This study estimates the incidence of symptomatic COVID-19 cases, both documented and undocumented, among U.S. Veterans across demographic groups from the beginning of the pandemic to the end of the public health emergency on May 11, 2023. By analyzing a cohort of Veterans alive as of March 1, 2020, we extended a mortality-based estimation approach to measure COVID-19 incidence. We relaxed the assumptions of a constant infection fatality rate (IFR) over time and across age groups and broadened the model from considering only excess respiratory deaths to including excess all-cause deaths. Descriptive analyses were performed to understand differential ascertainment biases among demographic groups. Resulting estimates suggested a significantly higher number of COVID-19 cases among Veterans than those documented in the electronic health record. We also identified varying biases among different demographic groups. These estimates offer a clearer view of COVID-19's impact on Veterans, accounting for missed cases among those who sought care outside of the VA. Differences between documented and estimated cases were substantial. Policymakers should recognize that actual numbers are likely much higher than documented and that documented rates may not be directly comparable across populations or time periods.

Introduction Little is known regarding the impact of mobile vaccine clinics (MVCs) on COVID-19 vaccination rates in the USA. This study aimed to evaluate the effectiveness of MVCs in increasing COVID-19 vaccination uptake in the state of Utah.Methods In this longitudinal observational study, we collected and analysed data on MVCs and COVID-19 vaccinations in Utah from 1 April 2021 to 31 March 2022. The primary exposure was the weekly number of MVC days in host ZIP codes (where MVCs operated). The secondary exposure was the weekly number of MVC days in nearby ZIP codes. The outcome was the weekly first-dose vaccination rate. A mixed-effects zero-inflated beta regression model was used. Confounding variables adjusted in the model included the Health Accessibility Barriers Index, the Resource-Constrained Health System Index, the Social Vulnerability Index (SVI), vaccine hesitancy and prior vaccination rates.Results MVCs were deployed for 2760 days (8.5 MVC days per 10 000 residents). MVC density was higher in areas with high proportions of Hispanic populations (11.7 days per 10 000 residents), urban areas (9.0 days per 100 000 residents), and areas with very high SVI (14.9 days per 10 000 residents). Each additional MVC day in a given week reduced the odds of no vaccination in that week by 79.5% (OR=0.205, 95% CI 0.064 to 0.659) in host ZIP codes and by 21.1% (OR=0.789, 95% CI 0.732 to 0.849) in nearby ZIP codes. For ZIP codes with vaccinations, each additional MVC day increased the odds of weekly vaccination rates by 1.6% (OR=1.016, 95% CI 1.001 to 1.032) and by 0.6% (OR=1.006, 95% CI 1.003 to 1.009) in nearby ZIP codes.Conclusions MVCs increased COVID-19 vaccination uptake on both host and nearby ZIP codes. Policymakers can leverage these findings to use MVCs as a promising strategy to improve vaccine coverage for future pandemic responses or other vaccination programmes.

ABSTRACT Since the COVID-19 pandemic, forecasting hubs and non-traditional respiratory disease surveillance streams have become increasingly common. However, many forecasting approaches assume that relationships between surveillance predictors and disease outcomes remain stable over time and that incorporating additional historical data will improve forecast performance. To evaluate these assumptions in a real-world setting, we developed and evaluated forecasts of SARS-CoV-2 and influenza hospitalizations in Utah using syndromic surveillance, test positivity, and wastewater data. Rather than identifying a single, best-performing model, we examined whether relationships between surveillance predictors and hospitalization outcomes remained stable across seasons and whether longer historical training periods consistently improved forecast accuracy. Relationships between surveillance predictors and hospitalizations varied substantially by pathogen and season. Analyses using pooled data across multiple years suggested strong positive correlations between predictors and outcomes, but these aggregated patterns often obscured weak or negative correlations observed during SARS-CoV-2 variant waves and influenza seasons. Forecast performance similarly varied over time. Models that performed well during some seasons, transmission phases, or under certain training strategies frequently performed worse than benchmark models in others. Training on additional historical data generally reduced forecast accuracy, though this varied by disease and transmission phase. Forecasting groups should prioritize continual evaluation of surveillance predictors, adaptive strategies, and diverse ensembles, rather than relying on a single model, data stream, or historical training framework each year. AUTHOR SUMMARY Respiratory disease forecasting hubs and novel data streams have become integral parts of infectious disease surveillance and public health decision-making since the COVID-19 pandemic. Many forecasting groups assume that adding more historical data will improve model performance and that relationships between surveillance predictors, such as emergency department visits or wastewater, and hospitalizations will remain stable over time. We evaluated these assumptions using forecasts of SARS-CoV-2 and influenza hospitalizations in Utah. We found that relationships between surveillance predictors and hospitalizations varied across SARS-CoV-2 variants, influenza seasons, and periods of increasing and decreasing transmission. Forecast performance also varied considerably, with models that performed well in some seasons often performing poorly in others. Public health groups should continually evaluate the utility of surveillance predictors in real-time and prioritize adaptable, diverse modeling approaches.

Dental students and practitioners may have an increased risk of COVID-19 infection due to frequent aerosol-generating procedures (AGP) and close patient contact. We examined the role of vaccination status, work role, and AGP frequency on positive SARS-CoV-2 PCR surveillance test using a Cox proportional hazards regression and weighted for dropout. A total of 410 dental health workers (200 students, 104 faculty, and 106 staff) had 8,270 screening tests performed between May 2020 and February 2022, with 158 positive tests; 60 (38%) occurred in January 2022. Omicron had a significant impact on vaccination effectiveness. Vaccine effectiveness within < 4 months was 91% (HR: 0.09,95% CI: 0.02-0.40) prior to Omicron, which decreased after its emergence. Work role was not associated with risk of positive test. Reported AGP frequency was also not associated with positive test risk; however, these analyses were limited to a subset of participants and should be considered exploratory. More than a third of all positive tests occurred during one month of Omicron. We found a high vaccine effectiveness prior to the Omicron surge, which decreased after the emergence of Omicron. Our results support encouraging dental healthcare workers (DCWs) to maintain up-to-date vaccination and continue engaging in preventive measures.

IntroductionReliable assessment of disease state probabilities for an individual following a specific exposure event, such as an occupational exposure, is critical for managing isolation and quarantine and reducing onward transmission to susceptible individuals. Such assessments are particularly important for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), where infection, testing, and infectiousness vary substantially across individuals and time since exposure.MethodsWe present a method, accompanying software programs, and a publicly available website for calculating the probability that an individual is in each disease state immediately following an exposure event that may or may not have resulted in transmission of SARS-CoV-2. The framework integrates timing of exposure, test type and timing, and symptom status to estimate probabilities of latent infection, infectiousness, recovery, or no infection.ResultsWe illustrate the utility of this approach by calculating: (i) the time at which an exposed individual's risk of being infectious falls below an acceptable threshold; (ii) the benefit of a second test for asymptomatic individuals with an initial negative test; (iii) the value of polymerase chain reaction (PCR) and antigen testing for case counting; and (iv) the time at which the risk that an infected individual remains infectious becomes comparable to background population risk. The results demonstrate that test interpretation should not be done naively: a negative test may reflect absence of transmission, a false-negative result, rapid resolution of infection, or an unusually prolonged latent period, each with distinct implications for risk management.ConclusionsAccurate differentiation among possible disease states following exposure is essential for informed public health decision-making. Our software provides a rigorous, transparent means to assess and clearly communicate state probabilities, enabling more nuanced interpretation of test results and better-supported decisions regarding isolation, quarantine, and testing strategies.

BACKGROUND:The effectiveness of contact precautions (CP) and active surveillance (AS) for preventing methicillin-resistant Staphylococcus aureus (MRSA) in acute care remains uncertain. Some studies suggest CP reduces MRSA spread, while others report limited benefit. The COVID-19 pandemic disrupted MRSA prevention practices in the VA, creating an opportunity to assess their impact on MRSA healthcare-associated infections (HAIs). METHODS:We studied 121 VA acute care hospitals from July 2020-June 2022. Facility practices (AS, CP for colonized [CPC], CP for infected [CPI]) were assessed via national surveys. Patient-level data identified MRSA HAIs (incident cultures ≥3 days postadmission). Secondary outcomes included sterile-site infections and 30-day postdischarge cultures. Associations between practices and HAI rates were estimated using Poisson, negative binomial, and mixed-effects Poisson regression, adjusting for baseline MRSA burden, COVID-19 admissions, culturing intensity, and hospital characteristics. RESULTS:Among 905 164 admissions, 1708 incident MRSA cultures were identified. Many facilities suspended at least one prevention practice early in the pandemic, though most later reinstated them. In simpler models, discontinuation of AS, CPC, or CPI was associated with higher MRSA rates, but these associations were attenuated after adjustment for baseline burden. Mixed-effects models found no significant associations, and results were consistent across secondary outcomes. CONCLUSIONS:Discontinuation of MRSA prevention practices during the pandemic was not consistently linked to increased HAIs after accounting for baseline burden. Findings emphasize the role of facility-specific factors and modeling assumptions in evaluating infection control. Unmeasured pandemic-related practices (eg, masking, PPE use) likely also influenced transmission, highlighting the need for flexible, context-sensitive, evidence-based infection prevention policies.

Declining childhood vaccination rates have fueled a resurgence of measles in the United States. Surveillance systems may not accurately measure the true extent of outbreaks. As of May 2026, the largest ongoing measles outbreak in the United States originated along the Utah-Arizona border in a community with high vaccine exemption rates and limited engagement with healthcare systems, leading to incomplete testing and reporting. To quantify the true outbreak size, we used two independent approaches with complementary data sources: a phylodynamic analysis and an agent-based model. Both methods found significant underreporting, estimating the true outbreak size to be 3.1- to 4.8-fold larger than reported, with confirmed cases representing only 20.96%-32.5% total infections. These findings suggest that substantial underreporting of measles occurs, especially in tight knit communities. The use of complementary analytical approaches to evaluate completeness of reporting can reveal the extent of measles transmission and aid control efforts.

Background:Vancomycin-resistant Enterococcus (VRE) species are common healthcare-associated pathogens that cause difficult-to-treat infections. Whole genome sequencing of patients has revealed a substantial burden of patient-to-patient VRE transmission in hospitals, with patients in intensive care units (ICUs) at particularly high risk of acquisition. However, few studies adequately characterize the pathways of VRE transmission between patients in acute care settings-a necessary step to identify current gaps in infection prevention practices. By harnessing genomic clustering analyses of whole genome sequences of VRE isolates from patients, environmental surfaces, and healthcare providers (HCP) in ICUs, we aim to reconstruct indirect pathways of pathogen movement to identify patterns of VRE spread and opportunities for transmission prevention. Methods and Findings:We collected daily samples (N = 6848) from ICUs in two hospitals over 13 weeks from four main sampling sources: patients, HCP hands, patient rooms, and shared surfaces. Samples were cultured on selective media and sent for whole genome sequencing (WGS). We used genomic thresholds to identify clusters of related VRE isolates and distinguish unrelated isolates. VRE was detected in samples from 20 out of 322 unique occupant-stays (6.22%). VRE isolates were detected from all sampling sources except for shared surfaces. A total of 44 unique VRE isolates were identified, 43 Enterococcus faecium (VREfm) and one Enterococcus faecalis (VREf). Two distinct patterns of VREfm spread were observed: 1) an outbreak setting with observed patient-to-patient transmission and low VRE diversity, and 2) high VRE diversity and pathogen movement between occupant-stays facilitated by persistent HCP and environmental contamination, but no observed transmission events. VRE detection probabilities were not significantly different between occupant-stays in outbreak and non-outbreak settings (OR = 0.63, 95% CI (0.23, 1.83), p = 0.32). However, inclusion of VRE isolated from non-patient samples increased the number of occupant-stays with VRE detection from 6 to 20, a 3.3-fold increase, as compared to patient samples alone. Inclusion of non-patient samples also increased the number of VRE multi-isolate genomic clusters detected by 7-fold. Our findings are limited because sampling was primarily conducted in ICUs. Due to the combination of short ICU stay durations and imperfect test sensitivity, VRE transmission events may have been underdetected. Conclusions:Our findings characterize the complex nature of VRE transmission pathways in ICU settings. Even without an ongoing outbreak, we found substantial evidence of VRE movement between occupant-stays, facilitated by a combination of HCP hands and environmental surfaces. This study highlights the importance of environmental sampling for understanding VRE transmission potential, which is likely to be underestimated using patient sampling alone. We recommend that future studies incorporate follow-up sampling after discharge to better understand the true burden of transmission.

Background: Multidrug-resistant organisms (MDROs) are prevalent in skilled nursing facilities (SNFs), but patterns of pathogen movement in these facilities are not well understood. We used genomic surveillance to identify MDRO presence on environmental surfaces, focusing on shared mobile medical equipment (MME) and patient room surfaces, to assess contamination patterns in a skilled nursing facility setting. Methods: We conducted environmental microbiological sampling in an 18-bed floor of a community-based, ventilator-capable SNF over four consecutive days. We collected composite samples of patient room environments and five types of shared MME: glucometers, vital signs carts, shower chairs, shower beds, and patient lifts. The timing and location of each sampling event were recorded. 105 samples were collected, cultured on selective media (for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus species, extended-spectrum ?-lactamase producing Enterobacteriaceae, and multidrug-resistant Acinetobacter species), and presumptive MDRO isolates were MALDI-TOF confirmed and whole genome sequenced. We assessed pairwise genomic relatedness using split-kmer analysis for any MDRO species that was isolated at least twice. We established genomic clusters based on two criteria: the proportion of kmers that matched between isolates (< 0.9) and a single-nucleotide polymorphism (SNP) threshold for each MDRO species based on established literature (e.g., < 7 SNPs). Results: In the 105 samples, four MDROs were detected more than once: vancomycin-resistant Enterococcus faecium (VREfm; N=17), methicillin-resistant Staphylococcus aureus (MRSA; N=9), Klebsiella pneumoniae (KP; N=4), and Acinetobacter baumannii (AB; N=2). To date, MRSA isolates have not been whole genome sequenced and are thus excluded from our results. MDRO detection rates varied across species and sample locations (Table 1). To assess whether these detections indicated pathogen movement, we assessed genomic relatedness (Figure 1) and found: 12 out of 17 VREfm isolates belonged to three multi-isolate clusters of sizes ranging from two to seven isolates; three out of four KP isolates formed a single cluster; while the two AB isolates were unrelated. All four clusters that were detected in the study included isolates collected from shared MME. Three of the four clusters detected involved samples taken in more than one location within the ward, with the largest cluster involving VRE isolates collected from five unique patient rooms and three equipment types stored in a hallway (Figure 1). Conclusions: Our findings suggest that MME may be an important reservoir for MDROs and can facilitate pathogen movement between patient rooms in SNFs. Adequate cleaning of shared MME is necessary to address the risk of fomite-based

Importance:Prompt antimicrobial therapy is essential in sepsis, but accelerating antimicrobial administration may increase overtreatment. Objectives:To examine the extent of and factors associated with physician variation in time from emergency department (ED) presentation to antimicrobial administration (hereinafter termed door-to-antimicrobial time) for sepsis and to assess whether faster practice patterns are associated with overtreatment. Design, Setting, and Participants:This explanatory mixed-methods study linked a quantitative retrospective cohort (July 1, 2013, to January 31, 2017) involving 30-day patient follow-up with prospective qualitative physician interview data (May 17, 2022, to June 28, 2023) at 4 Utah EDs. Participants included ED attending physicians and their patients meeting sepsis criteria (including intravenous antimicrobial administration) before ED departure. Data analysis occurred from 2021 to 2025. Main Outcomes and Measures:Assessment for physician door-to-antimicrobial time variation used a likelihood ratio test comparing a linear mixed-effects model incorporating physician-level random intercepts and patient-level covariates with a model without physician random effects. Empirical best linear unbiased predictions of the physician random intercepts (termed physician-predicted mean door-to-antimicrobial times) quantified variation. The primary analysis used a joint mixed-effects shared parameter model to evaluate the association of physicians' door-to-antimicrobial practice patterns with their overtreatment rate (infection ruled out on final retrospective adjudication). Qualitative analysis of semistructured cognitive task analysis interviews compared ED physicians in the fastest and slowest door-to-antimicrobial time quartiles. Results:Quantitative analyses included 88 ED physicians (71 [80.7%] male; median age, 39 [IQR, 35-49] years) and 9810 patients with sepsis (median age, 63 [IQR, 48-75] years), of whom 4635 (50.5%) were female and 3540 (38.6%) received antimicrobials more than 3 hours after ED arrival. The median number of patient encounters per physician was 105 (IQR, 75-129). Physicians' door-to-antimicrobial time varied significantly (likehood ratio test P < .001), with average physician-level estimated mean door-to-antimicrobial time of 184 (95% estimation interval, 146-222) minutes for a typical patient, but was not associated with overtreatment (adjusted odds ratio, 0.98 [95% CI 0.94-1.02] per 10-minute increase in physician estimated mean door-to-antimicrobial time; P = .37). Among 18 physicians interviewed, physicians with faster door-to-antimicrobial times emphasized proactive, parallel task execution and care team coordination, while physicians with slower times described a more reactive and stepwise sepsis evaluation and treatment process. Conclusions and Relevance:In this mixed-methods study, ED physicians' antimicrobial administration time for sepsis varied significantly, but faster antimicrobial initiation practice patterns were not associated with overtreatment. Physicians with shorter door-to-antimicrobial times described a proactive, parallel processing approach to sepsis care.

Background:Mobile vaccine clinic (MVC) programs represent a significant public health investment, rigorous data on their health, economic, and equity impacts are needed to guide policy for future immunization efforts. We estimated the health and economic outcomes of the State of Utah's 1-year COVID-19 MVC program, stratified by Hispanic and non-Hispanic populations. Methods:We used a decision-analytic model combining a susceptible-infected-removed (SIR) model with a decision tree to simulate 3.23 million Utah residents over one year (April 1, 2021, to March 31, 2022). We compared an MVC program scenario with a no-MVC program scenario. Health outcomes included vaccinations, infections, hospitalizations, intensive care unit (ICU) admissions, and deaths. Economic outcomes included direct and total costs (in 2021 US dollars) and return on investment (ROI) from healthcare sector and societal perspectives. All outcomes were stratified by Hispanic and non-Hispanic populations. Findings:In this economic evaluation of 3.23 million Utah residents, the 1-year MVC program vaccinated 29,420 additional people, preventing an estimated 41,503 infections, 923 hospitalizations, 240 ICU admissions, and 253 deaths. The MVC program was cost-saving compared with no MVC program from both healthcare sector (net savings, $51.71 million) and societal (net savings, $71.30 million) perspectives. Every $1 invested in the MVC program yielded $9.70 in societal savings. Prevented adverse outcomes per 100,000 persons were 3.2-6.0 times higher in the Hispanic versus non-Hispanic population. Interpretation:The MVC program was a cost-saving and equity-enhancing public health strategy. These findings support investment in MVC programs for future vaccination campaigns. Funding:This study was funded by cooperative agreement CDC-RFA-FT-23-0069 from the CDC's Center for Forecasting and Outbreak Analytics.

Introduction: Local health departments (LHDs) play an essential role in providing COVID-19 vaccines to underserved populations in Utah. This study aimed to understand barriers to COVID-19 vaccine uptake for these populations and challenges faced by LHDs from LHDs’ perspectives. In addition, we explored LHDs’ experience with implementing COVID-19 mobile vaccine clinics (MVCs) in Utah. Materials and Methods: We conducted virtual focus group discussions (FGDs) from October 28 to November 1, 2022, with health officers from Utah’s Department of Health and Human Services (DHHS) and LHDs. We recruited participants via email, transcribed recordings verbatim, and analyzed data using inductive content analysis. Results: Eight participants, one from the Utah DHHS and seven from Utah’s LHDs (mostly executive directors or managers), participated in two FGDs. Barriers to vaccine uptake among underserved communities included structural, behavioral, and informational barriers. LHDs faced two main challenges to increasing vaccination rate: limited resources and the lack of established partnerships with trusted communities/organizations/leaders. Strategies implemented to increase vaccine uptake included multiple channels for vaccine access and information provision, and building multiple partnerships. Key lessons learned were the importance of partnerships with trusted community/organization leaders and building core staff for vaccine uptake. Regarding MVCs, they were effective in reaching underserved populations, however, their impact was unclear in rural areas. Conclusion: Building trust through partnerships with trusted community/organization leaders was crucial for increasing vaccine uptake in underserved populations and promoting health equity. The impact of MVCs on underserved populations in different settings remains unclear, further research is needed.

We provide a method to track the active prevalence of COVID-19 in real time, correcting for time-varying sample selection in symptom-based testing data and incomplete tracking of recovered cases and fatalities. Our method only requires publicly available data on positive testing rates in combination with one parameter, which we estimate based on a representative randomized sample of nearly 10,000 individuals tested in Utah in May and June 2020. We validate our method using external studies in Indiana in April 2020 and two counties in Utah in March 2021. In all three locations and times, our estimates of latent prevalence are within the 95 percent confidence intervals of prevalence estimates from randomized testing. Applying our method to all 50 states, we show that true prevalence is 2-3 times higher than publicly reported.

Abstract Background The role of active surveillance (AS) and contact precautions (CP) in acute care settings for preventing transmission of endemic drug resistant organisms such as methicillin-resistant Staphylococcus aureus (MRSA) remains unsettled. The emergence of SARS-CoV-2 led to a shift in VA policy in March 2020, when VA acute care facilities were allowed to suspend AS for MRSA and CP for patients with MRSA colonization or active infection, resulting in a partial and variable de-implementation of AS/CP across the VA (Figure 1). We evaluated the impact of this change on VA MRSA infection rates. Methods We modeled monthly positive MRSA culture rate at the ward-facility level using (1) all positive MRSA cultures, and (2) only positive sterile-site cultures (to more closely capture ‘true infections’). Our primary outcome was HAIs (occurring ≥ 3d after admission), including those up to 30-days post-discharge. We used Poisson, Negative Binomial, and Poisson mixed-effects regression approaches, clustering within ward type (ICU/non-ICU) and facility. With each approach, 4 different models incorporated increasing numbers of covariates to evaluate the robustness of the results. Results Using Poisson regression, we found culture rate, discontinuing AS & CP, and discontinuing CP only for colonization are associated with an increased MRSA positive culture rate (Model 1, Table 1). Addition of the year prior infection rate (Models 2–4) nullifies the association between AS & CP and MRSA positive culture rate. Results were similar when modeling positive sterile site cultures only (not shown) and using Negative Binomial regression (Table 2). Facility-level use of AS & CP is not associated with MRSA positive culture rate when using Poisson mixed-effects regression (Table 3), suggesting that accounting for facility-level clustering eliminates (or reduces) the apparent effect of AS/CP. Conclusion The impact of de-implementing AS & CP is complex and difficult to discern. The inference that de-implementation of AS & CP increased MRSA infection rates was not robust to relaxation of simplifying assumptions. These findings combined with the existence of unobservable data (e.g., use of gowns/gloves during the pandemic), imply substantial challenges surrounding statistical interpretation. Disclosures All Authors: No reported disclosures

Importance:Clostridioides difficile is among the most prevalent health care-associated pathogens worldwide. Controlling it remains a critical challenge, due in part to spore viability on surfaces. Objective:To quantify transmission of C difficile within health care facilities and evaluate the roles of environmental surfaces and health care personnel (HCP) hands in C difficile movement. Design, Setting, and Participants:In 2018, a 13-week longitudinal, observational study was conducted in 2 intensive care units (ICUs) in Utah with daily culture-based sampling of patient body sites, room environmental surfaces, HCP hands, and shared environmental surfaces. Both toxigenic and nontoxigenic C difficile strains were selected for whole genome sequencing and included in the analysis. Data were analyzed from September 2021 to September 2024. Main Outcomes and Measures:The primary outcome was the identification of transmission clusters based on genomic relatedness between isolates from patients, environmental surfaces, and HCP hands. Clusters were defined as isolates with 2 or fewer single nucleotide variants between them. Results:Of the 278 unique ICU admissions, 177 patients consented to body site sampling and were sampled. Along with these, environment surfaces and HCP hands were sampled daily for all occupied rooms, leading to 7000 total samples. Sampling patients, their environment, and HCP hands revealed that nearly 8% of all patients had C difficile linked to other admissions and 57% of transmission clusters bridged nonoverlapping patient-stays. Including environmental surfaces and HCP hands, a 3.6-fold higher C difficile movement was identified than with patient sampling alone, highlighting environmental surfaces as reservoirs. Conclusions and Relevance:These results challenge the idea that nosocomial transmission is not a primary source of acquisition and underscore the importance of hand hygiene and environmental decontamination. This study reinforces the need to include environmental surfaces and HCP hands in future work characterizing the burden of nosocomial transmission. Understanding the transmission pathways of C difficile within health care facilities, particularly the roles of environmental surfaces and HCP hands, is critical to improving infection control measures.

Background:Systematic evidence on antimicrobial selection for antimicrobial resistance (AMR) is scarce. We estimated the effect of prescribing key antibiotic classes on AMR across U.S. Veterans Affairs Medical Centres (VAMC). Methods:We analysed clinical isolates of Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae , and Pseudomonas aeruginosa from 138 VAMC from Feb 1, 2007 to Dec 31, 2021. Antimicrobial prescribing was measured as inpatient days of therapy per 1000 patient-days; multidrug resistance as number of resistant phenotypes per 1,000 admissions. Temporal trends were modelled using generalized estimating equations and average annual percentage changes (AAPC). Multilevel multinomial logistic regression related facility-level antibiotic prescribing (days of therapy per 100 patient-days in the last 14d) to the relative odds of resistant phenotypes. Findings:Hospital-onset infection incidence declined for all pathogens, except third-generation cephalosporin (3GC)-resistant E coli . Antimicrobial prescribing remained stable or decreased, except 3GC prescribing, which increased from 2007 until 2019 (AAPC=2·4%, 95% CI 1·3%-3·5%, p-value<0.0001). Fluoroquinolone (FQL) use was associated with resistance across all pathogens. In S aureus , each day of FQL treatment was linked to a 4·6% (95CI: 1·5, 7·7, p-value=0.0127) increase in the relative odds of isolating FQL-resistant, macrolide-susceptible, methicillin-resistant S aureus . Anti-staphylococcal beta-lactams were not linked to MRSA. Each day of 3GC treatment increased the odds of isolating 3GC- and beta-lactam/beta-lactamase-resistant E coli by 5·2% (95%CI: 1·3%, 9·4%, p-value=0.0079) and K pneumoniae by 3·0% (95% CI: -0·1%-6·2%, p-value=0.0600). Each day of carbapenem treatment increased the odds of carbapenem-resistant, FQL- and BL/BLI-susceptible P aeruginosa by 15·7% (95%CI: 9·4%, 22·4%, p-value<0.0001). Interpretation:Higher facility-level antimicrobial use increased the odds of corresponding resistant phenotypes, with important exceptions. FQLs selected for resistance across multiple pathogens. Increased 3GC prescribing likely offset reductions in FQLs and was associated with co-resistance in E coli . These findings underscore the need for comprehensive stewardship that coordinates strategies across antimicrobials.

Abstract Background Clostridioides difficile infections (CDI) are caused by a diverse group of strains with differences in prevalence and differing antimicrobial susceptibilities. Over the past 20 years the C. difficile (CD) molecular epidemiology has changed as the prevalence of the epidemic strain recognized as PCR-Ribotype group (RT) 027 has decreased. The objective of this study was to determine the current molecular epidemiology and antimicrobial susceptibility patterns of CD at two Veteran Affairs hospitals.Figure 1.PCR-Ribotyping of Clostridioides difficile isolates collected from the Hines VA and Cleveland VA from 7/2022 - 6/2023 Methods We determined the molecular epidemiology and antimicrobial susceptibility of CD at the Edwards Hines Jr., VA hospital and the Louis Stokes Cleveland VA hospital from 7/2022 – 6/2023 from clinically relevant stool specimens. Available stools were cultured and recovered CD isolates underwent PCR-RT (n=194). In vitro minimum inhibitory concentration (MIC) was determined by agar gel dilution for 9 antibiotics known to precipitate CDI. Geometric mean MIC was compared between hospitals by Wilcoxon rank sum test and Kruskal-Wallis was used to compare MICs across PCR-RT groups. Results From 7/2022 – 6/2023, RT106 was the most prevalent strain accounting for 23.5% (16/68) and 15.1% (19/128) of isolates at the Hines VA and Cleveland VA, respectively. (Figure 1) RT002 and RT014/020 were the next most common strains, while RT027 accounted for only 4.1% (8/194) of all isolates. The Hines VA isolates had a higher geometric mean MIC for cefepime (208.15 µg/ml vs 155.13 µg/ml, p< 0.01), clindamycin (9.91 µg/ml vs 5.3 µg/ml, p< 0.01), and piperacillin/tazobactam (9.46 µg/ml vs 7.36 µg/ml, p=0.03). The Cleveland isolates had a higher doxycycline geometric mean MIC (0.08 µg/ml vs 0.05 µg/ml, p< 0.01). (Table 1) The clindamycin geometric mean MIC was elevated for RT255 (9.33 µg/ml) and RT027 (49.35 µg/ml) when compared to other groups (p< 0.01). The doxycycline geometric mean MIC was elevated for RT078/126 (1.17 µg/ml) when compared to other groups (p< 0.01). (Table 2) Conclusion The once epidemic strain RT027 has been supplanted by three different strain groups at both VA hospitals. Further research is needed to correlate local antibiotic usage patterns with the differing strain prevalence and antimicrobial susceptibilities noted. Disclosures Andrew M. Skinner, MD, BioK plus: Advisor/Consultant|Ferring Pharmaceuticals: Advisor/Consultant|Recursion pharmaceutical: Advisor/Consultant Larry K. Kociolek, MD, MSCI, Merck: Grant/Research Support Curtis Donskey, MD, Clorox: Grant/Research Support|Pfizer: Grant/Research Support Dale N. Gerding, MD, AstraZeneca: Advisor/Consultant|Destiny Pharma: Advisor/Consultant|Destiny Pharma: Licensed IP to Destiny|Sebela: Advisor/Consultant|Sebela: Licensed IP Stuart Johnson, M.D., Acurx Pharmaceuticals: Advisor/Consultant|Bio-K Plus International: Advisor/Consultant|Ferring Phamraceuticals: Advisor/Consultant

Objective:To describe the implementation of an outpatient UTI intervention and its impact on UTI management. Design:Quasi-experimental retrospective controlled study. Participants:Outpatient clinicians practicing in emergency and primary care settings within 8 Veterans Affairs Medical Centers. Methods:An intervention conducted utilizing the CDC Core Elements Antibiotic Stewardship framework between September 2022 and July 2023. Actions included academic detailing, audit feedback, and updated reflex culture procedures. Logistic regression adjusted for covariates (risk ratio [RR], 95% confidence interval [CI]), and a difference-in-differences (DID) analysis compared multiple UTI management metrics between intervention and control facilities. Results:There were 278,419 and 157,067 genitourinary (GU) tract qualifying visits [mean (SD) age 71.7 (13.9), 92.6% male] within 8 intervention and 8 control sites, respectively. Antibiotic prescribing rates for a broad-based GU tract metric that included UTIs pre/post implementation were [N, (%)] 12,688 (8.0) and 4,062 (8.0) within intervention sites and 5,686 (6.3) and 1,920 (6.8) within control sites, respectively [DID aRR 0.97 (0.92, 1.02)]. Appropriate treatment selection for uncomplicated UTI (uUTI) pre/post implementation was 5,994(76.9) and 1,945(79.9), compared to 2,519(74.6) and 977(82.1) within control sites, respectively [DID aRR 0.94 (0.91, 0.98)]. uUTI appropriate treatment duration pre/post implementation was 5,709 (73.3) and 1,927 (79.2), compared to 2,469 (73.1) and 869 (73.0) within control sites, respectively [DID aRR 1.08 (1.03, 1.13)]. No evidence of diagnostic shifting or return GU visits post-implementation was observed. Conclusions:Implementation of an outpatient UTI intervention in a predominantly male population was feasible but marginally effective.

Importance:Intestinal multidrug-resistant organism (MDRO) colonization is highly prevalent in long-term acute care hospital (LTACH) patients and is associated with MDRO infection and transmission. However, there are no therapies approved by the US Food and Drug Administration to reduce intestinal MDRO colonization. Objective:To determine the safety and acceptability of fecal microbiota transplantation (FMT) in LTACH patients. Design, Setting, and Participants:This single-center, open-label nonrandomized clinical trial was conducted from April to December 2023 at an LTACH in the Southeastern US with median 50-patient census and 28-day length of stay. Patients with MDRO colonization were identified by perirectal prevalence sampling. Patients colonized with at least 1 target MDRO were approached for informed consent for FMT. FMT recipients were compared with untreated controls with MDRO colonization. Data were analyzed from August 2024 to May 2025. Intervention:Healthy donor fecal microbiota (50-100 g stool and 250 mL normal saline with 9% glycerol) instilled via gastrostomy tube or enema without antibiotic or bowel preparation conditioning. Main Outcomes and Measures:The primary outcome was frequency and severity of adverse events. Solicited adverse events were recorded for 7 days. Unsolicited adverse events were recorded for 6 months. Four weekly perirectal MDRO cultures were performed after FMT. Results:A total of 42 patients, including 10 (mean [SD] age, 63.8 (14.5) years; 7 [70%] female) who received FMT and 32 contemporaneous controls (mean [SD] age, 64.0 [13.7] years; 13 [41%] female) were assessed. In 2 prevalence surveys, 23 of 32 (72%) and 26 of 34 (77%) perirectal cultures grew at least 1 MDRO. Among the FMT group, 5 patients received FMT via gastrostomy alone, 4 via enema alone, and 1 with both routes more than 30 days apart. No serious adverse events were attributed to FMT, and post-FMT solicited adverse events were mild. At final visit, all perirectal cultures from FMT recipients grew at least 1 MDRO. Post hoc analyses found numerically fewer FMT recipients had positive blood culture results (0 individuals vs 6 individuals [19%]; P = .31), pathogen intestinal dominance (2 of 8 individuals [25%] vs 4 of 8 individuals [50%]; P = .61), and 7 fewer days of antibiotic therapy per 1000 patient days (median [IQR], 12.6 [0-25.2] days vs 19.7 [6.5-36.1] days; P = .38) compared with controls in the 6 months after prevalence survey, although these differences were not statistically significant. Accounting for higher baseline FMT recipient antibiotic use, difference-in-differences analysis estimated 26 (95% CI, -64 to 12) fewer days of antibiotic therapy per 1000 patient-days after FMT, although this difference was also not statistically significant. Conclusions and Relevance:In this nonrandomized pilot clinical trial, FMT was acceptable for LTACH patients without related serious adverse events. Although not powered to test these outcomes, this study found potential reductions in bacteremia, intestinal pathogen domination, and antibiotic use associated with FMT, suggesting FMT should be evaluated in larger, randomized trials. Trial Registration:ClinicalTrials.gov Identifier: NCT05780801.

BACKGROUND:Risk perceptions and social activities shaped SARS-CoV-2 transmission. However, most related studies are cross-sectional, often neglecting correlated outcomes and dropout bias. We assessed relationships between local COVID-19 incidence levels and health care personnel (HCP) risk perceptions and social activity count. METHODS:We conducted a prospective cohort study using monthly surveys (December 2021-May 2022) at an academic health care system (n = 1,590 HCP). COVID-19 incidence was categorized into 4 levels, from low to high. Five risk perception measures (scaled 1-4) and activity count were modeled simultaneously using a Bayesian joint model to estimate the impact of incidence on risk perception and behavior. RESULTS:COVID-19 incidence was associated with various risk perception measures and activity count. Strongest risk perception associations were perceived risk of infection and risk while unmasked indoors in public, with score increases of 0.60 (95% credible interval [CI]: 0.51, 0.69) and 0.62 (95% CI: 0.52, 0.71), respectively, during high incidence. Individuals reported 0.68 (95% CI: -0.88, -0.47) fewer social activities during high incidence levels. CONCLUSIONS:During the Omicron surge, HCP adjusted their risk perceptions and behaviors in response to changing risk and placed high value on the protective effects of masking. These findings can inform communication strategies during future outbreaks.