Booster vaccination protection against SARS-CoV-2 infections in young adults during an Omicron BA.1-predominant period: A retrospective cohort study.

BACKGROUND: While booster vaccinations clearly reduce the risk of severe Coronavirus Disease 2019 (COVID-19) and death, the impact of boosters on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections has not been fully characterized: Doing so requires understanding their impact on asymptomatic and mildly symptomatic infections that often go unreported but nevertheless play an important role in spreading SARS-CoV-2. We sought to estimate the impact of COVID-19 booster doses on SARS-CoV-2 infections in a vaccinated population of young adults during an Omicron BA.1-predominant period. METHODS AND FINDINGS: We implemented a cohort study of young adults in a college environment (Cornell University's Ithaca campus) from a period when Omicron BA.1 was the predominant SARS-CoV-2 variant on campus (December 5 to December 31, 2021). Participants included 15,800 university students who completed initial vaccination series with vaccines approved by the World Health Organization for emergency use, were enrolled in mandatory at-least-weekly surveillance polymerase chain reaction (PCR) testing, and had no positive SARS-CoV-2 PCR test within 90 days before the start of the study period. Robust multivariable Poisson regression with the main outcome of a positive SARS-CoV-2 PCR test was performed to compare those who completed their initial vaccination series and a booster dose to those without a booster dose. A total of 1,926 unique SARS-CoV-2 infections were identified in the study population. Controlling for sex, student group membership, date of completion of initial vaccination series, initial vaccine type, and temporal effect during the study period, our analysis estimates that receiving a booster dose further reduces the rate of having a PCR-detected SARS-CoV-2 infection relative to an initial vaccination series by 56% (95% confidence interval [42%, 67%], P < 0.001). While most individuals had recent booster administration before or during the study period (a limitation of our study), this result is robust to the assumed delay over which a booster dose becomes effective (varied from 1 day to 14 days). The mandatory active surveillance approach used in this study, under which 86% of the person-days in the study occurred, reduces the likelihood of outcome misclassification. Key limitations of our methodology are that we did not have an a priori protocol or statistical analysis plan because the analysis was initially done for institutional research purposes, and some analysis choices were made after observing the data. CONCLUSIONS: We observed that boosters are effective, relative to completion of initial vaccination series, in further reducing the rate of SARS-CoV-2 infections in a college student population during a period when Omicron BA.1 was predominant; booster vaccinations for this age group may play an important role in reducing incidence of COVID-19.

Veterinary Students' Knowledge and Awareness of Antimicrobial Stewardship before and after Clinical Rotations.

Given the global threat of antimicrobial resistance, it is imperative that veterinary graduates are effective antimicrobial stewards. Veterinary students learn the principles of antimicrobial stewardship explicitly, through pre-clinical coursework, and implicitly, through the cases they each encounter on clinical rotations. We aimed to understand the influence of pre-clinical versus clinical learning on veterinary students' knowledge and awareness of antimicrobial concepts to guide efforts to improve instruction in these areas. To assess knowledge acquisition and to explore student perceptions of antimicrobial stewardship, a standardized online survey was administered to Cornell University veterinary students at two timepoints: in August 2020 before clinical rotations (N = 26 complete responses and N = 24 partial responses) and again in May 2021 after their clinical rotations (N = 17 complete responses and N = 6 partial responses). Overall and section-specific confidence and knowledge scores were calculated, using pairwise deletion for incomplete responses. Students generally had low confidence in antimicrobial topics and correctly answered only half of knowledge questions correctly; they performed the best on antimicrobial resistance knowledge questions. There were no significant differences in knowledge or confidence after clinical rotations. On average, students had only read one antimicrobial stewardship guideline. Students reported that human health care providers contributed more to antimicrobial resistance than veterinarians. In conclusion, graduating veterinary students at our institution have significant knowledge gaps in critical principles that are essential to become antimicrobial stewards. Explicit instruction in antimicrobial stewardship is necessary in the pre-clinical and clinical coursework, and the practical use of antimicrobial stewardship guidelines should be emphasized.

Integrated Surveillance System for Controlling COVID-19 on a University Campus, 2020‒2021.

To minimize the impacts of COVID-19 and to keep campus open, Cornell University's Ithaca, NY, campus implemented a comprehensive process to monitor COVID-19 spread, support prevention practices, and assess early warning indicators linked to knowledge, behaviors, and attitudes of campus community members. The integrated surveillance approach informed leadership and allowed for prompt adjustments to university policies and practices through evidence-based decisions. This approach enhanced healthy behaviors and promoted the well-being and safety of all community members. (Am J Public Health. 2022;112(7):980-984. https://doi.org/10.2105/AJPH.2022.306838).

Analysis of Multidrug Resistance in Staphylococcus aureus with a Machine Learning-Generated Antibiogram.

Multidrug resistance (MDR) surveillance consists of reporting MDR prevalence and MDR phenotypes. Detailed knowledge of the specific associations underlying MDR patterns can allow antimicrobial stewardship programs to accurately identify clinically relevant resistance patterns. We applied machine learning and graphical networks to quantify and visualize associations between resistance traits in a set of 1,091 Staphylococcus aureus isolates collected from one New York hospital between 2008 and 2018. Antimicrobial susceptibility testing was performed using reference broth microdilution. The isolates were analyzed by year, methicillin susceptibility, and infection site. Association mining was used to identify resistance patterns that consisted of two or more individual antimicrobial resistance (AMR) traits and quantify the association among the individual resistance traits in each pattern. The resistance patterns captured the majority of the most common MDR phenotypes and reflected previously identified pairwise relationships between AMR traits in S. aureus Associations between ß-lactams and other antimicrobial classes (macrolides, lincosamides, and fluoroquinolones) were common, although the strength of the association among these antimicrobial classes varied by infection site and by methicillin susceptibility. Association mining identified associations between clinically important AMR traits, which could be further investigated for evidence of resistance coselection. For example, in skin and skin structure infections, clindamycin and tetracycline resistance occurred together 1.5 times more often than would be expected if they were independent from one another. Association mining efficiently discovered and quantified associations among resistance traits, allowing these associations to be compared between relevant subsets of isolates to identify and track clinically relevant MDR.

Modeling the Effect of Tylosin Phosphate on Macrolide-Resistant Enterococci in Feedlots and Reducing Resistance Transmission.

Tylosin phosphate (TYL) is administered to more than 50% of U.S. beef cattle to reduce the incidence of liver abscesses but may increase the risk of macrolide-lincosamide-streptogramin-resistant bacteria disseminating from the feedlot. Limited evidence has been collected to understand how TYL affects the proportion of resistant bacteria in cattle or the feedlot environment. We created a mathematical model to investigate the effects of TYL administration on Enterococcus dynamics and examined preharvest strategies to mitigate the impact of TYL administration on resistance. The model simulated the physiological pharmacokinetics of orally administered TYL and estimated the pharmacodynamic effects of TYL on populations of resistant and susceptible Enterococcus within the cattle large intestine, feedlot pen, water trough, and feed bunk. The model parameters' population distributions were based on the available literature; 1000 Monte Carlo simulations were performed to estimate the likely distribution of outcomes. At the end of the simulated treatment period, the median estimated proportion of macrolide-resistant enterococci was only 1 percentage point higher within treated cattle compared with cattle not fed TYL, in part because the TYL concentrations in the large intestine were substantially lower than the enterococci minimum inhibitory concentrations. However, 25% of the simulated cattle had a >10 percentage point increase in the proportion of resistant enterococci associated with TYL administration, termed the TYL effect. The model predicts withdrawing TYL treatment and moving cattle to an antimicrobial-free terminal pen with a low prevalence of resistant environmental enterococci for as few as 6 days could reduce the TYL effect by up to 14 percentage points. Additional investigation of the importance of this subset of cattle to the overall risk of resistance transmission from feedlots will aid in the interpretation and implementation of resistance mitigation strategies.

Expanding behavior pattern sensitivity analysis with model selection and survival analysis.

BACKGROUND: Sensitivity analysis is an essential step in mathematical modeling because it identifies parameters with a strong influence on model output, due to natural variation or uncertainty in the parameter values. Recently behavior pattern sensitivity analysis has been suggested as a method for sensitivity analyses on models with more than one mode of output behavior. The model output is classified by behavior mode and several behavior pattern measures, defined by the researcher, are calculated for each behavior mode. Significant associations between model inputs and outputs are identified by building linear regression models with the model parameters as independent variables and the behavior pattern measures as the dependent variables. We applied the behavior pattern sensitivity analysis to a mathematical model of tetracycline-resistant enteric bacteria in beef cattle administered chlortetracycline orally. The model included 29 parameters related to bacterial population dynamics, chlortetracycline pharmacokinetics and pharmacodynamics. The prevalence of enteric resistance during and after chlortetracycline administration was the model output. Cox proportional hazard models were used when linear regression assumptions were not met. RESULTS: We have expanded the behavior pattern sensitivity analysis procedure by incorporating model selection techniques to produce parsimonious linear regression models that efficiently prioritize input parameters. We also demonstrate how to address common violations of linear regression model assumptions. Finally, we explore the semi-parametric Cox proportional hazards model as an alternative to linear regression for situations with censored data. In the example mathematical model, the resistant bacteria exhibited three behaviors during the simulation period: (1) increasing, (2) decreasing, and (3) increasing during antimicrobial therapy and decreasing after therapy ceases. The behavior pattern sensitivity analysis identified bacterial population parameters as high importance in determining the trajectory of the resistant bacteria population. CONCLUSIONS: Interventions aimed at the enteric bacterial population ecology, such as diet changes, may be effective at reducing the prevalence of tetracycline-resistant enteric bacteria in beef cattle. Behavior pattern sensitivity analysis is a useful and flexible tool for conducting a sensitivity analysis on models with varied output behavior, enabling prioritization of input parameters via regression model selection techniques. Cox proportional hazard models are an alternative to linear regression when behavior pattern measures are censored or linear regression assumptions cannot be met.

Use of pharmacokinetic modeling to assess antimicrobial pressure on enteric bacteria of beef cattle fed chlortetracycline for growth promotion, disease control, or treatment.

Antimicrobial use in food animals may increase antimicrobial resistance in their enteric bacteria that can be transferred to human microbiome. Over 70% of U.S. beef feedlots use non-ionophore in-feed antimicrobials for animal disease control, treatment, or growth promotion. The fraction of feedlots feeding chlortetracycline (CTC), mostly for disease control but also for treatment, has increased since the mid-1990s to present. Quantitative information on the antimicrobial selective pressure on the enteric bacteria of cattle fed CTC is lacking. Hence, the purpose of this study was to develop a deterministic mathematical model of the pharmacokinetics of ingested CTC in a beef steer and estimate the concentration of antimicrobially active (undegraded) CTC in the animal's large intestine. To evaluate the fit of the model to existing data, we also estimated the CTC concentrations in the central circulation, and fresh and aging manure from the steer. The model accounted for CTC abiotic degradation while in the gastrointestinal tract, absorption into the central circulation and tissues, biliary and renal excretion, and removal from the intestine by defecation. The model included an increase in the large intestine volume as the steer grew. We estimated that during CTC feeding to a 300-kg steer for growth promotion, the maximal drug concentration in the large intestine was 0.3 µg/mL; during disease control it was 1.7 µg/mL; and during treatment it was 31.5 µg/mL. The estimated CTC concentrations in the central circulation and the steer's manure agreed reasonably well with published data.

An exploration of descriptive machine learning approaches for antimicrobial resistance: Multidrug resistance patterns in Salmonella enterica.

Salmonellosis is one of the most common foodborne diseases worldwide, with the ability to infect humans and animals. Antimicrobial resistance (AMR) and, particularly, multidrug resistance (MDR) among Salmonella enterica poses a risk to human health. Antimicrobial use (AMU) regulations in livestock have been implemented to reduce AMR and MDR in foodborne pathogens. In this study, we used an integrated machine learning approach to investigate Salmonella AMR and MDR patterns before and after the implementation of AMU restrictions in agriculture in the United States. For this purpose, Salmonella isolates from cattle in the National Antimicrobial Resistance Monitoring System (NARMS) dataset were analysed using three descriptive models consisting of hierarchical clustering, network analysis, and association rule mining. The analysis showed the impact of the United States' 2012 extra-label cephalosporin regulations on AMR trends and revealed a distinctive MDR pattern in the Dublin serotype. The results also indicated that each descriptive model provides insights on a specific aspect of resistance patterns and, therefore, combining these approaches make it possible to gain a deeper understanding of AMR.

Longitudinal antimicrobial susceptibility trends of canine Staphylococcus pseudintermedius.

Antimicrobial resistance within Staphylococcus pseudintermedius poses a significant risk for the treatment of canine pyoderma and as a reservoir for resistance and potential zoonoses, but few studies examine long-term temporal trends of resistance. This study assesses the antimicrobial resistance prevalence and minimum inhibitory concentration (MIC) trends in S. pseudintermedius (n=1804) isolated from canine skin samples at the Cornell University Animal Health Diagnostic Center (AHDC) between 2007 and 2020. Not susceptible (NS) prevalence, Cochran-Armitage tests, logrank tests, MIC50 and MIC90 quantiles, and survival analysis models were used to evaluate resistance prevalence and temporal trends to 23 antimicrobials. We use splines as predictors in accelerated failure time (AFT) models to model non-linear temporal trends in MICs. Multidrug resistance was common among isolates (47%), and isolates had moderate to high NS prevalence to the beta-lactams, chloramphenicol, the fluoroquinolones, gentamicin, the macrolides/lincosamides, the tetracyclines, and trimethoprim-sulfamethoxazole. However, low levels of NS to amikacin, rifampin, and vancomycin were observed. Around one third of isolates (38%) were found to be methicillin resistant S. pseudintermedius (MRSP), and these isolates had a higher prevalence of NS to all tested antimicrobials than methicillin susceptible isolates. Amongst the MRSP isolates, one phenotypically vancomycin resistant isolate (MIC >16 µg/mL) was identified, but genomic sequence data was unavailable. AFT models showed increasing MICs across time to the beta-lactams, chloramphenicol, the fluoroquinolones, gentamicin, and the macrolides/lincosamides, and decreasing temporal resistance (decreasing MICs) to doxycycline was observed amongst isolates. Notably, ATF modeling showed changes in MIC distributions that were not identified using Cochran-Armitage tests on prevalence, MIC quantiles, and logrank tests. Increasing resistance amongst these S. pseudintermedius isolates highlights the need for rational, empirical prescribing practices and increased antimicrobial resistance (AMR) surveillance to maintain the efficacy of current therapeutic agents. AFT models with non-linear predictors may be a useful, breakpoint-independent, surveillance tool alongside other modeling methods and antibiograms.

Syndromic Surveillance Tracks COVID-19 Cases in University and County Settings: Retrospective Observational Study.

Background: Syndromic surveillance represents a potentially inexpensive supplement to test-based COVID-19 surveillance. By strengthening surveillance of COVID-19-like illness (CLI), targeted and rapid interventions can be facilitated that prevent COVID-19 outbreaks without primary reliance on testing. Objective: This study aims to assess the temporal relationship between confirmed SARS-CoV-2 infections and self-reported and health care provider-reported CLI in university and county settings, respectively. Methods: We collected aggregated COVID-19 testing and symptom reporting surveillance data from Cornell University (2020-2021) and Tompkins County Health Department (2020-2022). We used negative binomial and linear regression models to correlate confirmed COVID-19 case counts and positive test rates with CLI rate time series, lagged COVID-19 cases or rates, and day of the week as independent variables. Optimal lag periods were identified using Granger causality and likelihood ratio tests. Results: In modeling undergraduate student cases, the CLI rate (P=.003) and rate of exposure to CLI (P<.001) were significantly correlated with the COVID-19 test positivity rate with no lag in the linear models. At the county level, the health care provider-reported CLI rate was significantly correlated with SARS-CoV-2 test positivity with a 3-day lag in both the linear (P<.001) and negative binomial model (P=.005). Conclusions: The real-time correlation between syndromic surveillance and COVID-19 cases on a university campus suggests symptom reporting is a viable alternative or supplement to COVID-19 surveillance testing. At the county level, syndromic surveillance is also a leading indicator of COVID-19 cases, enabling quick action to reduce transmission. Further research should investigate COVID-19 risk using syndromic surveillance in other settings, such as low-resource settings like low- and middle-income countries.

Multidrug-resistant pathogens contaminate river water used in irrigation in disenfranchised communities.

OBJECTIVES: The contamination of fresh surface waters poses a significant burden on human health and prosperity, especially in marginalized communities with limited resources and inadequate infrastructure. Here, we performed in-depth genomic analyses of multidrug-resistant bacteria (MDR-B) isolated from Al-Oueik river water that is used for irrigation of agricultural fields in a disenfranchised area that also hosts a makeshift Syrian refugee camp. METHODS: A composite freshwater sample was filtered. Faecal coliforms were counted and extended spectrum cephalosporins and/or ertapenem resistant bacteria were screened. Isolates were identified using MALDI-TOF-MS and analysed using whole-genome sequencing (WGS) to identify the resistome, sequence types, plasmid types, and virulence genes. RESULTS: Approximately 106 CFU/100 mL of faecal coliforms were detected in the water. Four drug-resistant Gram-negative bacteria were identified, namely Escherichia coli, Klebsiella pneumoniae, Enterobacter hormaechei, and Pseudomonas otitidis. Notably, the E. coli isolate harboured blaNDM-5 and a YRIN-inserted PBP3, representing an emerging public health challenge. The K. pneumoniae isolate carried blaSHV-187 as well as mutations in the gene encoding the OmpK37 porin. Enterobacter hormaechei and P. otitidis harboured blaACT-16 and blaPOM-1, respectively. CONCLUSION: This report provides comprehensive genomic analyses of MDR-B in irrigation water in Lebanon. Our results further support that irrigation water contaminated with faecal material can be a reservoir of important MDR-B, which can spread to adjacent agricultural fields and other water bodies, posing both public health and food safety issues. Therefore, there is an urgent need to implement effective water quality monitoring and management programs to control the proliferation of antibiotic-resistant pathogens in irrigation water in Lebanon.

Representative Public Health Surveys Pose Several Challenges: Lessons Learned Across 9 Communities During the COVID-19 Pandemic.

Community surveillance surveys offer an opportunity to obtain important and timely public health information that may help local municipalities guide their response to public health threats. The objective of this paper is to present approaches, challenges, and solutions from SARS-CoV-2 surveillance surveys conducted in different settings by 2 research teams. For rapid assessment of a representative sample, a 2-stage cluster sampling design was developed by an interdisciplinary team of researchers at Oregon State University between April 2020 and June 2021 across 6 Oregon communities. In 2022, these methods were adapted for New York communities by a team of veterinary, medical, and public health practitioners. Partnerships were established with local medical facilities, health departments, COVID-19 testing sites, and health and public safety staff. Field staff were trained using online modules, field manuals describing survey methods and safety protocols, and in-person meetings with hands-on practice. Private and secure data integration systems and public awareness campaigns were implemented. Pilot surveys and field previews revealed challenges in survey processes that could be addressed before surveys proceeded. Strong leadership, robust trainings, and university-community partnerships proved critical to successful outcomes. Cultivating mutual trust and cooperation among stakeholders is essential to prepare for the next pandemic.

Associations between Mycobacterium avium subsp. paratuberculosis antibodies in bulk tank milk, season of sampling and protocols for managing infected cows.

BACKGROUND: The objective of this study was to identify associations between the concentration of Mycobacterium avium subsp. paratuberculosis (MAP) antibodies in bulk milk and potential risk factors in herd management and herd characteristics, explaining high MAP antibody titers in milk. An extensive questionnaire was administered to 292 organic and conventional dairy farms from New York, Wisconsin and Oregon. Bulk milk samples were taken from each farm for MAP enzyme-linked immunosorbent assay (ELISA). A general linear model was constructed with MAP ELISA value as the outcome variable and the management factors and herd characteristics as independent variables, while at the same time controlling for the study design variables of state, herd size, and production system (organic or conventional). High bulk tank MAP ELISA value may be due to either a high prevalence of MAP in a herd with many cows contributing to the antibody titer or due to a few infected cows that produce large quantities of antibodies. RESULTS: Results of the regression models indicated that bulk milk ELISA value was associated with season of sampling and the presence or absence of protocols for managing MAP-positive cows. The concentration of MAP antibodies in bulk milk varied seasonally with a peak in the summer and low concentrations in the winter months. When compared to farms that had never observed clinical Johne's disease, keeping MAP-positive cows or only culling them after a period of delay was associated with an increase in optical density. CONCLUSIONS: The seasonal variation in MAP antibody titers, with a peak in the summer, may be due to a seasonal increase in MAP-bacterial load. Additionally, seasonal calving practices may contribute to seasonal fluctuations in MAP antibody titers in bulk tank milk. Keeping MAP-positive cows increases the antibody titer in bulk milk, likely due to direct antibody production in the infected cow and indirect triggering of antibody production in herdmates.

Evidence for the transmission of antimicrobial resistant bacteria between humans and companion animals: A scoping review.

Objective: Transmission of antimicrobial resistant bacteria between people and household pets, such as dogs and cats, is an emerging global public health problem. This scoping review synthesized existing evidence of human-pet bacteria transmission to understand the magnitude and breadth of this issue. Methods: The search included specific and generic terms for bacteria, resistance, transmission, pets, and humans. Searches were conducted through PubMed, Scopus, Web of Science, CABI Global Health, Networked Digital Library of Theses and Dissertations, Google Scholar. All studies published in English and Mandarin that isolated bacteria from pets (cats and dogs) and humans who had contact with the pets, and reported phenotypic or genotypic antimicrobial sensitivity test results, were included in this review. In cases of bacterial species that are commonly associated with pets, such as Staphylococcus pseudintermedius and Pasteurella multocida, we also included studies that only isolated bacteria from humans. Results: After removing duplication, the search captured 9355 studies. A total of 1098 papers were screened in the full-text review, and 562 studies were identified as eligible according to our inclusion criteria. The primary reason for exclusion was the lack of sensitivity testing. The included studies were published between 1973 and 2021. The most common study location was the United States (n = 176, 31.3%), followed by the United Kingdom (n = 53, 9.4%), Japan (n = 29, 5.2%), and Canada (n = 25, 4.4%). Most of the included studies were case reports (n = 367, 63.4%), cross-sectional/prevalence studies (n = 130, 22.4%), and case series (n = 51, 8.8%). Only few longitudinal studies (n = 14, 2.4%), case-control studies (n = 12, 2.1%), and cohort studies (n = 5, 0.9%) were included in our review. Most studies focused on Pasteurella multocida (n = 221, 39.3%), Staphylococcus aureus (n = 81, 14.4%), and Staphylococcus pseudintermedius (n = 52, 8.9%). For the 295 studies that used strain typing methods to compare bacteria from humans and pets, most used DNA banding pattern-based methods (n = 133, 45.1%) and DNA sequencing-based methods (n = 118, 40.0%). Conclusion: Transmission of bacteria could occur in both directions: pets to humans (e.g., S. pseudintermedius and P. multocida) and humans to pets (e.g., S. aureus). The majority of studies provided a low level of evidence of transmission (e.g., case reports), suggesting that more rigorous longitudinal, cohort, or case-control studies are needed to fully understand the risk of human-pet resistant bacterial transmission.

Divergent veterinarian and cat owner perspectives are barriers to reducing the use of cefovecin in cats.

OBJECTIVE: To understand veterinarian and cat owner perspectives on antimicrobial use in cats, reasons for prescribing cefovecin, and barriers to improving antimicrobial stewardship, including veterinarian and cat owner perspectives of giving oral medication to cats. SAMPLE: 21 New York veterinarians and 600 cat owners across the US. METHODS: Cat owners were surveyed about their preferences for and experiences in giving oral medications to cats and their experiences with antimicrobials specifically. Veterinarians were interviewed about antimicrobial use decisions in cats, benefits and drawbacks of cefovecin, and their perspectives on antimicrobial resistance. RESULTS: Many veterinarians reported feeling pressure to prescribe antimicrobials, while 41% of cat owners reported requesting antimicrobials. Although veterinarians are aware of the downsides of prescribing cefovecin, many prescribed cefovecin in situations where an antimicrobial was not needed or cefovecin may not have been the best choice. Veterinarians thought that 20% of cat owners could not give oral medications, but < 10% of cat owners had a cat that was impossible to medicate. CLINICAL RELEVANCE: The disconnect between veterinarians' assessment of and cat owners' reported abilities in administering oral medication may contribute to cefovecin use. Demonstrating for cat owners how to give oral medication may help improve compliance and reduce the use of parenteral long-acting formulations. Structural and educational interventions are needed to address other contributors to inappropriate antimicrobial use. This research provides the specific considerations about barriers and motivations for cat owners and veterinarians that are required to guide strategic, tailored interventions for both audiences to advance stewardship.

Pathways to sustainable antimicrobial use in cats.

Antimicrobial stewardship encompasses all the individual and collective actions that medical professionals take to preserve the efficacy of antimicrobials. It is a one-health problem, affecting animals and humans. The current state of antimicrobial use in cats, particularly (1) the overuse and improper use of cefovecin, which belongs to the third-generation cephalosporin class that is critically important to human health, and (2) use of antimicrobials when they are not needed, poses unsustainable risks of antimicrobial resistance. This paper describes the principles of antimicrobial stewardship and stewardship challenges faced by feline veterinarians, including (1) poor adherence to or awareness of antimicrobial use guidelines, (2) lack of access to affordable diagnostic tests and antibiograms, (3) lack of access to materials and tools for clients that may facilitate more sustainable antimicrobial use and help cat owners understand resistance risks, (4) underestimating the ability of cat owners to administer oral antimicrobials, and (5) limited time and resources to support stewardship efforts. Based on research described in this paper; an original research article by Cazer et al, JAVMA, December 2023; and a Currents in One Health article by Cobo-Angel et al, AJVR, December 2023, several solutions are proposed to advance antimicrobial stewardship in feline medicine. Many of these proposals were expressly requested by veterinarians interviewed in Cazer et al, JAVMA, December 2023. Education and training of veterinarians and cat owners is an essential step toward sustainable antimicrobial use, but it must be complemented with innovations in diagnostic testing, antimicrobial drug development, structural changes, and technological supports.

Equine synovial sepsis laboratory submissions yield a low rate of positive bacterial culture and a high prevalence of antimicrobial resistance.

OBJECTIVE: To investigate (1) variables associated with the likelihood of obtaining a positive culture, (2) commonly isolated microorganisms, and (3) antimicrobial resistance patterns of isolates from horses with presumptive synovial sepsis. SAMPLES: Synovial fluid, synovium, and bone samples from equine cases with presumptive synovial sepsis submitted to the Cornell University Animal Health Diagnostic Center from 2000 to 2020 for microbial culture and antimicrobial sensitivity testing. PROCEDURES: Univariable and multivariable analyses were performed to determine the effect of variables on the likelihood of positive culture. Frequency distributions for isolated organisms and antimicrobial resistance were generated. Multidrug resistance patterns and associations were assessed with association rule mining. RESULTS: The positive culture rate for all samples was 37.4%, while the positive culture rate among samples confirmed to be septic by a combination of clinical pathological variables and case details was 43%. Blood culture vial submissions were 1.7 times more likely to yield a positive culture compared to samples submitted in a serum tube. Structure sampled, tissue submitted, and horse age were associated with a positive culture. Staphylococcus spp (23.7%), Streptococcus spp (22.4%), and Enterococcus spp (9.67%) were commonly isolated. Multidrug resistance prevalence decreased from 92% (2000 to 2009) to 76% (2010 to 2020) of gram-negative isolates and 60% (2000 to 2009) to 52% (2010 to 2020) of gram-positive isolates. CLINICAL RELEVANCE: The positive culture rate from synovial fluid submissions with traditional sampling and culture methods remains low and may be optimized by submitting samples in blood culture vials. Overall, antimicrobial resistance was frequently observed but did not increase from the first to second decade for most genera.

Case-control study to identify risk factors for SARS-CoV-2 infection among university students in the northeastern USA.

Curbing the coronavirus disease 2019 (COVID-19) pandemic requires a thorough understanding of risk factors for transmission of SARS-CoV-2, the etiologic agent. Institutions of higher education present unique challenges for controlling disease spread because of features inherent to these settings. Our objective was to determine risk factors for SARS-CoV-2 infection among a university student population in the northeastern USA during the spring and fall 2021 semesters, using the case-control study design. Cases were defined as students with a newly diagnosed SARS-CoV-2 infection detected either through the robust PCR-based surveillance testing program on campus or through healthcare testing if symptoms compatible with COVID-19 were present. Controls were defined as students with negative SARS-CoV-2 status, based on consistently negative PCR results at the time of selection. A comprehensive questionnaire was administered to each student enrolled in the study, covering a broad range of campus life activities. A total of 446 cases and 1,185 controls were included in this study. Multivariable logistic regression analysis showed that recent party attendance (adjusted OR = 2.3, p < .0001), recently visiting a bar (aOR = 1.6, p = .007), living in a campus residence hall (aOR = 1.6, p = .001), fraternity/sorority membership (aOR = 1.8, p = .002), and recent travel (aOR = 1.3, p = .04) were associated with being a COVID-19 case. Having an on-campus job was negatively associated with being a COVID-19 case (aOR = 0.6, p = .0003). Among cases, the most commonly reported symptoms were cough (43.9%), fatigue (38.1%) and sore throat (30.3%). These findings can be used to inform the development of COVID-19 mitigation strategies and public health outreach efforts in university settings, thus reducing SARS-CoV-2 transmission among students and helping to preserve the vital education and research missions of these institutions.

Brief Research Report: Veterinary Student Perspective on COVID-19 and Veterinary Medicine.

COVID-19 has had significant effects on the field of veterinary medicine. Adaptation to pandemic-related and post-pandemic challenges requires engagement from all levels of the professional pipeline, including veterinary college students. Insights gained from this group may inform curriculum design, help the veterinary profession innovate, maximize opportunities for positive change, and avoid negative outcomes. The current study aimed to understand the potential impacts of the COVID-19 pandemic on veterinary medicine, as foreseen by second-year veterinary students in an online discussion during a public health course in the spring of 2020. Twenty-one percent of the 113 students agreed to participate in this qualitative research study. We used an inductive coding process and distilled the student responses into descriptive themes to capture diverse perspectives and understand possible post-pandemic pathways for the veterinary profession. Four themes emerged from the student discussion posts, describing how veterinarians might be affected by the COVID-19 pandemic: (1) economic and social impacts, (2) adapting to challenges, (3) collaborations to improve public health, and (4) disparities and diversity. These themes are a starting point for discussion and innovation as veterinarians plan for the post-pandemic world; further investigation will provide additional guidance for veterinary leaders.

Corrigendum: Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining.

[This corrects the article DOI: 10.3389/fmicb.2019.00687.].