Abstract
The emergence of bacterial resistance to last-resort drugs like Carbapenems across various environments has led to increased surveillance of resistant bacteria in meat-producing animals. This thesis aims to gather knowledge on these emerging resistant bacteria to support the design of an active surveillance protocol. Chapter 2 focuses on a quantitative risk assessment of introducing Carbapenemase-Producing Enterobacteriaceae (CPE) into livestock, using a stochastic model to estimate the likelihood and impact of potential harm. The assessment process includes defining hazards, identifying vulnerable populations, and quantifying the probability of CPE-resistant bacteria occurring in livestock. Chapter 3 presents a transmission experiment comparing ESBL with CPE in broiler chickens, utilizing Bayesian statistics to address limitations in detecting transmission moments. Chapter 4 conducts a meta-analysis of individual patient data from multiple studies, analyzing transmission rates using a Bayesian hierarchical model. This analysis provides insights into the transmission dynamics of resistant bacteria and the impact of various factors. Chapter 5 highlights simulation modeling as a tool for understanding the spread of antibiotic-resistant bacteria and evaluating intervention strategies, offering insights into the dissemination and persistence of resistant bacteria within livestock populations
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 30 Sept 2024 |
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Publication status | Published - 30 Sept 2024 |
Keywords
- Antimicrobial resistance
- Carbapenems
- livestock
- longitudinal study
- transmission dynamics
- simulation study
- Bayesian inferance
- Risk assessment