arXiv subjects

Anthony J. Webster

Publications and source records attributed to Anthony J. Webster.

6 recordsLinked to original sources

arXiv2025

Multimorbidity as a multistage disease process

There is a growing proportion of people with several disease conditions ("multimorbidity"), placing increasing demands on healthcare systems. One hypothesis is that clusters of diseases may arise from shared underlying disease processes (shared "pathogenesis"), whereby the presence of one disease indicates the state of disease progression to several related disease types. This article explains how this hypothesis can be tested using observational data for disease incidence. Specifically, a multistage model is used to test whether two diseases can have a "shared stage" or "step", before either disease can occur, and how the unobserved rate of this step can be determined. The approach offers a simple method for studying multiple diseases and identifying shared underlying causes of multiple conditions, and is illustrated with published data and numerical examples. The fundamental mathematical model is analysed to compare key statistical properties such as the expectation and variance with those of independent diseases. The main results do not need an understanding of the underlying mathematics and can be appreciated by a non-expert. Significance: It is widely believed that there are shared underlying pathways that can lead to several disease types (shared "pathogenesis"), and this may explain observed clusters of disease types. This article shows how this hypothesis can be tested for a pair or cluster of diseases, using observational data of disease incidence.

stat.ME↗

arXiv2022

Bayesian information criteria for clustering normally distributed data

Maximum likelihood estimates (MLEs) are asymptotically normally distributed, and this property is used in meta-analyses to test the heterogeneity of estimates, either for a single cluster or for several sub-groups. More recently, MLEs for associations between risk factors and diseases have been hierarchically clustered to search for diseases with shared underlying causes, but an objective statistical criterion is needed to determine the number and composition of clusters. To tackle this problem, conventional statistical tests are briefly reviewed, before considering the posterior distribution for a partition of data into clusters. The posterior distribution is calculated by marginalising out the unknown cluster centres, and is different to the likelihood associated with mixture models. The calculation is equivalent to that used to obtain the Bayesian Information Criterion (BIC), but is exact, without a Laplace approximation. The result includes a sum of squares term, and terms that depend on the number and composition of clusters, that penalise the number of free parameters in the model. The usual BIC is shown to be unsuitable for clustering applications unless the number of items in each individual cluster is sufficiently large.

math.ST↗

arXiv2018

A global consumer-led strategy to tackle climate change

A successful response to climate change needs vast investments in low-carbon research, energy, and sustainable development. Governments can drive research, provide environmental regulation, and accelerate global development, but the necessary low-carbon investments of 2-3% GDP have yet to materialise. A new strategy to tackle climate change through consumer and government action is outlined. It relies on ethical investments for sustainable development and low-carbon energy, and a voluntarily financed low-carbon fund for adaptation to climate change. Together these enable a global response through individual actions and investments. With OECD savings exceeding 5% of disposable household income, ethical savings alone have considerable potential.

physics.soc-ph↗

arXiv2017

An Insurance-Led Response to Climate Change

Climate change is widely expected to increase weather related damage and the insurance claims that result from it. This will increase insurance premiums, in a way that is independent of a customer's contribution to the causes of climate change. Insurance provides a financial mechanism that mitigates some of the consequences of climate change, allowing damage from increasingly frequent events to be repaired. We observe that the insurance industry could reclaim any increase in claims due to climate change, by increasing the insurance premiums on energy producers for example, without needing government intervention or a new tax. We argue that this insurance-led levy must acknowledge both present carbon emissions and a modern industry's carbon inheritance, that is, to recognise that fossil-fuel driven industrial growth has provided the innovations and conditions needed for modern civilisation to exist and develop. A tax or levy on energy production is one mechanism that would recognise carbon inheritance through the increased (energy) costs for manufacturing and using modern technology, and can also provide an incentive to minimise carbon emissions, through higher costs for the most polluting industries. The necessary increases in insurance premiums would initially be small, and will require an event attribution (EA) methodology to determine their size. We propose that the levies can be phased in as the science of event attribution becomes sufficiently robust for each claim type, to ultimately provide a global insurance-led response to climate change.

physics.soc-ph↗

arXiv2015

Lightning Strikes and Attribution of Climatic Change

Using lightning strikes as an example, two possible schemes are discussed for the attribution of changes in event frequency to climate change, and estimating the cost associated with them. The schemes determine the fraction of events that should be attributed to climatic change, and the fraction that should be attributed to natural chance. They both allow for the expected increase in claims and the fluctuations about this expected value. Importantly, the attribution fraction proposed in the second of these schemes is necessarily different to that found in epidemiological studies. This ensures that the statistically expected fraction of attributed claims is correctly equal to the expected increase in claims. The analysis of lightning data highlights two particular difficulties with data-driven, as opposed to modeled, attribution studies. The first is the possibility of unknown "confounding" variables that can influence the strike frequency. This is partly accounted for here by considering the influence of temperature changes within a given month, so as to standardise the data to allow for cyclical climatic influences. The second is the possibility suggested by the data presented here, that climate change may lead to qualitatively different climate patterns, with a different relationship between e.g. strike frequency and temperature.

stat.AP↗

arXiv2014

ELM Processes and Properties in 2T 2MA JET Plasmas

During July 2012, 150 almost identical H-mode plasmas were consecutively created in the Joint European Torus (JET), providing a combined total of approximately 8 minutes of steady-state plasma with 15,000 Edge Localised Modes (ELMs). In principle, each of those 15,000 ELMs are statistically equivalent. Here the changes in edge density and plasma energy associated with those ELMs are explored, using the spikes in Beryllium II (527 nm) radiation as an indicator for the onset of an ELM. Two timescales are found during the ELM process. The first timescale is associated with the density drop, and the second (longer) timescale is associated with a reduction in MHD energy that is consistent with a resistive relaxation of the plasma's edge. The statistical properties of the energy and density losses due to the ELMs are explored. Surprisingly the commonly reported link between ELM energy (E) and ELM frequency (f), of E proportional to 1/f, is not found. Instead beyond the first 0.02 seconds of waiting time between ELMs, the energy losses due to the ELMs are found to be statistically the same. Surprisingly no correlation is found between the energies of consecutive ELMs either. A weak link is found between the density drop and the ELM waiting time. Consequences of these results for ELM control and modelling are discussed.

physics.plasm-ph↗