Search

Antimicrobial resistance (AMR) is a growing global public health concern due to the rapid emergence and spread of resistant bacteria and other pathogens. Machine learning (ML) and genomics-based approaches are becoming more common compared to lab-based phenotypic methods for AMR detection as they bypass the laboratory culture process and offer an understanding of AMR-associated factors. The simultaneous prediction of multiple AMRs is a developing area since current multi-label prediction models are not well-suited to deal with a significant number of missing labels. A Rectified Classifier Chain (RCC) model was proposed and showed that it could effectively handle large numbers of missing labels in multi-label genomic sequence data and explain the results. Developing Next-Generation Sequencing (NGS) technologies and increasing Graphical Processing Unit capabilities have enabled rapid prediction of AMR with Deep Learning (DL) models. However, many genomics sequence datasets lack complete labelling, making applying a DL modelling approach challenging. Therefore, a Masked Loss Convolution Neural(ML-ConvNet) network was developed to improve the performance of the AMR prediction, particularly when there are large numbers of missing labels as the second contribution. Additionally, different Explainable AI (XAI) models were explored, and an XAI pipeline was integrated and validated, which showed that the model could predict AMR effectively even with a limited number of features. Finally, a 1-D Transformer based interpretable model was proposed to predict AMR from antimicrobial administration data for real-time antimicrobial stewardship. The results were interpreted and verified using quantitative validation metrics through an Integrated Gradient with rectified baseline pipeline. The proposed methods showed significant improvements in simultaneous AMR prediction with missing labels and provided interpretable results, which can be applied in real-world scenarios to improve antimicrobial stewardship. These contributions will pave the way for personalised antibiotic treatments and the introduction of AMR-aware food in the long term to overcome AMR challenges.

Salmonella Typhi (S. Typhi) is a Gram-negative bacterium and the etiologic agent of typhoid fever. High rates of typhoid were historically associated with urban slums in South Asia with poor sanitation, but recent multicentre surveillance studies have demonstrated that typhoid is also a major problem of urban and rural areas in sub-Saharan Africa. Typhoid necessitates antimicrobial therapy; however, antimicrobial resistance (AMR) poses a serious threat to the effective clinical management of typhoid, particularly in South Asia, where resistance to all oral antimicrobials used to treat typhoid has been reported. New typhoid conjugate vaccines (TCVs) are highly efficacious and two have been prequalified by the World Health Organization (WHO); a small number of countries have introduced TCVs into their national immunization programs. However, many countries lack primary surveillance data to inform decision-making for TCV introduction. Here, aiming to aggregate and analyse globally representative whole genome sequencing (WGS) data to inform public health action, I conducted a genomic investigation of the global distribution and transmission dynamics of AMR S. Typhi. With colleagues from Pakistan and India, I conducted phylogenetic analyses of the first molecularly confirmed azithromycin-resistant S. Typhi isolated in Pakistan and India and put them into context with contemporaneous azithromycin-resistant isolates. I found that single point mutations in acrB (efflux pump) were emerging independently in these settings, potentially associated with selective pressure. AMR in S. Typhi is associated with the H58 lineage, which arose recently before becoming globally dominant within a relatively short time. Given this lineage's association with AMR, I sought to investigate how, when, and where it emerged. Working with collaborators from the United Kingdom Health Security Agency (UKHSA), we performed phylogenetic and phylodynamic analyses using S. Typhi from returning travellers to the UK between 1980 and 1995. This dataset, which contained the earliest described H58 S. Typhi, indicates that the prototype H58 organisms were MDR, and that they emerged spontaneously in India in 1987 and became radially distributed throughout South Asia. These early organisms were associated with a single long branch and possessed mutations associated with increased bile tolerance, suggesting that the first H58 organism was generated during chronic carriage. The subsequent increased use of fluoroquinolones led to several independent mutations in gyrA, leading to decreased fluoroquinolone susceptibility. The apparent ability of H58 to acquire and maintain AMR genes continues to pose a threat, suggesting that TCVs should be deployed across South Asia to minimise the potential emergence of new drug-resistant variants. I worked with a broad range of collaborators to establish the Global Typhoid Genomics Consortium (GTGC) to encourage sharing of S. Typhi genomic data and standardised metadata, and to enable analysis and visualisation of these data in context to support public health decision-making. Here, I engaged with groups sequencing S. Typhi genomes to analyse and draft a global update paper; the final dataset contained >13,000 sequences. This work provides an updated overview of AMR and genotype distribution and illustrates key international transmission events, with the aim of informing TCV introduction decision-making and treatment guidelines. To create a translational link between laboratory scientists, genomics experts, clinicians, and policy makers, I outlined use cases for WGS in surveillance, diagnostic development, clinical management, and informing vaccine introduction as well as typhoid control. I hope to advance this work by fostering broader participation in the GTGC, and by encouraging funding support for the generation and analysis of S. Typhi WGS data. I also intend to create greater visibility for, and advocate for the value of, such data in conversations with country decision-makers and other policymakers via the WHO.

Introduction: Heterogeneity of outcomes measured in trials to improve antimicrobial stewardship (AMS) in care homes has impeded synthesising evidence and producing definitive conclusions. This thesis aimed to develop a core outcome set (COS) for use in trials focusing on improving AMS in care homes. Methods: The research presented in this thesis followed current guidelines for development of a COS (COMET) and selection of outcome measurement instruments (OMIs) for the COS (COSMIN). A systematic review was conducted to evaluate the effectiveness of randomised controlled trials (RCTs) to improve AMS in care homes and to determine outcomes reported in these studies. A qualitative study was undertaken to explore outcomes deemed important to key stakeholders comprising researchers, healthcare professionals, and family members of care home residents. Subsequently, a series of consensus procedures with relevant stakeholders were carried out to reach consensus on outcomes that should be included in the COS for use in trials aimed at improving AMS in care homes. Finally, methodology suggested by the COSMIN guidelines was followed to select OMIs available in the literature for outcomes in the COS. Results: The systematic review identified six RCTs with 28 outcomes reported and found the interventions had limited effect on improvement of antimicrobial prescribing. Interviews with 41 key stakeholders in the qualitative study revealed 49 outcomes that were deemed important to them, including 40 additional outcomes which had not been used in previous RCTs. Outcomes identified in the systematic review and the qualitative study were reviewed and refined by the research team to produce an inventory of 14 outcomes. This inventory was presented in an online Delphi survey with 82 participants from 17 different countries, followed by an online consensus exercise with 12 participants in Northern Ireland. Consensus was reached to include five outcomes in the COS, comprising two main outcomes (‘The total number of antimicrobial courses prescribed’ and ‘Appropriateness of antimicrobial prescribing’) and three optional outcomes (‘Days of therapy per 1000 resident-days’, ‘Rate of antimicrobial resistance’, and ‘Mortality related to infection’). Following the COSMIN approach, 17 potential OMIs for the COS identified in literature searches were assessed for quality of measurement properties. Three OMIs with the best quality of evidence were presented in a consensus exercise with 59 Delphi panel members from 16 different countries. Ultimately, consensus was reached to select two OMIs for two outcomes ‘The total number of antimicrobial courses prescribed’ and ‘Days of therapy per 1000 resident-days’ in the COS. No OMIs were selected for the other outcomes in the COS. Conclusion: The research described in this thesis developed a COS for use in trials aimed at improving AMS in care homes. Future studies should use this COS to measure the effectiveness and safety of AMS interventions in care homes.

Antimicrobials have been described as the "wonder drug" of the 20th century. Not only are they crucial for the treatment of infection, antimicrobials are used across the whole healthcare system including to support cancer chemotherapy, and organ transplantation. The use, including avoidable misuse and over use, of antimicrobials drives antimicrobial resistance. The World Health Organisation has described antimicrobial resistance as a serious global health problem and strategies are required to minimise overuse and misuse. Antimicrobial stewardship interventions are implemented in the community setting where it is estimated that up to one third of prescriptions are inappropriate and in the hospital setting where, at any given time, approximately one third of all patients receive antibiotics. It is important to understand what antimicrobial stewardship interventions are effective in reducing inappropriate prescribing and influence resistance without worsening clinical outcomes. Robust methods of evaluation are needed. This thesis examines the advantages and disadvantages of methods available to evaluate antimicrobial stewardship interventions. A systematic review of the quality of design, analysis and reporting in 107 studies identified in a recent Cochrane systematic review of antimicrobial stewardship interventions for hospital inpatients was performed. An uncontrolled before-after design was used to evaluate the prescribing outcome in 44 (41%) studies. Uncontrolled before-after studies do not adjust for underlying trends in the data and are at high risk of bias. There was agreement on the direction of change and statistical significance of the change in only ten (23%) uncontrolled before-after studies when compared to the results of a segmented regression re-analysis of their data. A time series method was used in 60 (56%) studies and the most commonly used analysis methods were segmented regression (70%) and Autoregressive Integrated Moving Average (ARIMA) (12%). There is no published consensus reporting guideline for interrupted time series studies but approximately half of the studies that used segmented regression or ARIMA also reported the results of an uncontrolled before-after analysis to "support" their results. The findings of this systematic review were used to develop recommendations for the design, analysis and reporting of interrupted time series studies. Analysis at national and regional health board level of a previously published national interrupted time series analysis reporting the success of two antimicrobial stewardship interventions was conducted. The interventions aimed to reduce the use of carbapenems and piperacillin/tazobactam in Scotland and the first intervention was the introduction of a treatment guideline for infection with multidrug resistant Gram negative bacteria (MDRGNB). The second intervention was a quality improvement programme involving a survey of prescribing and laboratory practice, feedback of survey results to individual health boards and discussion of results at national antimicrobial prescribing group meetings. Intervention one had an immediate impact on carbapenem prescribing but the intervention effect was not sustained, and had no impact on piperacillin/tazobactam prescribing. Intervention two had an immediate and sustained impact on both carbapenem and piperacillin/tazobactam prescribing. Analysis at individual board level showed that the intervention impact was not observed in every health board. Some boards responded to the interventions and other boards did not. It was unclear as to what characteristics of boards were associated with an intervention impact. The intervention was evaluated in line with the recommendations developed above. Multilevel models are an established method to account for any underlying hierarchical structure within aggregated data but have rarely been applied to evaluations of non-randomised healthcare interventions. A multilevel interrupted time series analysis was developed to examine general practice level effects underlying a previously published health board level analysis reporting the impact of an intervention to reduce the use of 4C (co-amoxiclav, ciprofloxacin, cephalosporins and clindamycin) antimicrobials which are associated with a higher risk of Clostridium difficile infection (CDI). Overall the intervention was successful at changing the level and trend of 4C antimicrobial prescribing at board level although each individual practice did not respond to the intervention. Practices that had a higher level of 4C antimicrobial prescribing at the start of the study period tended to have a bigger decrease in use before the intervention and a bigger decrease in level after the intervention compared to practices with lower baseline rates of prescribing. Multilevel interrupted time series models are more useful than multiple single level interrupted time series analyses to understand what practices are more likely to respond to an intervention and allows for inclusion of a larger number of subunits. Antimicrobial stewardship is a key strategy in tackling the emerging threat of antimicrobial resistance. Evaluation of antimicrobial stewardship interventions are increasingly reported in the literature but methodological flaws in the design, analysis and reporting of these interventions hinder the interpretation and wider implementation of apparently successful interventions. The number of large-scale antimicrobial stewardship programmes is rapidly growing internationally. High quality interrupted time series studies are a key component of robust evaluation, and this thesis has explored how they can best be used in this context.

Introduction: The Antimicrobial Self-assessment Toolkit for Acute NHS Trusts (ASAT) was developed by a pharmacist reference group of an Advisory Non-Departmental Public Body on Antimicrobial Resistance and Healthcare Associated Infections (ARHAI). It was developed in conjunction with the Department of Health. The primary purpose of the ASAT is to identify and to measure the methods of implementation of antimicrobial stewardship programmes in acute NHS trusts. The face validity was previously tested by ARHAI. The overall aims of this programme of work were to investigate the validity of the ASAT and to make iterative changes to improve its validity. Ethical approval was not required for this PhD project because it was categorised as service evaluation by the LREC. Also, ethical approval from the University of Manchester Research Ethics Committee was deemed unnecessary at the time of the PhD project due to the nature of the data collected. Methods: A mixed methodology approach utilising a sequential exploratory strategy was used to investigate the validity of the ASAT. This PhD project was composed of four sequential studies which resulted in iterative changes to the ASAT, that is, from ASAT v15a to ASAT v18. In Study 1, cognitive interviews were conducted with eight antimicrobial pharmacists in order to investigate the content validity of ASAT v15a. In Study 2, both cognitive interviews and semi-structured interviews were conducted with 10 clinical microbiologists in order to investigate the content validity of ASAT v16. In Study 3, Rasch modelling and analyses using the Partial Credit Model (PCM) were conducted on the responses to ASAT v17 from 33 NHS trusts across England. In Study 4, simple OLS regression analyses were conducted using the NHS trust ‘ability’ estimates or calibrations and Clostridium difficile (CDI) rates of participating NHS trusts in order to investigate model fit and the predictive validity of the ASAT. Results: The cognitive interviews conducted in study 1 indicated that AMPs encountered cognitive difficulties along the cognitive processing pathway in response to ASAT v15a. These difficulties included comprehension in 27 (32.5%) questions and response generation/formatting in 13 (15.7%) questions. Also respondents indicated that the role of clinical microbiologists in ASPs was underrepresented in ASAT v15a. The interviews conducted in Study 2 were confirmatory in nature as they reflected the findings of Study 1. For example terms such as ‘formulary’ and ‘policy’ were misinterpreted by respondents. Rasch modelling and analysis showed that there were items within ASAT v17 which were underfitting and overfitting the Partial Credit Model. Item fit was investigated after removal of these items which resulted in improved fit for domains 2 and 5. ASAT v18 was developed after these analyses and was included items that were productive for measurement. On examination of the OLS regression analyses conducted in Study 4, it was seen that there was poor model fit and very limited predictive validity of the model. Conclusion: The iterative methodology utilised to investigate the validity and subsequently improve the ASAT was effective in establishing content and construct validity. However, the predictive validity of the ASAT was limited. This may be due to the outcome variable chosen for the OLS regression modelling. A more sensitive outcome measure such as compliance to treatment or prophylaxis guidelines may have been more effective at establishing predictive validity. The findings of this programme of work highlighted that there is further work required to validate the ASAT such as the determination of the appropriate weights and scores for ASAT domains and also the determination of the appropriate outcomes measures to determine the efficacy of ASPs. It is recommended that further validity testing should be conducted before a further iteration of the ASAT is used as a set of quality standards or as a hospital benchmarking tool

Having risen as a global concern, characterization of antimicrobial resistant (AMR) bacteria within different agricultural landscapes is essential to recognize and mitigate AMR-associated global health risks. Individual animal factors such as lactation stage, parity, and previous antimicrobial use and herd-level factors like size and production type may need to be supplemented with community-level factors such as landscape diversity, density of agricultural animals, soil composition, landscape fragmentation, and connectivity to describe AMR in across agricultural landscapes. Because cephalosporins are used extensively and commensal organisms often harbor resistance in cattle, we investigated herd and community level risk factors of broad-spectrum cephalosporin resistance (BSCR) in cattle across 54 cattle farms in two Ohio counties to explore the role of community-level factors in AMR. From the summer of 2019 through the summer of 2021, interview data, pooled manure samples from cattle, and deer manure samples were collected from farms (n=54) across two counties with different landscape types in Ohio. Proportions of BSCR Enterobacteriaceae were calculated using counts of bacterial colonies grown on non-selective and selective MacConkey agar plates. Herd level predictors included in analysis were outdoor access, other livestock species’ presence on the farm, cattle imports to the farm, and herd size. Community level predictors were calculated using a centroid buffer with a 3-kilometer radius around each farm and included cropland diversity, mean dairy kernel density, mean beef kernel density, distance to nearest hospital, distance to nearest wastewater treatment plant, and proportion of broad spectrum cephalosporin resistance in deer manure collected on the property. Beta regression was used to identify significant predictors across both counties combined and stratified by county. Of all models, those including only herd size outcompeted the others in the combined analysis and in County B. In the best fit model for County C, distance to wastewater treatment was the only significant predictor and showed positive relationship with BSCR. Based on our results, community factors did not consistently predict BSCR. However, wastewater treatment plants and beef kernel density had a near-significant effect on resistance that merits further exploration. Further exploration of community and landscape factors and expanding the One Health framework in AMR research in cattle may provide additional insights.

The widespread use of antibiotics is a primary risk factor for the development of Clostridioides difficile infection (CDI), a major public health threat. In the United States (U.S.), a significant portion of antibiotics are prescribed in both the inpatient and outpatient settings. Despite efforts taken by the U.S. government and the Centers for Disease Control and Prevention (CDC) in decreasing the overall incidence of inappropriate antibiotic prescribing, these rates have not significantly changed over the past few years. While antibiotic prescribing rates have been described in the overall U.S. population, it is imperative to understand and characterize specific patient populations that are vulnerable to inappropriate antibiotic use. As antibiotics target the offending pathogens causing disease, they may also deplete important commensal bacteria that reside in the gut. Antibiotic use and overprescribing can further damage the gut microbiome, which can lead to the colonization of opportunistic pathogens like C. difficile and further, CDI. Few studies have evaluated the extent of CDI and its related outcomes in different racial/ethnic populations, as well as sex and age. Using the National Ambulatory Medical Care Survey (NAMCS), Veteran’s Health Administration (VHA), and Premier Healthcare Database (PHD), this study discovered national disparities in 1) overall and inappropriate antibiotic prescribing, 2) individual and combined antibiotic-associated CDI risk, and 3) CDI-associated health outcomes among patients of differing races/ethnicities, sex, and age groups. This study found that overall and inappropriate antibiotic prescribing rates were significant within all populations of interest. Additionally, this study showed that broad-spectrum antibiotics, like carbapenems, 3ʳᵈ, 4ᵗʰ, and 5ᵗʰ generation cephalosporins, and clindamycin, were significant risk factors for CDI. Combinations including fluoroquinolones were also shown to be significant risk factors for antibiotic CDI across all populations of interest. Lastly, patients 18 to 64 years and those 65 years and older were also shown to be significant predictors of CDI recurrence, while the same age groups and male sex were significant predictors of mortality. Findings from these analyses indicate that future studies in antibiotic and CDI-associated health disparities are needed to improve overall antimicrobial stewardship and patient outcomes.

Antimicrobial Stewardship are methods to slow the progression of antimicrobial resistance which is a global threat. Previous research has discussed the possibility for the pharmacy profession to act as a workforce to support these efforts, but prior to this further education is needed to achieve a standard of consistency around appropriate antibiotic usage. This study aims to determine if a specified educational module intervention can achieve this. Based on a review of the literature, an online survey was distributed to potential participants on a pharmacist Facebook group and within the School of Pharmacy and Medical Sciences at Griffith University. Participants (n=42) were randomly allocated into two groups (control and intervention) and asked to provide their judgement on the appropriateness of the actions taken in 10 hypothetical urinary tract infection cases of residents in aged care. Analysis of the responses demonstrated a poor level of agreement between participants, irrespective of their group allocation, and emphasised the significant lack in standardised guidelines/tools for determining appropriate antibiotic usage. The results revealed the potential issues with current educational styles, including perceived pre-existing knowledge and the factor of time in our ever increasingly busy lifestyles. This study has paved the way for further insight in this area of educational training-based research. It is suggested that the educational intervention utilised in further research be re-designed to suit the latest emerging style that is micro learning and tested with a larger sample size of final year pharmacy students where, if successful, could undertake free-of-cost AMS auditing in the form of university placement.

Background: Although children with tracheostomies frequently undergo respiratory culture testing, the frequency of antibiotic prescribing and the prevalence of respiratory culture antibiotic resistance are not known. It is also not clear if recent antibiotic use contributes to the development of antibiotic-resistant respiratory culture organisms.Objective: To quantify antibiotic prescribing, determine the prevalence of antibiotic-resistant respiratory culture organisms, and assess for an association between frequent antibiotic prescribing and the development of antibiotic-resistant organisms in children with tracheostomies. Methods: This single-center retrospective cohort study included children with tracheostomies 2 months to 18 years old from 2010-2018. Detailed demographic and antibiotic prescribing data were extracted from the medical record and combined with respiratory culture results (tracheostomy aspirate or bronchoalveolar lavage). Antibiotics were classified by spectrum using CDC definitions; resistance was defined using Clinical and Laboratory Standards Institute breakpoints. New antibiotic resistance was defined as any organism with resistance for which the same organism was previously isolated without resistance or for which the resistant organism had never been isolated in the child before. Antibiotics prescribed were summarized using the number of courses initiated and days of therapy (DOTs) of antibiotics prescribed per child per year of enrollment during the study period. Descriptive statistics were generated for respiratory culture growth and antibiotic-resistance data. A generalized estimating equation was used to assess for association between antibiotic use within 120 days and the outcomes of any or newly antibiotic-resistant organism(s) on respiratory culture while accounting for patient-level covariates and within patient clustering. Results: Children were prescribed a median of 7.1 antibiotic courses per child per year (IQR: 0.6-56.6) for a total median exposure of 50.0 DOTs per child per year (IQR: 22.6-127.0) or 137.0 DOTs per 1000 person-days (IQR: 61.9-347.9). Most (73.9%) antibiotic courses were broad-spectrum. Among 484 positive respiratory cultures, 984 organisms were isolated. 35.5% of organisms had antibiotic resistance, affecting 53.4% of children with positive cultures. Twenty percent of organisms met the definition for new antibiotic resistance. In adjusted analysis, there was no association between isolation of antibiotic resistant or newly resistant respiratory organisms and antibiotic prescribing within the preceding 120 days.Conclusions: Among children with tracheostomies, frequent antibiotic prescribing and high prevalence of antibiotic-resistant organisms were identified in respiratory cultures. Yet antibiotic prescribing within 120 days of organism isolation was not associated with new antibiotic resistance. Our findings suggest that the timing of antibiotic prescribing may not be an important factor in the development of respiratory organism antibiotic resistance.

ABSTRACT Exploring Antibiotic Resistance and the Effect of Antimicrobial Stewardship on Physicians’ and Non-Physician Prescribing Clinicians through Knowledge, Attitudes, Practices and Beliefs (KAPB) Utilizing the Social Cognitive Theory (SCT) Tamika Carty Seton Hall University, 2021 Dissertation Chair: Genevieve Pinto Zipp, PT, EdD, FNAP Background: Antibiotics are one of the greatest medical discoveries, revolutionizing the field of medicine. However, antimicrobial and antibiotic over usage has become a prevalent issue among outpatients, leading to antibiotic resistance (AR) (Ventola, 2015). As a result of, its widespread usage and associated concerns, the World Health Organization (WHO) has cited AR as a growing concern for many nations (WHO, 2015). This in turn has led to the development of management programs such as stewardships which are often led by health professionals and clinicians to address this growing issue. One would argue that stewardship programs are only as effective if those leading them are adequately prepared. Therefore, it is imperative to identify physicians’ and prescribing non-physician practitioners’ knowledge, attitudes, practices, and beliefs regarding AR and the incorporation of Antimicrobial Stewardship Programs (ASPs) to combat AR. Purpose: The purpose of this study was threefold: first to create, validate and test the reliability of the novel instrument “Antibiotic Resistance & Antimicrobial Stewardship Assessment Tool (ABRASAT)”. The second purpose was to test the valid and reliable tool in physicians’ and non-physician prescribing practitioners. The final purpose was to use the valid and reliable tool in the population of interest to understand physicians’ and non-physician prescribing practitioners’ knowledge, attitudes, practices, and beliefs with regard to antibiotic resistance and ASPs as combative method for AR. Methods: This study employed a mixed methods research approach, utilizing specifically an explanatory mixed methods design. The study can also further be categorized as non-experimental, descriptive, cross sectional, correlational and explanatory. The study consisted of two practitioner groups (physicians’ and non-physician prescribing practitioners) in which their knowledge, attitudes, practices, and beliefs were explored utilizing the ABRASAT instrument which was rooted in the available “evidenced based” literature, KAPBs theory and the Social Cognitive Theory (SCT). The ABRASAT consisted of 10 demographic questions and 25 questions relating to KAPBs, expectations, suggestions and thoughts on AR and ASPs. Data Collection and Analysis: Data was collected from both practitioner groups. Participants were recruited via social media (Facebook, WhatsApp, Twitter, Reddit and LinkedIn) and research platform (Research Gate), in addition to convenience sampling. The PI utilized descriptive statistics in addition to statistical analysis tests (ANOVA, T-Test, MANOVA and Pearson’s Correlation) to analyze quantitative data. The PI employed an inductive approach utilizing descriptive and in vivo coding to analyze qualitative data. Both the quantitative and qualitative data helped to form an inclusive overview of KAPBs of physicians’ and non-physician prescribing practitioners. Results: A total of 234 participants completed the survey. The study results for both the quantitative and qualitative data for descriptive research questions (RQ) 1 -5 resulted in the following: for RQ1, the quantitative and the qualitative data shows overall both practitioner groups had high knowledge on AR. For RQ2, the quantitative and the qualitative data shows overall both practitioner groups had high knowledge on what ASPs were. For RQ3, the quantitative and the qualitative data shows overall both practitioner groups had favorable attitudes with regards to ASPs. For RQ4, the quantitative and the qualitative data shows overall both practitioner groups had good ASP practices. For RQ5, the quantitative and the qualitative data shows overall both practitioner groups had favorable beliefs with regards to ASPs. The study results for both the quantitative and qualitative data for relational research questions (RQ) and hypotheses 6 -13 resulted in the following: for RQs 6 & 7, there was no significant difference in practitioner groups on knowledge, resulting in failure to reject the null hypothesis. For RQs 8 - 11, there was a significant difference in practitioner groups on attitudes and beliefs resulting in rejection of the null hypothesis. Finally, for RQ 12 & 13, like RQs 6 & 7, there was no significant difference in practitioner groups on practices, resulting in failure to reject the null hypothesis. While the overall instrument had a high reliability of .843 and successfully measured attitudes, practices and beliefs, knowledge had a poor reliability. While knowledge had poor reliability, it did not affect the overall reliability of the tool. However, it will need to be reassessed for future use as an individual construct. Conclusion: Though knowledge scored poorer in reliability it does not dispute the fact that physicians’ and non-physician prescribing clinicians have knowledge of AR, and displayed positive attitudes and beliefs towards ASPs. As a result, practitioners are generally in favor of ASPs yet improvements should still be made to ensure maximum benefits, thus society must continue to implement and refine these programs.

ABSTRACT OF THE DISSERTATIONApproaches for Improving Antimicrobial Stewardship ProgramsbyOlivia EllisDoctor of Philosophy in Environmental Health SciencesUniversity of California, Los Angeles, 2020Professor Hilary Godwin, Co-ChairProfessor Richard Ambrose, Co-ChairABSTRACT OF THE DISSERTATIONApproaches for Improving Antimicrobial Stewardship ProgramsbyOlivia EllisDoctor of Philosophy in Environmental Health SciencesUniversity of California, Los Angeles, 2020Professor Hilary Godwin, Co-ChairProfessor Richard Ambrose, Co-ChairThe overarching objective of the work described in this thesis is to explore approaches for improving Antimicrobial Stewardship Programs (ASPs) in clinical settings. Three discrete topics were explored: (1) using an Adenosine Triphosphate (ATP) assay to evaluate differences in bioburden and cleaning efficiency between surface types in operating rooms; (2) validating the use of a PCR-based assay to be used to tailor treatment recommendations for patients with Neisseria gonorrhoeae; and (3) investigation of antimicrobial susceptibility trends of Stenotrophomonas maltophilia in a health system over time to provide insights into whether treatment guidelines for S. maltophilia need to be changed. First, a commercial ATP detection assay was used to detect differences between the cleanliness of individual high touch surface types in operating rooms. This ATP testing assay revealed that irregularly shaped, uncovered surfaces (keyboards, overhead lights, and door handles) tend to harbor a larger bioburden than regularly shaped, covered surfaces (tables and mattresses). Additionally, surfaces were more likely to fail by ATP assay than by traditional Replicate Organism and Detection Plating (RODAC) methods. However, the majority of rooms (92%, 22/24) had least one surface that exceeded the 250 RLU threshold after turnaround cleaning via the ATP assay. Additionally, 42% (10/24) of the rooms had at least on surface that didn’t pass as clean after turnaround cleaning via the RODAC surface sample test. This study suggests that further experimentation to determine whether single use covers for irregularly shaped surfaces in operating rooms could reduce bioburden. In the second study reported in this thesis, a Real Time-Polymerase Chain Reaction (RT-PCR) assay for detecting ciprofloxacin-susceptible Neisseria gonorrhoeae was validated at three locations: Los Angeles (UCLA), San Francisco Public Health Lab (SFPHL), and Philadelphia Public Health Lab (PPHL). In this study, clinical specimens that had tested positive for Neisseria gonorrhoeae by Nucleic Acid Amplification Testing (NAAT) were further tested for susceptibility to ciprofloxacin using the validated RT-PCR assay that can detect a mutation in the gyrase A (gyrA) gene, which confers resistance to ciprofloxacin. At UCLA, 57% (n=319/557) of the specimens that could be genotyped were gyrA Wild Type (WT). At SFPHL, 72% (n=134/185) of the genotyped specimens were WT and at PPHL, 64% (27/42) were WT. The goal of this study was to validate an Antimicrobial Susceptibility Test (AST) that would allow clinicians to more rapidly tailor treatment for patients with ciprofloxacin susceptible gonorrhea. We also assessed the utility of this assay for different samples types at different laboratories. For instance, the proportion of indeterminate N. gonorrhoeae varied significantly by testing laboratory and anatomical source (p < 0.00001, χ2 = 28.7). Therefore, post hoc pairwise Fisher’s exact statistical testing was performed. There was a statistically significant number of indeterminate rectal and pharyngeal specimens between UCLA and SFPHL for (p < 0.05, P= 0.0016) as well as indeterminate urine and pharyngeal (p < 0.05, P = 0.02). The number of indeterminate pharyngeal and urine and indeterminate rectal and urine specimens also varied significantly between SFPHL and PPHL, respectively (p < 0.05, P = 0.0013 and p < 0.05, P = 0.0221).The third study reported in this thesis explores antibiotic treatment options for Stenotrophomonas maltophilia, which is an intrinsically multi-drug-resistant organism that poses an increasing threat to the health of immunocompromised patients in hospital settings. Antimicrobial susceptibility trends of Stenotrophomonas maltophilia isolates from a single health system were analyzed to elucidate possible trends in antimicrobial resistance over time. While resistance to trimethoprim-sulfamethoxazole (Bactrim) has been reported globally, 98% of all specimens tested at the health system between 2009-2018 were susceptible to Bactrim. 99% of all isolates tested were also susceptible to minocycline monotherapy. These antibiotics also show the most susceptibility when analyzed in combination (one or the other antibiotics were susceptible 100% of the time). The results of this study suggest that using larger data sets — both through combining data from multiple sites within the same network and by combining data from multiple years — may provide more robust treatment guidelines for clinicians who wish to choose the best empiric treatment for those with S. maltophilia.Taken together, these studies provide support for improving the framework of ASPs through advanced environmental monitoring, reduction in AST turn-around time, and enhanced tracking of Antimicrobial Resistance (AMR) patterns. These studies provide important insights into how to improve the management and use of antimicrobials in clinical settings.

Infections due to antibiotic-resistant Gram-negative rods (GNRs) result in high associated mortality and frequently have poor treatment options. To determine risk factors for recovery on culture of antibiotic resistant GNRs, cases were retrospectively analyzed at a major academic hospital system from 2011-2016. Three separate classes of antibiotics were studied - colistin (analyzed separately for GNRs and for Klebsiella Pneumoniae), carbapenems (analyzed separately for ertapenem and anti-Pseudomonal carbapenems), and aminoglycosides (analyzed separately for gentamicin/tobramycin and amikacin). In each case, bivariate associations were determined and used to develop multivariate models predicting the presence of resistance to the chosen antibiotic. Models had c-statistics ranging from 0.63 to 0.89. Common predictors included male gender, medical comorbidities, transfer from another healthcare facility, indicators of mechanical ventilation or tracheostomy, and recent antibiotic exposure. We then compared two strategies of treating empirically with either meropenem or colistin and performed sensitivity analyses to determine which strategy was preferable in terms of cost (low acuity) and avoidance of mortality (high acuity strategy) under several willingness-to-pay thresholds. Under base case assumptions, the meropenem-first strategy dominated in low acuity patients at a meropenem resistance rate of up to 10.9%. In high acuity patients, the colistin strategy was preferable with a willingness-to- pay per avoided death as low as $46,231; at $468,750 per avoided death, the colistin- first strategy was preferable with meropenem resistance rates as low as 5.5%. The model predicting likelihood of resistance to anti-Pseudomonal carbapenems can provide critical information in determining the optimal initial empiric antibiotic strategy.

Empiric antimicrobial therapy often consists of the combination of Gram-positive coverage with vancomycin (VAN) and Gram-negative coverage, specifically an anti-pseudomonal beta-lactam, such as piperacillin-tazobactam (PTZ). Nephrotoxicity is commonly associated with VAN therapy; however, recent reports demonstrate increasing nephrotoxicity rates among patients treated with the combination of VAN and PTZ. This study evaluated the effect of the VAN/PTZ combination on acute kidney injury (AKI), as defined by the RIFLE criteria, compared to VAN and PTZ monotherapies. Overall, 11,650 patients were analyzed, with 1,647 (14.1%) AKI cases occurring. AKI was significantly more frequent in the VAN/PTZ group (21%) compared to either monotherapy group (VAN 8.3%, PTZ 7.8%, p VAN combined with PTZ was associated with twice the odds of AKI development compared to either agent as monotherapy. This demonstrates the need for judicious use of combination empiric therapy.

This dissertation contains two types of population models with applications in conservation biology and epidemiology. In particular, it considers models for resource allocation and antimicrobial stewardship. In a population model with a parabolic differential equation and density dependent growth, we study the problem of allocating resources to maximize the net benefit in the conservation of a single species while the cost of the resource allocation is minimized. The net benefit is measured in terms of maximizing population abundance and the goal of maximizing abundance is divided between the goal of maximizing the overall abundance across space and time and the goal of maximizing abundance at the final time. We consider cases that model a fixed amount of resource as well as cases without this constraint. We regard the resource coefficient as a control and we consider cases where this coefficient varies in space and time as well as cases where it varies only in space. We establish the existence and uniqueness of the solution to the state system given a control and the existence of an optimal control. We establish the characterization of the optimal control and demonstrate uniqueness of the optimal control. Numerical simulations illustrate several cases with Dirichlet and Neumann boundary conditions. We implement an agent-based model for Clostridium difficile transmission in hospitals that accounts for several processes and individual factors including environmental and antibiotic heterogeneity in order to evaluate the efficacy of various control measures aimed at reducing environmental contamination and mitigating the effects of antibiotic use on transmission. In particular, we account for local contamination levels that contribute to the probability of colonization and we account for both the number and type of antibiotic treatments given to patients. Simulations illustrate the relative efficacy of several strategies for the reduction of nosocomial colonizations and nosocomial diseases.