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A classical hypothesis test for assessing the homogeneity of disease transmission in stochastic epidemic models (2024)
Journal Article
Aristotelous, G., Kypraios, T., & O'Neill, P. D. (2024). A classical hypothesis test for assessing the homogeneity of disease transmission in stochastic epidemic models. Scandinavian Journal of Statistics, https://doi.org/10.1111/sjos.12743

This paper addresses the problem of assessing the homogeneity of the disease transmission process in stochastic epidemic models in populations that are partitioned into social groups. We develop a classical hypothesis test for completed epidemics whi... Read More about A classical hypothesis test for assessing the homogeneity of disease transmission in stochastic epidemic models.

Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting (2023)
Journal Article
Pople, D., Kypraios, T., Donker, T., Stoesser, N., Seale, A. C., George, R., …Robotham, J. (2023). Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting. BMC Medicine, 21(1), Article 492. https://doi.org/10.1186/s12916-023-03007-1

Background Globally, detections of carbapenemase-producing Enterobacterales (CPE) colonisations and infections are increasing. The spread of these highly resistant bacteria poses a serious threat to public health. However, understanding of CPE trans... Read More about Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting.

Accelerating Bayesian inference for stochastic epidemic models using incidence data (2023)
Journal Article
Golightly, A., Wadkin, L. E., Whitaker, S. A., Baggaley, A. W., Parker, N. G., & Kypraios, T. (2023). Accelerating Bayesian inference for stochastic epidemic models using incidence data. Statistics and Computing, 33(6), Article 134. https://doi.org/10.1007/s11222-023-10311-6

We consider the case of performing Bayesian inference for stochastic epidemic compartment models, using incomplete time course data consisting of incidence counts that are either the number of new infections or removals in time intervals of fixed len... Read More about Accelerating Bayesian inference for stochastic epidemic models using incidence data.

Bayesian Model Choice for Directional Data (2023)
Journal Article
Fallaize, C. J., & Kypraios, T. (2024). Bayesian Model Choice for Directional Data. Journal of Computational and Graphical Statistics, 33(1), 25-34. https://doi.org/10.1080/10618600.2023.2206076

This article is concerned with the problem of choosing between competing models for directional data. In particular, we consider the question of whether or not two independent samples of axial data come from the same Bingham distribution. This is not... Read More about Bayesian Model Choice for Directional Data.

A multistate modeling approach to investigate long-term effects of claw horn disruption lesions and early lesion development in dairy cows (2023)
Journal Article
Thomas, M., Green, M., Kypraios, T., & Kaler, J. (2023). A multistate modeling approach to investigate long-term effects of claw horn disruption lesions and early lesion development in dairy cows. Journal of Dairy Science, https://doi.org/10.3168/jds.2021-21749

Claw horn disruption lesions (CHDL) are a leading cause of lameness in dairy cattle, and the development, effect, and pathology of these lesions remains an open area of interest within dairy cattle health. Current literature typically attempts to mea... Read More about A multistate modeling approach to investigate long-term effects of claw horn disruption lesions and early lesion development in dairy cows.

Posterior Predictive Checking for Partially Observed Stochastic Epidemic Models (2022)
Journal Article
Aristotelous, G., Kypraios, T., & O'Neill, P. D. (2023). Posterior Predictive Checking for Partially Observed Stochastic Epidemic Models. Bayesian Analysis, 18(4), 1283-1310. https://doi.org/10.1214/22-ba1336

We address the problem of assessing the fit of stochastic epidemic models to data. Two novel model assessment methods are developed, based on disease progression curves, namely the distance method and the position-time method. The methods are illustr... Read More about Posterior Predictive Checking for Partially Observed Stochastic Epidemic Models.

Mid-infrared spectral classification of endometrial cancer compared to benign controls in serum or plasma samples (2021)
Journal Article
Mabwa, D., Gajjar, K., Furniss, D., Schiemer, R., Crane, R., Fallaize, C., …Phang, S. (2021). Mid-infrared spectral classification of endometrial cancer compared to benign controls in serum or plasma samples. Analyst, 146(18), 5631-5642. https://doi.org/10.1039/D1AN00833A

This study demonstrates a discrimination of endometrial cancer versus (non-cancerous) benign controls based on mid-infrared (MIR) spectroscopy of dried plasma or serum liquid samples. A detailed evaluation was performed of four discriminant methods (... Read More about Mid-infrared spectral classification of endometrial cancer compared to benign controls in serum or plasma samples.

Predator size affects the intensity of mutual interference in a predatory mirid (2020)
Journal Article
Papanikolaou, N. E., Dervisoglou, S., Fantinou, A., Kypraios, T., Giakoumaki, V., & Perdikis, D. (2020). Predator size affects the intensity of mutual interference in a predatory mirid. Ecology and Evolution, 11(3), 1342-1351. https://doi.org/10.1002/ece3.7137

1. Interference competition occurs when access to an available resource is negatively affected by interactions with other individuals, where mutual interference involves individuals of the same species. The interactive phenomena among individuals may... Read More about Predator size affects the intensity of mutual interference in a predatory mirid.

Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole‐genome‐sequence data (2020)
Journal Article
Cassidy, R., Kypraios, T., & O'Neill, P. D. (2020). Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole‐genome‐sequence data. Statistics in Medicine, 39(12), 1746-1765. https://doi.org/10.1002/sim.8510

Whole genome sequencing of pathogens in outbreaks of infectious disease provides the potential to reconstruct transmission pathways and enhance the information contained in conventional epidemiological data. In recent years there have been numerous n... Read More about Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole‐genome‐sequence data.

Pair-based likelihood approximations for stochastic epidemic models (2019)
Journal Article
Stockdale, J. E., Kypraios, T., & O'Neill, P. D. (2021). Pair-based likelihood approximations for stochastic epidemic models. Biostatistics, 22(3), 575-597. https://doi.org/10.1093/biostatistics/kxz053

Fitting stochastic epidemic models to data is a non-standard problem because data on the infection processes defined in such models are rarely observed directly. This in turn means that the likelihood of the observed data is intractable in the sense... Read More about Pair-based likelihood approximations for stochastic epidemic models.

A statistical view on calcium oscillations (2019)
Journal Article
Powell, J., Falcke, M., Skupin, A., Bellamy, T., Kypraios, T., & Thul, R. (2019). A statistical view on calcium oscillations. Advances in Experimental Medicine and Biology, 1131, 799-826. https://doi.org/10.1007/978-3-030-12457-1_32

Transient rises and falls of the intracellular calcium concentration have been observed in numerous cell types and under a plethora of conditions. There is now a growing body of evidence that these whole-cell calcium oscillations are stochastic, whic... Read More about A statistical view on calcium oscillations.

A comparative study of estimation methods in quantum tomography (2019)
Journal Article
Acharya, A., Kypraios, T., & Guta, M. (2019). A comparative study of estimation methods in quantum tomography. Journal of Physics A: Mathematical and Theoretical, 52(23), 1-36. https://doi.org/10.1088/1751-8121/ab1958

As quantum tomography is becoming a key component of the quantum engineering toolbox, there is a need for a deeper understanding of the multitude of estimation methods available. Here we investigate and compare several such methods: maximum likelihoo... Read More about A comparative study of estimation methods in quantum tomography.

Bayes Factors for Partially Observed Stochastic Epidemic Models (2018)
Journal Article
Alharthi, M., Kypraios, T., & O'Neill, P. D. (2019). Bayes Factors for Partially Observed Stochastic Epidemic Models. Bayesian Analysis, 14(3), 927-956. https://doi.org/10.1214/18-BA1134

We consider the problem of model choice for stochastic epidemic models given partial observation of a disease outbreak through time. Our main focus is on the use of Bayes factors. Although Bayes factors have appeared in the epidemic modelling literat... Read More about Bayes Factors for Partially Observed Stochastic Epidemic Models.

Optimal experimental design for predator–prey functional response experiments (2018)
Journal Article
Zhang, J. F., Papanikolaou, N. E., Kypraios, T., & Drovandi, C. C. (2018). Optimal experimental design for predator–prey functional response experiments. Interface, 15(144), https://doi.org/10.1098/rsif.2018.0186

Functional response models are important in understanding predator–prey interactions. The development of functional response methodology has progressed from mechanistic models to more statistically motivated models that can account for variance and t... Read More about Optimal experimental design for predator–prey functional response experiments.

A unified stochastic modelling framework for the spread of nosocomial infections (2018)
Journal Article
López-García, M., & Kypraios, T. (2018). A unified stochastic modelling framework for the spread of nosocomial infections. Interface, 15(143), Article 20180060. https://doi.org/10.1098/rsif.2018.0060

Over the last years, a number of stochastic models have been proposed for analysing the spread of nosocomial infections in hospital settings. These models often account for a number of factors governing the spread dynamics: spontaneous patient coloni... Read More about A unified stochastic modelling framework for the spread of nosocomial infections.

Bayesian nonparametrics for stochastic epidemic models (2018)
Journal Article
Kypraios, T., & O'Neill, P. D. (2018). Bayesian nonparametrics for stochastic epidemic models. Statistical Science, 33(1), https://doi.org/10.1214/17-STS617

The vast majority of models for the spread of communicable diseases are parametric in nature and involve underlying assumptions about how the disease spreads through a population. In this article we consider the use of Bayesian nonparametric approach... Read More about Bayesian nonparametrics for stochastic epidemic models.

Efficient SMC2 schemes for stochastic kinetic models (2017)
Journal Article
Golightly, A., & Kypraios, T. (2018). Efficient SMC2 schemes for stochastic kinetic models. Statistics and Computing, 28(6), 1215-1230. https://doi.org/10.1007/s11222-017-9789-8

Fitting stochastic kinetic models represented by Markov jump processes within the Bayesian paradigm is complicated by the intractability of the observed-data likelihood. There has therefore been considerable attention given to the design of pseudo-ma... Read More about Efficient SMC2 schemes for stochastic kinetic models.

A rare event approach to high-dimensional approximate Bayesian computation (2017)
Journal Article
Prangle, D., Everitt, R. G., & Kypraios, T. (in press). A rare event approach to high-dimensional approximate Bayesian computation. Statistics and Computing, 28(4), https://doi.org/10.1007/s11222-017-9764-4

Approximate Bayesian computation (ABC) methods permit approximate inference for intractable likelihoods when it is possible to simulate from the model. However they perform poorly for high dimensional data, and in practice must usually be used in con... Read More about A rare event approach to high-dimensional approximate Bayesian computation.

Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment (2017)
Journal Article
Boehm-Sturm, P., Füchtemeier, M., Foddis, M., Mueller, S., Trueman, R. C., Zille, M., …Farr, T. D. (in press). Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment. Stroke, 48(1), https://doi.org/10.1161/STROKEAHA.116.014394

Background and Purpose�Chronic hypoperfusion in the mouse brain has been suggested to mimic aspects of vascular cognitive impairment, such as white matter damage. Although this model has attracted attention, our group has struggled to generate a re... Read More about Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment.