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Development of a cardiometabolic disease policy model: leveraging the role of UK primary care data
Get PDFCardiometabolic diseases, including type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD), pose a growing public health burden globally and in the UK. Effective policy responses require robust modeling tools to evaluate the long-term clinical and economic impacts, particularly for preventative interventions. This thesis presents the development of a cardiometabolic disease (CMD) policy model designed to simulate the natural history and progression of major cardiometabolic conditions.
The model adopts a multi-state survival analysis model with semi-Markov structure, by utilising real-world patient-level data from the Clinical Practice Research Datalink (CPRD) Aurum, linked with Hospital Episode Statistics (HES), mortality records, and the Index of Multiple Deprivation (IMD). It estimates transition probabilities across key health states: disease-free, T2DM, first and recurrent cardiovascular events, and death.
Both parametric and flexible survival models are explored to estimate transition risks and enable long-term extrapolation. The model also incorporates time-dependent covariates, allowing risks to evolve as patient characteristics change. Model performance is assessed through rigorous diagnostics and validation.
A key feature of this model is its hybrid approach, which combines cohort-based transitions with microsimulation components. This structure captures both population-level trends and individual-level heterogeneity, enhancing the model’s flexibility and relevance for policy analysis. Model outputs include life-years, quality-adjusted life years (QALYs), and healthcare costs, with also the extended ability to assess outcomes across different ethnic groups and explore health inequalities.
This CMD policy model offers a flexible, real-world-informed decision-support tool for policymakers, health economists, and public health planners. Its hybrid structure provides a foundation for supporting the long-term clinical and economic impacts of interventions to reduce the burden of cardiometabolic diseases in the UK population
Local solubility of a family of quadric surfaces over a biprojective base
Get PDFWe prove an asymptotic formula for the number of everywhere locally soluble diagonal quadric surfaces 𝑦₀𝑥²₀+𝑦₁𝑥²₁+𝑦₂𝑥²₂+𝑦₃𝑥²₃=0 parametrised by points 𝑦 ∈ ℙ³ (ℚ) lying on the split quadric surface 𝑦₀𝑦₁ = 𝑦₂𝑦₃ which do not satisfy −𝑦₀𝑦₂ = □ nor −𝑦₀𝑦₃ = □. Our methods involve proving asymptotic formulae for character sums with a hyperbolic height condition and proving variations of large sieve inequalities for quadratic characters
How can reinterpretation of digitised works of art facilitate polyvocality online?
No full textAbstract not currently available
‘Certainly not a philosophy that was likely to appeal to the experience, morals, and beliefs, of the practical Scot’: a survey of Medieval - Renaissance magic and esotericism in Scotland prior to 1560
No full textAbstract not currently available
Enhancing searches for gravitational waves from short transient bursts
Get PDFThe advanced detector era of gravitational wave (GW) searches has been highly successful in the detection of compact binary coalescence (CBC) events throughout three complete observing runs, while more detections are expected with the fourth run currently underway. As the search for GWs continues with increased detector sensitivities, it is expected for sources beyond CBCs to be detected. One example of an expected yet so far undetected source are short transient GW bursts; this signal type encapsulates a wide range of astrophysical sources with varying signal morphologies. The detection of transient bursts often relies upon search algorithms which hold minimal assumptions on a given signals morphology, referred to as un-modelled searches. One particular un-modelled search is the coherent WaveBurst (cWB) algorithm, which bases the detection of GWs upon excess coherent energy across a network of detectors. The weakly-modelled nature of cWB makes it sensitive to a wide range of transient GW signals, however also makes it highly susceptible to spurious transient noise artefacts known as glitches. Glitches directly effect the detection capabilities of searches, and the employment of noise mitigation techniques within searches is required to separate them from GW signals. The development of such noise mitigation techniques is crucial in optimising the sensitivities of searches as new detector upgrades introduce new sources of glitches into the data. The work presented here explores the enhancement of Gaussian mixture modelling (GMM) as a noise mitigation tool to the cWB algorithm in the search for short-duration GW transients. GMM allows for the populations of noise and signal to be modelled over a set of representative attributes, aiding in the classification of GW signals against glitches.
Investigations into various aspects of model training are executed in order to increase the reliability of the GMM methodology. Specifically, the analysis is made robust to a wide range of signal morphologies by removing a bias in the training set, and new approaches to optimise models are chosen to increase the accuracy of the analysis. Through initial tests, we show that the modification the GMM methodology also results in increased sensitivity to a selection of expected burst sources. Following this result, the performance of the enhanced cWB+GMM algorithm is further evaluated through extensive testing with data from the third LIGO-Virgo-KAGRA (LVK) observing run. For both 2- and 3-detector networks, we show that the GMM methodology obtains significant sensitivity improvements for Gaussian pulse and cosmic string waveforms compared to those obtained by previous cWB post-production methodologies. Thus, we demonstrate the ability of GMM to effectively mitigate the dominant source of noise for un-modelled searches: blip glitches. Through these tests it also shown that with the GMM methodology, the 3-detector network achieves sensitivities similar to those of the 2-detector network, which has not previously been possible with the cWB algorithm due to high glitch rates. Further comparison of the GMM method with other post-production pipelines highlight that it is competitively sensitive to wide range of expected burst sources while making minimal assumptions on morphology, proving it is beneficial to apply it in the generic search for GW transients.
We employ the cWB+GMM pipeline in the offline all-sky search for short-duration, low-frequency GWs in the LVK fourth observing run, presenting details on search configuration investigations and results with increased sensitivities. The newly enhanced GMM-based search detects 13 confident CBC events. The loudest non-CBC event is observed with significance of inverse false alarm rate (iFAR) equal to 1.75 years, however initial investigations indicate that this is likely an artefact of noise. Despite no confident burst events being detected, we show that the GMM observes significant sensitivity improvements across the short-duration low-frequency parameter space compared to those obtained in O3. Additionally, the implementation as an offline search highlighted many avenues for future improvements, with insight into GMM behaviour and initial investigations into dominant sources of glitches.
We extend the use of GMM as a noise mitigation tool in GW searches by applying it in a targeted sensitivity study for parabolic radiation-driven capture systems. The approach of a targeted GMM model is introduced, and performance is tested against against standard and generic GMM post-production approaches. We demonstrate that the use of a targeted GMM has the potential to significantly increase sensitivities, however further investigations into the construction of an optimised training set will refine this application further. Through this study we also conclude that high mass radiation-driven black hole capture systems with equal mass ratio and initial angular momentum of 0.9 may be detected with sensitive distance of 1.74Gpc, however upper limits of rates we can achieve with current sensitivities are not competitive with literature.
Overall, the development and extensive testing of the GMM post-production methodology to cWB proves that it is an effective technique in the mitigation of the dominant source of transient noise in un-modelled searches, increasing search sensitivities to expected burst sources across the parameters space. Furthermore, it is shown that the application to a 3-detector network and targeted searches for transient burst sources are promising implementations for the future
Genetic analysis of the rabies virus
Get PDFRabies is a fatal disease caused by a negative-strand RNA virus with a genome size of approximately 12 kilobases. Rabies kills an estimated 60,000 people per year, most of whom would have been bitten by a rabid domestic dog. In recent years whole genome sequencing of the rabies virus has become more accessible through the development of portable sequencing technologies and inexpensive protocols, which has led to an increase in the amount of publicly available genomic data, and in the capacity to rapidly acquire sequence data from new rabies outbreaks. In this thesis I aim to use rabies genomic and genetic data to investigate how rabies evolves, and how to best use this data to meet the global goal of achieving zero human rabies deaths by 2030. I developed a simulation framework consisting of an existing branching process epidemiological model and a novel mutation model to generate synthetic rabies sequences associated with known underlying transmission dynamics. In chapter 2 I used this framework to investigate whether the lack of temporal signal required to conduct Bayesian phylogenetic analyses on rabies sequence/added datasets could be due to rabies’ variable incubation period lengths. I found that at substitution rates comparable to rabies’, it is not possible to distinguish root-to-tip divergence plots for synthetic genomes generated using a per-unit time or pergeneration model of substitution; it is possible, however, at rates more representative of other RNA viruses, due to distinctive “ridges” that form under the per-generation model after unusually long or short incubation periods. I conclude that rabies’ slow evolution is more likely to be the cause of the lack of temporal signal than its variable incubation periods, but that thinking about evolution on a per-generation scale could be useful in certain contexts. Existing methods of estimating outbreak sizes, such as serological surveys and randomised testing, are unsuitable for estimating rabies outbreak sizes due to the fatality of the virus and the testing method respectively. In chapter 3, using the same simulation framework as in chapter 2, I developed a novel method of estimating outbreak sizes from phylogenetic trees which is simple, computationally inexpensive and takes advantage of the genomic data already usually gathered as part of the outbreak surveillance. I apply this method to a new outbreak of rabies in the Romblon province of the Philippines, confirming that there has been widespread undetected transmission, but that the outbreak surveillance was perhaps more effective at detecting cases than is usual for a rabies outbreak. In chapter 4 I used publicly available rabies sequence data to investigate to what extent codon usage was biased between different host-species-specific minor clades, and whether these differences were evidence of adaptation by the virus to the host. I found that while there was little evidence of the virus adapting its codon usage specifically to new host species, differences exist in RABV’s CpG content which suggest that bat- and carnivore-associated rabies clades are under differing levels of selection pressure from the host immune system on CpG dinucleotides. Together these findings demonstrate that genomic data is a valuable resource that can be used to inform outbreak responses and tell us about how rabies evolves and interacts with its wide range of hosts
A comparative analysis of the status of SOEs in Investor-State Dispute Settlement (ISDS), state immunity, and WTO anti-dumping and countervailing duties
Get PDFThis thesis discusses how the status of state-owned enterprises is identified in the fields of investor-state dispute settlement (ISDS), state immunity, and WTO anti-dumping and countervailing duties, and whether there is a need for a unified rule. The aim is to clarify under which circumstances state-owned enterprises in international activities may be considered to represent state proxies. Accordingly, the thesis analyses the existing rules in these three fields and discusses the question of whether the status of state-owned enterprises is determined by their structure or by their behaviour. In addressing the differences in rules across these three fields, the thesis then explores the issue of whether international law needs to apply a uniform rule in determining the status of state-owned enterprises.
This analysis goes beyond previous approaches which only examined rules within a single field, by providing a comparative discussion of rules in determining the status of an entity in international law across three different fields. The key point of the thesis is that there are both commonalities and differences in the rules governing the status of state-owned enterprises in these three fields, which arise from their distinct legislative objectives. In addition, due to the fragmentation of international law and the subjectivity of interpretation of international law, creating a uniform rule is not deemed necessary. According to the comparative study conducted across the three areas, this thesis suggests that rules from the state immunity field can be selectively applied to the other two areas. However, it is essential to consider their adaptability to the specific rules of each area
Science education, curriculum and pedagogy in 21st Century Kenya: an investigation in Laikipia
Get PDFPrompted by my lived experiences as a child born and raised in remote Laikipia county, a rural setting in Kenya this qualitative study explores the extent to which secondary school teachers and students of science in a secondary school in Kenya (Laikipia County) integrate indigenous science knowledge (ISK) and mother tongue language into the science curriculum to make science lessons more interesting and meaningful to learners. Science is an important curricular area and an area that Kenya is keen to grow and develop and yet studies show that Kenyan students fail to choose science at secondary school level. The school curriculum and teachers play a significant role in controlling what happens in classrooms in Kenya and although there is a set curriculum to be covered, teachers can decide how they will communicate to their students. While there is a focus on school science knowledge (SSK) teachers, students and policy recognise the part that indigenous science knowledge (ISK) can play in education for sustainable development. However, opportunities to include ISK are sometimes limited or thwarted by circumstances.
Qualitative data was collected through semi-structured interviews with teachers and the headteacher and focus groups for students in the school. Participants gave their insights into, and experiences of, learning and teaching in science using indigenous perspectives and languages. Students were purposively selected while due to the relatively small size of the school all science teachers took part. The science syllabus and policy documents provided information about the how and what of learning and teaching in science classrooms and provided a context for the primary data gathered from the interviews. The views of participants provided thick and in-depth narratives. The findings showed differences and similarities in participants’ views, experiences and they highlight doubts, worries and practical concerns around the use of indigenous perspectives in their Kenyan science classroom. Participants showed an understanding of ISK and its problem-solving benefits at home and the significant role it could play in learning science knowledge. In this study teachers and students thought that participative methods such as class discussions could promote creativity and innovation, and in the process create an understanding and appreciation of indigenous knowledge and its role in education for sustainability. Notwithstanding, participants also highlighted perennial issues such as poverty and a lack of resources and funding as impacting on education and in particular science education. While development since my own time in school seemed limited, there were glimmers of hope that the future could be different. The general positive view of ISK from the participants of this study suggest that it is an area of further ongoing development, particularly in regard to science education for sustainable development. The students in this study also shared important ideas about student voice and participation. Their understanding and appreciation of ISK, indigenous languages and culture in Kenyan science lessons could serve as a starting point for consideration and development of the role of ISK in sustainability and science education in rural settings
Modelling the dynamic distribution of geochemical signatures in shallow continental magma bodies
Get PDFContinental arcs are critical geological settings due to their role in recycling the Earth’s crust through subduction and magma generation. These regions are characterised by intense volcanic activity and host some of the world’s largest ore deposits. Extensive studies of continental arcs have produced large geochemical databases and widely accepted conceptual models. Despite this wealth of data, there is still ongoing debate within the literature on which processes are the dominant control on the diverse range of geochemical signatures observed in continental arcs. This ongoing debate is partially due to these systems being incredibly complex and their spatially and temporally inaccessible nature. This study models the uppermost sections of volcanic plumbing systems, located just below the volcanic edifices, to explore the dynamics that govern magma mixing and fractional crystallisation within these shallow magma bodies. The aim is to understand how these processes affect the geochemical signatures within shallow systems and to determine whether these signatures can be preserved over time. A twodimensional (2D) computational numerical model was employed to simulate shallow melt-rich magma bodies, tracking fluid dynamics, thermochemical evolution, and geochemical changes. Another objective of this research was to determine if two mixing end-member compositions can be reconstructed after magma mixing and fractionation. Machine learning techniques were utilised to reconstruct the initial input compositions. The results of this study show that the volatile content is the primary control of the system dynamics. Lower volatile contents led to faster crystallisation and cooling, while higher volatile contents in the recharging magma triggered vigorous convection, mixing and homogenising of the initial geochemical signatures. The machine learning analysis revealed that a single overturn event could overwrite the original geochemistry. However, it was possible to backtrack to the original geochemical signatures in the simulations without overturn. This study highlights the importance of numerical modelling for testing hypotheses about active volcanic systems. Numerical modelling combined with machine learning could help improve field sampling strategies by identifying zones where parental geochemical signatures are most likely to be preserved within a system
Metabolic adaptations of stem cells and their niche during intestinal regeneration
No full textAbstract not currently available
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