Antibiotic resistant Gram-negative bacteria in long-term care facilities, an epidemiological and dynamic modelling study

Tackling antimicrobial resistance (AMR) is a national and global priority. Despite this, much of our understanding of the epidemiology and transmission of AMR outside the hospital, and thus, how we might control it, remains limited. Long term care facilities (LTCFs) play an important role in the care of older people. However, there have been few studies of the epidemiology and transmission of AMR in this setting. LTCF residents present with frequent co-morbidities which increase their risk of hospitalisation and of AMR infection. LTCFs also offer opportunities for transmission of AMR strains due to the long lengths of stay of residents and the lack of strictly applied infection control measures. This thesis focuses on urinary tract infections (UTIs), one of the most common bacterial infections in LTCFs, hospitals and the community. I first present a systematic review of mathematical models of infectious disease transmission set in LTCFs and a critical review of mathematical models evaluating interventions against AMR bacteria in LTCFs. A checklist for good quality models in this area is proposed. Next, using data from routinely collected microbiology samples, the frequency of AMR in urinary tract E. coli and Klebsiella was compared in LTCF residents with that in older people living in their own homes. Residents of LTCFs had more than four times the rate of E. coli and Klebsiella UTI caused by antibiotic-resistant bacteria compared with those living in the community. The seasonality of UTI consultations was also assessed. A September to November peak in UTI consultation incidence was observed for ages 14-69. This seasonality progressively faded in older age groups and no seasonality was found in individuals aged 85 and over. Finally, a stochastic compartmental mathematical model was developed to explore the transmission of trimethoprim-resistant E. coli in LTCFs. Different treatment, importation and transmission scenarios were addressed

Understanding the impact of interventions to prevent antimicrobial resistant infections in the long-term care facility; a review and practical guide to mathematical modelling

(1) To systematically search for all dynamic mathematical models of infectious disease transmission in long-term care facilities (LTCFs); (2) to critically evaluate models of interventions against antimicrobial resistance (AMR) in this setting; and (3) to develop a checklist for hospital epidemiologists and policy makers by which to distinguish good quality models of AMR in LTCFs. The CINAHL, EMBASE, Global Health, MEDLINE, and Scopus databases were systematically searched for studies of dynamic mathematical models set in LTCFs. Models of interventions targeting methicillin-resistant Staphylococcus aureus in LTCFs were critically assessed. Using this analysis, we developed a checklist for good quality mathematical models of AMR in LTCFs. Overall, 18 papers described mathematical models that characterized the spread of infectious diseases in LTCFs, but no models of AMR in gram-negative bacteria in this setting were described. Future models of AMR in LTCFs require a more robust methodology (ie, formal model fitting to data and validation), greater transparency regarding model assumptions, setting-specific data, realistic and current setting-specific parameters, and inclusion of movement dynamics between LTCFs and hospitals. Mathematical models of AMR in gram-negative bacteria in the LTCF setting, where these bacteria are increasingly becoming prevalent, are needed to help guide infection prevention and control. Improvements are required to develop outputs of sufficient quality to help guide interventions and policy in the future. We suggest a checklist of criteria to be used as a practical guide to determine whether a model is robust enough to test policy