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(2023)ThesisCurrent healthcare infection surveillance rarely monitors the distribution of antimicrobial resistance (AMR) in bacteria beyond clinical settings in Australia and overseas. This results in a significant gap in our ability to fully understand and manage the spread of AMR in the general community. This thesis explores whether wastewater-based monitoring could reveal geospatial-temporal and demographic trends of antibiotic-resistant bacteria in the urban area of Greater Sydney, Australia. Untreated wastewater from 25 wastewater treatment plants sampled between 2017 and 2019 consistently contained extended-spectrum β-lactamases-producing Enterobacteriaceae (ESBL-E) isolates, suggesting its endemicity in the community. Carbapenem-resistant Enterobacteriaceae (CRE), vancomycin-resistant enterococci (VRE), and methicillin-resistant Staphylococcus aureus (MRSA) isolates were occasionally detected. Demographic and healthcare infection-related factors correlated with the ESBL-E load, and demographic variables influenced the VRE load. In contrast, the healthcare infection-related factor mainly drove the CRE load. These findings demonstrate the potential of wastewater-based surveillance to understand the factors driving AMR distribution in the community. The subsequent thesis work covers the genomic characterisation of selected ESBL-E and CRE wastewater isolates to reveal their nature, origin, and underlying resistance mechanisms. Phylogenetic analysis showed that Escherichia coli isolates were related to high-risk human-associated pandemic clones and non-human-associated clones. The Klebsiella pneumoniae and K. variicola isolates were related to globally disseminated and emerging human-associated clones, and some were detected for the first time in Australia. Genomic analysis also indicated novel resistance mechanisms against nitrofurantoin in E. coli, and against piperacillin/tazobactam and ticarcillin/clavulanic acid in Klebsiella isolates. The virulence gene content indicated that some E. coli and Klebsiella isolates were likely associated with infections, while the asymptomatic carriage was suggested for other isolates. These results demonstrate a clear potential for wastewater-based surveillance to monitor the emergence and dissemination of resistance in non-clinical isolates, and in particular, isolates from the community and non-human sources. The findings of this study can complement healthcare infection surveillance to inform management strategies to mitigate the emergence and dissemination of AMR and important human pathogens in the general community.
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(2020)ThesisPseudomonas aeruginosa causes both contact lens and non-contact lens-related keratitis (corneal infection). This opportunistic bacterium naturally has the ability to resist the mechanism of action of many antibiotics which are used for treatment. P. aeruginosa resistance patterns and the mechanism of resistance in isolates from keratitis are not well understood. This thesis described the phenotypic and genotypic patterns of antimicrobial resistance and compared these between ocular isolates of P. aeruginosa from Australia (contact lens) and India (non-contact lens). Changes in the antimicrobial susceptibility between isolates over time were also analysed. Susceptibility to antibiotics, multipurpose disinfecting solutions and disinfectants was analysed for twenty-seven Australian isolates from contact lens-related keratitis and forty non-contact lens-related isolated from India. The whole genomes of fourteen Australian (historical and recent) and twelve Indian isolates were sequenced using Illumina® MiSeq®. Computational analysis of the genomes was performed to analyse their core and pan genomes and these were examined for the presence of acquired resistance genes, virulence genes, gene mutations, and these compared to their phenotypic resistance to antibiotics. Indian isolates possessed large pan genomes with more acquired resistance (30) genes and larger numbers of genetic variations. The Indian isolates contained clones of three sequence types ST308, ST316 and ST491, whereas Australian isolates contained only one sequence type ST233. Isolates with larger gene variations had mutations in the DNA mismatch repair system. Most multi-drug resistant Indian (non-contact lens) isolates were exoU +. Indian isolates had large accessory genes compared to Australian isolates and this increased the pan genome size of the Indian isolates. The number of core genome mutations were larger in the Indian isolates a median of 50006 (IQR=26967-50600) compared to Australian isolates a median of 26317 (IQR=25681-33780). There were differences between isolates from Australia and India with respect to their antibiotic resistance and associated genes. Indian strains had more genetic diversity and were multi-drug resistant. However, there was no evidence of substantial genetic or phenotypic changes within isolates from their respective countries.
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(2023)ThesisThe transmission of dengue fever is already being impacted by the changing climate. This phenomenon poses a considerable public health challenge for countries like Bangladesh, where regular seasonal outbreaks of dengue fever are already prevalent. This thesis aims to investigate how changing climate will impact long-term dengue epidemiology in Bangladesh as a whole and more specifically in Dhaka, the capital city of the country over the 21st Century. Several statistical models have been developed to estimate the short-term risk of dengue outbreaks as a function of climate variables but the underlying causal relationships that contribute to dengue transmission and the observed patterns of dengue epidemiology are not accounted for in these models. Initially, we determined the suitability of using climate projections for 21st Century from Global Climate Models (GCM) to assess the impact of changing climate on future dengue risk in Bangladesh setting. We then used the GCM output to assess the impact of changing climate on one aspect of dengue transmission by calculating the change in vectorial capacity (VC) of Aedes aegypti mosquitoes at a seasonal level for all regions in Bangladesh under two future climate change scenarios. The analysis indicates that the annual VC in all divisions of Bangladesh is expected to consistently exceed the threshold for dengue transmission throughout the 21st Century, regardless of the climate change scenarios considered. However, during the latter half of the century, there is a projected decline in the annual VC compared to the period between 1986 and 2005. Despite this, monthly VC variations reveal that the winter/dry season could see an increase in VC, potentially leading to a longer dengue season with outbreaks occurring year-round. The application of the VC calculation is limited by the fact that it only accounts for temperature and does not consider the impact of other climate variables such as rainfall and humidity, as well as the role of host immunity. To incorporate these factors, we then developed a mechanistic dengue transmission model that considers the influence of temperature, rainfall, and humidity on the transmission of two different dengue serotypes among human hosts and mosquito vectors. We calibrated and validated the model against observed dengue epidemiology data from Dhaka for 1995-2014 using observed climate data as input. We then used GCM output for two future climate change scenarios to simulate the model for two future periods (2030-2049 and 2080-2099) to assess the potential changes in dengue epidemiology in Dhaka. When utilizing observed climate data and climate projections from GCMs specific to Dhaka, our mechanistic model reasonably reproduced the observed dengue epidemiology in Dhaka between 1995 and 2014 in terms of the recurring annual dengue outbreaks, the seasonal pattern of transmission, and the increase in seroprevalence. Simulations for 2030-2049 indicate that dengue transmission is likely to increase regardless of the combination of initial seroprevalence, GCM, and climate change scenario, when compared to the baseline period of 1995-2014. However, for the period 2080-2099, the projected changes in dengue transmission vary, with some combinations of initial seroprevalence, GCM, and climate change scenario predicting a slight increase and others indicating a decrease. The simulations also suggest the seasonal pattern of dengue infections is likely to change in future, with more pronounced change projected for the 2080-2099 period, resulting in a lengthening of the dengue season. The primary contribution of this thesis is to present a modelling framework that considers the anticipated changes in the future climate and immunological factors to project the long-term risk of dengue epidemics. The model is flexible enough to be adapted to other settings and other pathogens transmitted by the same mosquito vector.