk of Clostridioides difficile Infection.

BACKGROUND: Antibiotics are a strong risk factor for Clostridioides difficile infection (CDI), and CDI incidence is often measured as an important outcome metric for antimicrobial stewardship interventions aiming to reduce antibiotic use. However, risk of CDI from antibiotics varies by agent and dependent on the intensity (i.e., spectrum and duration) of antibiotic therapy. Thus, the impact of stewardship interventions on CDI incidence is variable, and understanding this risk requires a more granular measure of intensity of therapy than traditionally used measures like days of therapy (DOT). METHODS: We performed a retrospective cohort study to measure the independent association between intensity of antibiotic therapy, as measured by the antibiotic spectrum index (ASI), and hospital-associated CDI (HA-CDI) at a large academic medical center between January 2018 and March 2020. We constructed a marginal Poisson regression model to generate adjusted relative risks for a unit increase in ASI per antibiotic day. RESULTS: We included 35,457 inpatient encounters in our cohort. Sixty-eight percent of patients received at least one antibiotic. We identified 128 HA-CDI cases, which corresponds to an incidence rate of 4.1 cases per 10,000 patient-days. After adjusting for known confounders, each additional unit increase in ASI per antibiotic day is associated with 1.09 times the risk of HA-CDI (Relative Risk = 1.09, 95% Confidence Interval: 1.06 to 1.13). CONCLUSIONS: ASI was strongly associated with HA-CDI and could be a useful tool in evaluating the impact of antibiotic stewardship on HA-CDI rates, providing more granular information than the more commonly used days of therapy.

Impact of Shifting University Policies During the COVID-19 Pandemic on Self-Reported Employee Social Networks.

Objectives: To ascertain if faculty and staff were the link between the two COVID-19 outbreaks in a rural university county, and if the local university's COVID-19 policies affected contact rates of their employees across all its campuses. Methods: We conducted two anonymous, voluntary online surveys for faculty and staff of a PAC-12 university on their contact patterns both within and outside the university during the COVID-19 pandemic. One was asked when classes were virtual, and another when classes were in-person but masking. Participants were asked about the individuals they encountered, the type and location of the interactions, what COVID-19 precautions were taken - if any, as well as general questions about their location and COVID-19. Results: We received 271 responses from the first survey and 124 responses from the second. The first survey had a median of 3 contacts/respondent, with the second having 7 contacts/respondent (p<0.001). During the first survey, most contacts were family contacts (Spouse, Children), with the second survey period having Strangers and Students having the most contact (p<0.001). Over 50% of the first survey contacts happened at their home, while the second survey had 40% at work and 35% at home. Both respondents and contacts masked 42% and 46% of the time for the two surveys respectively (p<0.01). Conclusion: For future pandemics, it would be wise to take employees into account when trying to plan for the safety of university students, employees, and surrounding communities. The main places to be aware of and potentially push infectious disease precautions would be on campus, especially confined spaces like offices or small classrooms, and the home, as these tend to be the largest areas of non-masked close contact.

Estimating SARS-CoV-2 transmission parameters between coinciding outbreaks in a university population and the surrounding community.

Prior studies suggest that population heterogeneity in SARS-CoV-2 (COVID-19) transmission plays an important role in epidemic dynamics. During the fall of 2020, many US universities and the surrounding communities experienced an increase in reported incidence of SARS-CoV-2 infections, with a high disease burden among students. We explore the transmission dynamics of an outbreak of SARS-CoV-2 among university students, how it impacted the non-student population via cross-transmission, and how it could influence pandemic planning and response. Using surveillance data of reported SARS-CoV-2 cases, we developed a two-population SEIR model to estimate transmission parameters and evaluate how these subpopulations interacted during the 2020 Fall semester. We estimated the transmission rate among the university students (ßU) and community residents (ßC), as well as the rate of cross-transmission between the two subpopulations (ßM) using particle Markov Chain Monte Carlo (pMCMC) simulation-based methods. We found that both populations were more likely to interact with others in their population and that cross-transmission was minimal. The cross-transmission estimate (ßM) was considerably smaller [0.04 × 10-5 (95% CI: 0.00 × 10-5, 0.15 × 10-5)] compared to the community estimate (ßC) at 2.09 × 10-5 (95% CI: 1.12 × 10-5, 2.90 × 10-5) and university estimate (ßU) at 27.92 × 10-5 (95% CI: 19.97 × 10-5, 39.15 × 10-5). The higher within population transmission rates among the university and the community (698 and 52 times higher, respectively) when compared to the cross-transmission rate, suggests that these two populations did not transmit between each other heavily, despite their geographic overlap. During the first wave of the pandemic, two distinct epidemics occurred among two subpopulations within a relatively small US county population where university students accounted for roughly 41% of the total population. Transmission parameter estimates varied substantially with minimal or no cross-transmission between the subpopulations. Assumptions that county-level and other small populations are well-mixed during a respiratory viral pandemic should be reconsidered. More granular models reflecting overlapping subpopulations may assist with better-targeted interventions for local public health and healthcare facilities.

Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling.

Studies designed to estimate the effect of an action in a randomized or observational setting often do not represent a random sample of the desired target population. Instead, estimates from that study can be transported to the target population. However, transportability methods generally rely on a positivity assumption, such that all relevant covariate patterns in the target population are also observed in the study sample. Strict eligibility criteria, particularly in the context of randomized trials, may lead to violations of this assumption. Two common approaches to address positivity violations are restricting the target population and restricting the relevant covariate set. As neither of these restrictions is ideal, we instead propose a synthesis of statistical and simulation models to address positivity violations. We propose corresponding g-computation and inverse probability weighting estimators. The restriction and synthesis approaches to addressing positivity violations are contrasted with a simulation experiment and an illustrative example in the context of sexually transmitted infection testing uptake. In both cases, the proposed synthesis approach accurately addressed the original research question when paired with a thoughtfully selected simulation model. Neither of the restriction approaches was able to accurately address the motivating question. As public health decisions must often be made with imperfect target population information, model synthesis is a viable approach given a combination of empirical data and external information based on the best available knowledge.

Estimate of undetected severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in acute-care hospital settings using an individual-based microsimulation model.

OBJECTIVE: Current guidance states that asymptomatic screening for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) prior to admission to an acute-care setting is at the facility's discretion. This study's objective was to estimate the number of undetected cases of SARS-CoV-2 admitted as inpatients under 4 testing approaches and varying assumptions. DESIGN AND SETTING: Individual-based microsimulation of 104 North Carolina acute-care hospitals. PATIENTS: All simulated inpatient admissions to acute-care hospitals from December 15, 2021, to January 13, 2022 [ie, during the SARS-COV-2 ο (omicron) variant surge]. INTERVENTIONS: We simulated (1) only testing symptomatic patients, (2) 1-stage antigen testing with no confirmatory polymerase chain reaction (PCR) test, (3) 1-stage antigen testing with a confirmatory PCR for negative results, and (4) serial antigen screening (ie, repeat antigen test 2 days after a negative result). RESULTS: Over 1 month, there were 77,980 admissions: 13.7% for COVID-19, 4.3% with but not for COVID-19, and 82.0% for non-COVID-19 indications without current infection. Without asymptomatic screening, 1,089 (credible interval [CI], 946-1,253) total SARS-CoV-2 infections (7.72%) went undetected. With 1-stage antigen screening, 734 (CI, 638-845) asymptomatic infections (67.4%) were detected, with 1,277 false positives. With combined antigen and PCR screening, 1,007 (CI, 875-1,159) asymptomatic infections (92.5%) were detected, with 5,578 false positives. A serial antigen testing policy detected 973 (CI, 845-1,120) asymptomatic infections (89.4%), with 2,529 false positives. CONCLUSIONS: Serial antigen testing identified >85% of asymptomatic infections and resulted in fewer false positives with less cost per identified infection compared to combined antigen plus PCR testing.

Household Transmission of SARS-CoV-2 from Humans to Pets, Washington and Idaho, USA.

SARS-CoV-2 likely emerged from an animal reservoir. However, the frequency of and risk factors for interspecies transmission remain unclear. We conducted a community-based study in Idaho, USA, of pets in households that had >1 confirmed SARS-CoV-2 infections in humans. Among 119 dogs and 57 cats, clinical signs consistent with SARS-CoV-2 were reported for 20 dogs (21%) and 19 cats (39%). Of 81 dogs and 32 cats sampled, 40% of dogs and 43% of cats were seropositive, and 5% of dogs and 8% of cats were PCR positive. This discordance might be caused by delays in sampling. Respondents commonly reported close human‒animal contact and willingness to take measures to prevent transmission to their pets. Reported preventive measures showed a slightly protective but nonsignificant trend for both illness and seropositivity in pets. Sharing of beds and bowls had slight harmful effects, reaching statistical significance for sharing bowls and seropositivity.

Sequence Similarity Network Analysis Provides Insight into the Temporal and Geographical Distribution of Mutations in SARS-CoV-2 Spike Protein.

Severe acute respiratory syndrome-related coronavirus (SARS-CoV-2), which still infects hundreds of thousands of people globally each day despite various countermeasures, has been mutating rapidly. Mutations in the spike (S) protein seem to play a vital role in viral stability, transmission, and adaptability. Therefore, to control the spread of the virus, it is important to gain insight into the evolution and transmission of the S protein. This study deals with the temporal and geographical distribution of mutant S proteins from sequences gathered across the US over a period of 19 months in 2020 and 2021. The S protein sequences are studied using two approaches: (i) multiple sequence alignment is used to identify prominent mutations and highly mutable regions and (ii) sequence similarity networks are subsequently employed to gain further insight and study mutation profiles of concerning variants across the defined time periods and states. Additionally, we tracked the variants using visualizations on geographical maps. The visualizations produced using the Directed Weighted All Nearest Neighbors (DiWANN) networks and maps provided insights into the transmission of the virus that reflect well the statistics reported for the time periods studied. We found that the networks created using DiWANN are superior to commonly used approximate distance networks created using BLAST bitscores. The study offers a richer computational approach to analyze the transmission profile of the prominent S protein mutations in SARS-CoV-2 and can be extended to other proteins and viruses.

Use of Contact Networks to Estimate Potential Pathogen Risk Exposure in Hospitals.

Importance: Person-to-person contact is important for the transmission of health care-associated pathogens. Quantifying these contact patterns is crucial for modeling disease transmission and understanding routes of potential transmission. Objective: To generate and analyze the mixing matrices of hospital patients based on their contacts within hospital units. Design, Setting, and Participants: In this quality improvement study, mixing matrices were created using a weighted contact network of connected hospital patients, in which contact was defined as occupying the same hospital unit for 1 day. Participants included hospitalized patients at 299 hospital units in 24 hospitals in the Southeastern United States that were part of the Duke Antimicrobial Stewardship Outreach Network between January 2015 and December 2017. Analysis was conducted between October 2021 and February 2022. Main Outcomes and Measures: The mixing matrices of patients for each hospital unit were assessed using age, Elixhauser Score, and a measure of antibiotic exposure. Results: Among 1 549 413 hospitalized patients (median [IQR] age, 44 [26-63] years; 883 580 [56.3%] women) in 299 hospital units, some units had highly similar patterns across multiple hospitals, although the number of patients varied to a great extent. For most of the adult inpatient units, frequent mixing was observed for older adult groups, while outpatient units (eg, emergency departments and behavioral health units) showed mixing between different age groups. Most units mixing patterns followed the marginal distribution of age; however, patients aged 90 years or older with longer lengths of stay created a secondary peak in some medical wards. From the mixing matrices by Elixhauser Score, mixing between patients with relatively higher comorbidity index was observed in intensive care units. Mixing matrices by antibiotic spectrum, a 4-point scale based on priority for antibiotic stewardship programs, resulted in 6 major distinct patterns owing to the variation of the type of antibiotics used in different units, namely those dominated by a single antibiotic spectrum (narrow, broad, or extended), 1 pattern spanning all antibiotic spectrum types and 2 forms of narrow- and extended-spectrum dominant exposure patterns (an emergency room where patients were exposed to one type of antibiotic or the other and a pediatric ward where patients were exposed to both types). Conclusions and Relevance: This quality improvement study found that the mixing patterns of patients both within and between hospitals followed broadly expected patterns, although with a considerable amount of heterogeneity. These patterns could be used to inform mathematical models of health care-associated infections, assess the appropriateness of both models and policies for smaller community hospitals, and provide baseline information for the design of interventions that rely on altering patient contact patterns, such as practices for transferring patients within hospitals.

Longitudinal observation of meticillin-resistant Staphylococcus pseudintermedius pulsotypes in six veterinary hospitals in the north-western United States.

Background: Meticillin-resistant Staphylococcus pseudintermedius (MRSP) infections in companion animals are increasing and are difficult to treat. Environmental contamination with MRSP in small animal primary care hospitals may pose an exposure risk to animal patients. Methods: This longitudinal study assessed the genotypic relationships of MRSP isolated from 39 environmental samples collected from six private small animal primary care hospitals, in the north-eastern United States, between August 2018 and April 2019. Results: Of the 39 bacterial isolates, 18 unique pulsotypes were identified based on pulsed-field gel electrophoresis, including six clusters of two or more indistinguishable isolates. Single pulsotypes were frequently detected from multiple hand-contact and animal-contact surfaces within a hospital during a single sampling event, but detection of a single pulsotype within the same hospital on subsequent visits was infrequent. However, one pulsotype was recovered from three separate hospitals, which suggests that either MRSP transmission between hospitals may have occurred via people, animals, or fomites or that there was a dominant community strain. Conclusions: Single strains of MRSP were isolated from various hand-contact and animal-contact surfaces within hospitals, indicating the important role of humans, animals and the environment in MRSP transmission. Additionally, the detection of a single strain between hospitals and over time suggests that either MRSP transmission between hospitals may have occurred via people, animals or fomites or that there was a dominant community strain.

Examining the impact of ICU population interaction structure on modeled colonization dynamics of Staphylococcus aureus.

BACKGROUND: Complex transmission models of healthcare-associated infections provide insight for hospital epidemiology and infection control efforts, but they are difficult to implement and come at high computational costs. Structuring more simplified models to incorporate the heterogeneity of the intensive care unit (ICU) patient-provider interactions, we explore how methicillin-resistant Staphylococcus aureus (MRSA) dynamics and acquisitions may be better represented and approximated. METHODS: Using a stochastic compartmental model of an 18-bed ICU, we compared the rates of MRSA acquisition across three ICU population interaction structures: a model with nurses and physicians as a single staff type (SST), a model with separate staff types for nurses and physicians (Nurse-MD model), and a Metapopulation model where each nurse was assigned a group of patients. The proportion of time spent with the assigned patient group (γ) within the Metapopulation model was also varied. RESULTS: The SST, Nurse-MD, and Metapopulation models had a mean of 40.6, 32.2 and 19.6 annual MRSA acquisitions respectively. All models were sensitive to the same parameters in the same direction, although the Metapopulation model was less sensitive. The number of acquisitions varied non-linearly by values of γ, with values below 0.40 resembling the Nurse-MD model, while values above that converged toward the Metapopulation structure. DISCUSSION: Inclusion of complex population interactions within a modeled hospital ICU has considerable impact on model results, with the SST model having more than double the acquisition rate of the more structured metapopulation model. While the direction of parameter sensitivity remained the same, the magnitude of these differences varied, producing different colonization rates across relatively similar populations. The non-linearity of the model's response to differing values of a parameter gamma (γ) suggests simple model approximations are appropriate in only a narrow space of relatively dispersed nursing assignments. CONCLUSION: Simplifying assumptions around how a hospital population is modeled, especially assuming random mixing, may overestimate infection rates and the impact of interventions. In many, if not most, cases more complex models that represent population mixing with higher granularity are justified.

How Drivers of Seasonality in Respiratory Infections May Impact Vaccine Strategy: A Case Study in How Coronavirus Disease 2019 (COVID-19) May Help Us Solve One of Influenza's Biggest Challenges.

Vaccines against seasonal infections like influenza offer a recurring testbed, encompassing challenges in design, implementation, and uptake to combat a both familiar and ever-shifting threat. One of the pervading mysteries of influenza epidemiology is what causes the distinctive seasonal outbreak pattern. Proposed theories each suggest different paths forward in being able to tailor precision vaccines and/or deploy them most effectively. One of the greatest challenges in contrasting and supporting these theories is, of course, that there is no means by which to actually test them. In this communication we revisit theories and explore how the ongoing coronavirus disease 2019 (COVID-19) pandemic might provide a unique opportunity to better understand the global circulation of respiratory infections. We discuss how vaccine strategies may be targeted and improved by both isolating drivers and understanding the immunological consequences of seasonality, and how these insights about influenza vaccines may generalize to vaccines for other seasonal respiratory infections.

Carceral Amplification of COVID-19: Impacts for Community, Corrections Officer, and Incarcerated Population Risks.

COVID-19 is challenging many societal institutions, including our criminal justice systems. Some have proposed or enacted (e.g., the State of New Jersey) reductions in the jail and/or prison populations. We present a mathematical model to explore the epidemiologic impact of such interventions in jails and contrast them with the consequences of maintaining unaltered practices. We consider infection risk and likely in-custody deaths, and estimate how within-jail dynamics lead to spill-over risks, not only affecting incarcerated people but increasing exposure, infection, and death rates for both corrections officers and the broader community beyond the justice system. We show that, given a typical jail-community dynamic, operating in a business-as-usual way results in substantial, rapid, and ongoing loss of life. Our results are consistent with the hypothesis that large-scale reductions in arrest and speeding of releases are likely to save the lives of incarcerated people, jail staff, and the wider community.

Household transmission of SARS-CoV-2 from humans to pets in Washington and Idaho: burden and risk factors.

SARS-CoV-2 is believed to have emerged from an animal reservoir; however, the frequency of and risk factors for inter-species transmission remain unclear. We carried out a community-based study of pets in households with one or more confirmed SARS-CoV-2 infection in humans. Among 119 dogs and 57 cats with completed surveys, clinical signs consistent with SARS-CoV-2 were reported in 20 dogs (21%) and 19 cats (39%). Out of 81 dogs and 32 cats sampled for testing, 40% of dogs and 43% of cats were seropositive, and 5% of dogs and 8% of cats were PCR positive; this discordance may be due to delays in sampling. Respondents commonly reported close human-animal contact and willingness to take measures to prevent transmission to their pets. Reported preventative measures showed a slightly protective trend for both illness and seropositivity in pets, while sharing of beds and bowls had slight harmful effects.

Coronavirus disease 2019 (COVID-19) research agenda for healthcare epidemiology.

This SHEA white paper identifies knowledge gaps and challenges in healthcare epidemiology research related to coronavirus disease 2019 (COVID-19) with a focus on core principles of healthcare epidemiology. These gaps, revealed during the worst phases of the COVID-19 pandemic, are described in 10 sections: epidemiology, outbreak investigation, surveillance, isolation precaution practices, personal protective equipment (PPE), environmental contamination and disinfection, drug and supply shortages, antimicrobial stewardship, healthcare personnel (HCP) occupational safety, and return to work policies. Each section highlights three critical healthcare epidemiology research questions with detailed description provided in supplementary materials. This research agenda calls for translational studies from laboratory-based basic science research to well-designed, large-scale studies and health outcomes research. Research gaps and challenges related to nursing homes and social disparities are included. Collaborations across various disciplines, expertise and across diverse geographic locations will be critical.

Excess Risk of COVID-19 to University Populations Resulting from In-Person Sporting Events.

BACKGROUND: One of the consequences of COVID-19 has been the cancelation of collegiate sporting events. We explore the impact of sports on COVID-19 transmission on a college campus. METHODS: Using a compartmental model representing the university, we model the impact of influxes of 10,000 visitors attending events and ancillary activities (dining out, visiting family, shopping, etc.) on 20,000 students. We vary the extent visitors interact with the campus, the number of infectious visitors, and the extent to which the campus has controlled COVID-19 absent events. We also conduct a global sensitivity analysis. RESULTS: Events caused an increase in the number of cases ranging from a 25% increase when the campus already had an uncontrolled COVID-19 outbreak and visitors had a low prevalence of COVID-19 and mixed lightly with the campus community to an 822% increase where the campus had controlled their COVID-19 outbreak and visitors had both a high prevalence of COVID-19 and mixed heavily with the campus community. The model was insensitive to parameter uncertainty, save for the duration a symptomatic individual was infectious. CONCLUSION: Sporting events represent a threat to the health of the campus community. This is the case even in circumstances where COVID-19 seems controlled both on-campus and among the general population.

Estimated Methicillin-Resistant Staphylococcus aureus Decolonization in Intensive Care Units Associated With Single-Application Chlorhexidine Gluconate or Mupirocin.

Importance: Chlorhexidine gluconate (CHG) and mupirocin are widely used to decolonize patients with methicillin-resistant Staphylococcus aureus (MRSA) and reduce risks associated with infection in hospitalized populations. Quantifying the association of an application of CHG alone or in combination with mupirocin with risk of MRSA infection is important for studies evaluating alternative decolonization strategies or schedules and for identifying whether there is room for improved decolonizing agents. Objective: To estimate the proportion of patients with MRSA decolonized per application of CHG and mupirocin from existing population-level studies. Design, Setting, and Participants: A stochastic mathematical model of an 18-bed intensive care unit (ICU) in an academic medical center operating over 1 year was used to estimate parameters for the proportion of simulated patients with MRSA decolonized per application of CHG and mupirocin. The model was conducted using approximate bayesian computation with data from an existing meta-analysis of studies conducted from February 2005 through January 2015. Data were analyzed from January 2018 through November 2019. Exposure: A universal decolonization protocol for colonized patients in the ICU using CHG or CHG and mupirocin in combination was simulated. Main Outcomes and Measures: The proportion of patients with MRSA decolonized per application of CHG and mupirocin was estimated. Results: The estimated proportion of patients with MRSA decolonized per application of CHG was 0.15 (95% credible interval, 0.01-0.42), and the estimated proportion per application of mupirocin in conjunction with CHG was 0.15 (95% credible interval, 0.01-0.54). A lag in colonization detection was associated with decreases in the CHG estimate (0.11; 95% credible interval, 0.01-0.30) and mupirocin estimate (0.10; 95% credible interval, 0.00-0.34), which were sensitive to the value of the modeled contact rate between nurses and patients. A 1% increase in the value of this parameter was associated with a 0.73% increase in the estimated combined outcomes associated with CHG and mupirocin (95% CI: 0.71, 0.75). Gaps longer than 24 hours in the administration of decolonizing agents were associated with a decrease of within-ICU MRSA transmission. Compared with a mean (SD) of 1.23 (0.27) acquisitions per 1000 patient-days in scenarios with no decolonizing bathing, a bathing protocol administering CHG and mupirocin every 120 hours was associated with a mean (SD) acquisition rate of 1.03 (0.24) acquisitions per 1000 patient days, a 16.3% decrease (95% CI, 14.7%-18.0%; P > .001). Conclusions and Relevance: These findings suggest that there may be room for significant improvement in anti-MRSA disinfectants, including the compounds themselves and their delivery mechanisms. Despite the decolonization estimates found in this study, these agents are associated with robust outcomes after delays in administration, which may help in alleviating concerns over patient comfort and toxic effects.

Carriage of antimicrobial-resistant bacteria in a high-density informal settlement in Kenya is associated with environmental risk-factors.

BACKGROUND: The relationship between antibiotic use and antimicrobial resistance varies with cultural, socio-economic, and environmental factors. We examined these relationships in Kibera, an informal settlement in Nairobi-Kenya, characterized by high population density, high burden of respiratory disease and diarrhea. METHODS: Two-hundred households were enrolled in a 5-month longitudinal study. One adult (≥ 18 years) and one child (≤ 5 years) participated per household. Biweekly interviews (n = 1516) that included questions on water, sanitation, hygiene, and antibiotic use in the previous two weeks were conducted, and 2341 stool, 2843 hand swabs and 1490 drinking water samples collected. Presumptive E. coli (n = 34,042) were isolated and tested for susceptibility to nine antibiotics. RESULTS: Eighty percent of presumptive E. coli were resistant to ≥ 3 antibiotic classes. Stool isolates were resistant to trimethoprim (mean: 81%), sulfamethoxazole (80%), ampicillin (68%), streptomycin (60%) and tetracycline (55%). Ninety-seven households reported using an antibiotic in at least one visit over the study period for a total of 144 episodes and 190 antibiotic doses. Enrolled children had five times the number of episodes reported by enrolled adults (96 vs. 19). Multivariable linear mixed-effects models indicated that children eating soil from the household yard and the presence of informal hand-washing stations were associated with increased numbers of antimicrobial-resistant bacteria (counts increasing by 0·27-0·80 log10 and 0·22-0·51 log10 respectively, depending on the antibiotic tested). Rainy conditions were associated with reduced carriage of antimicrobial-resistant bacteria (1·19 to 3·26 log10 depending on the antibiotic tested). CONCLUSIONS: Antibiotic use provided little explanatory power for the prevalence of antimicrobial resistance. Transmission of resistant bacteria in this setting through unsanitary living conditions likely overwhelms incremental changes in antibiotic use. Under such circumstances, sanitation, hygiene, and disease transmission are the limiting factors for reducing the prevalence of resistant bacteria.

Prevalence of methicillin-resistant Staphylococcus pseudintermedius on hand-contact and animal-contact surfaces in companion animal community hospitals.

Methicillin-resistant Staphylococcus pseudintermedius (MRSP) is an important companion animal pathogen, but few published studies have evaluated its epidemiology in primary care settings. This study determined MRSP prevalence on hand- and animal-contact surfaces in 11 small animal primary care hospitals in Washington and Idaho, USA. Overall, MRSP was isolated from at least 1 sample from 7 of 11 hospitals (64%) and from 36 of 374 total samples (10%) with no difference in prevalence between hand- and animal-contact surfaces (P = 0.51). Strain typing by pulsed-field gel electrophoresis indicated high within-hospital similarity of MRSP strains, but minimal similarity between strains from different hospitals. Indistinguishable MRSP strains were present on handand animal-contact surfaces within individual hospitals. A questionnaire was administered to a representative from each hospital. Respondents reported that animal-contact surfaces were cleaned and disinfected more frequently than hand-contact surfaces (P < 0.001). Improving hand hygiene and disinfection of hand-contact surfaces may decrease exposure of veterinary patients to MSRP.

Prévalence de Staphylococcus pseudintermedius résistant à la méthicilline sur des surfaces en contact avec les mains et des surfaces en contact avec les animaux dans des hôpitaux de première ligne pour animaux de compagnie. Staphylococcus pseudintermedius résistant à la méthicilline (MRSP) est un agent pathogène important chez les animaux de compagnie, mais peu d'études publiées ont évalué son épidémiologie dans les sites de soins de première ligne. Dans la présente étude on détermina la prévalence de MRSP sur les surfaces de contact avec les mains et les surfaces de contact avec les animaux dans 11 hôpitaux de première ligne pour animaux de compagnie dans les états de Washington et de l'Idaho, USA. De manière globale, le MRSP fut isolé à partir d'au moins un échantillon dans 7 des 11 hôpitaux (64 %) et de 36 des 374 échantillons (10 %) sans noter de différence dans la prévalence entre les contacts main-surface ou animal-surface (P = 0,51). Le typage des souches par électrophorèse en champs pulsés indiqua une similarité intra-hôpital élevée des souches de MRSP, mais une similarité minimale entre les souches provenant d'hôpitaux différents. Des souches indistinguables de MRSP étaient présentes sur les surfaces de contact avec les mains et les animaux dans un même hôpital. Un questionnaire fut soumis à un représentant de chaque hôpital. Les répondants rapportèrent que les surfaces de contact avec l'animal étaient nettoyées et désinfectées plus fréquemment que les surfaces de contact avec les mains (P < 0,001). Une amélioration de l'hygiène des mains et de la désinfection des surfaces en contacts avec les mains pourraient diminuer l'exposition de patients vétérinaires au MSRP.(Traduit par Dr Serge Messier).

Assessing the Potential Impact of a Long-Acting SkinDisinfectant in the Prevention of Methicillin-Resistant Staphylococcus aureus Transmission.

Healthcare-associated transmission of methicillin-resistant Staphylococcus aureus (MRSA)remains a persistent problem. The use of chlorhexidine gluconate (CHG) as a means of decolonizingpatients, either through targeted decolonization or daily bathing, is frequently used to supplementother interventions. We explore the potential of a long-acting disinfectant with a persistent effect,immediate decolonizing action in the prevention of MRSA acquisition, and clinical illness andmortality in an 18-bed intensive care unit, based on a previous model. A scenario with nointervention is compared to CHG bathing, which decolonizes patients but provides no additionalprotection, and a hypothetical treatment that both decolonizes them and provides protection fromsubsequent colonization. The duration and effectiveness of this protection is varied to fully explorethe potential utility of such a treatment. Increasing the effectiveness of the decolonizing agentreduces colonization, with a 10% increase resulting in a colonization rate ratio (RR) of 0.89 (95% CI:0.89,0.90). Increasing the duration of protection results in a much more modest reduction, with a 12-hour increase in protection resulting in an RR of 0.99 (95% CI: 0.99, 0.99). There is little evidence ofsynergy between the two.