Papers by george streftaris
The control of highly infectious diseases of agricultural and plantation crops and livestock repr... more The control of highly infectious diseases of agricultural and plantation crops and livestock represents a key challenge in epidemiological and ecological modelling, with implemented control strategies often being controversial. Mathematical models, including the spatio-temporal stochastic models considered here, are playing an increasing role in the design of control as agencies seek to strengthen the evidence on which selected strategies are based. Here, we investigate a general approach to informing the choice of control strategies using spatio-temporal models within the Bayesian framework. We illustrate the approach for the case of strategies based on pre-emptive removal of individual hosts. For an exemplar model, using simulated data and historic data on an epidemic of Asiatic citrus canker in Florida, we assess a range of measures for prioritizing individuals for removal that take account of observations of an emerging epidemic. These measures are based on the potential infecti...
International Journal of Environmental Research and Public Health, 2020
Many epidemiological studies have shown an association between outdoor particulate air pollutants... more Many epidemiological studies have shown an association between outdoor particulate air pollutants and increased morbidity and mortality. Inhalation of ambient aerosols can exacerbate or promote the development of cardiovascular and pulmonary diseases as well as other diseases, such as type 2 diabetes mellitus (T2DM) and neurodegenerative diseases. Occupational exposure to dust, fumes and diesel exhaust particulates can also cause adverse health outcomes and there are numerous occupations where workers are exposed to airborne particles that are similar to ambient air pollution. An individual’s job title has normally been identified as a major determinant of workplace exposure in epidemiological studies. This has led to the development of Job–Exposure Matrices (JEMs) as a way of characterising specific workplace exposures. One JEM for airborne chemical exposures is the Airborne Chemical Exposure Job–Exposure Matrix (ACE JEM), developed specifically for the UK Biobank cohort. The objec...
To account for overdispersion in count data, that is variation in excess of that justified from t... more To account for overdispersion in count data, that is variation in excess of that justified from the assumed model, one may consider an additional source of variation, by assuming that each observation, Y2 , i = 1,... , m, arises from a conditionally independent Poisson distribution, given its respective mean O, i = 1,... , M. We review various frequentist methods for the estimation of the Poisson parameters O, i = 1,... , m, which are based on the inadmissibility of the usual unbiased maximum likelihood estimator, in terms of the associated risk in dimensions greater than two. The so called shrinkage estimators adjust the maximum likelihood estimates towards a fixed or data-determined point, abandoning unbiasedness in favour of lower risk. Inferences for the parameters of interest can also be drawn employing Bayesian methods. Conjugate models are often adopted to facilitate the computational procedure. In this thesis we assume a nonconjugate log-normal prior distribution, which allo...
The mortality rates in the UK has changed over time. The prevalence of Ischaemic Heart Disease (I... more The mortality rates in the UK has changed over time. The prevalence of Ischaemic Heart Disease (IHD) and stroke in the UK has been decreasing which has contributed to the changes between 1981 and 2000. The major risk factors associated with IHD and stroke, in addition to age, sex and smoking, are body mass index, diabetes, hypertension and hypercholesterolaemia. The objectives of this study is to investigate the effect of changes in the risk factors and quantify the extent of these changes. The results showed that smoking and hypertension has the highest effect on IHD, stroke and mortality for males and females. Lower rates of hypertension would reduce the prevalence of IHD and stroke as it has a direct effect on IHD, stroke and mortality. Changes in the risk factors would increase or decrease the number of IHD, stroke and deaths. Deaths from these factors could be reduced if the smoking ban policy and promotion towards no smoking are done widely and reducing the level of hypertension by living a healthy lifestyle.
Several studies have allowed the most common symptoms of hypoglycaemia for diabetic patients to b... more Several studies have allowed the most common symptoms of hypoglycaemia for diabetic patients to be identified and categorised [1]. However, limited attention has been given to symptom variability at individual patient level. In this work we develop a model for assessing intraindividual consistency in reporting specific symptoms throughout a number of hypoglycaemic episodes. The data are taken from a study aiming to record prospectively the symptoms of hypoglycaemia experienced by adults with type 1 and type 2 diabetes. Patients used selfcompleted symptom forms, on which they selected from a typical list of symptoms commonly associated with hypoglycaemia. A logistic-type model for individual subjects is used, in which the probability for individual to report symptom at episode depends on a stochastic threshold being exceeded by a critical value determined by latent variables representing the propensity of reporting symptom and the acuteness of episode . The stochastic thresholds are ...
The copyright in this thesis is owned by the author. Any quotation from the thesis or use of any ... more The copyright in this thesis is owned by the author. Any quotation from the thesis or use of any of the information contained in it must acknowledge this thesis as the source of the quotation or information.
The control of highly infectious diseases of agricultural and plantation crops and livestock repr... more The control of highly infectious diseases of agricultural and plantation crops and livestock represents a key challenge in epidemiological and ecological modelling, with implemented control strategies often being controversial. Mathematical models, including the spatio-temporal stochastic models considered here, are playing an increasing role in the design of control as agencies seek to strengthen the evidence on which selected strategies are based. Here, we investigate a general approach to informing the choice of control strategies using spatio-temporal models within the Bayesian framework. We illustrate the approach for the case of strategies based on pre-emptive removal of individual hosts. For an exemplar model, using simulated data and historic data on an epidemic of Asiatic citrus canker in Florida, we assess a range of measures for prioritizing individuals for removal that take account of observations of an emerging epidemic. These measures are based on the potential infection hazard a host poses to susceptible individuals (hazard), the likelihood of infection of a host (risk) and a measure that combines both the hazard and risk (threat). We find that the threat measure typically leads to the most effective control strategies particularly for clustered epidemics when resources are scarce. The extension of the methods to a range of other settings is discussed. A key feature of the approach is the use of functional-model representations of the epidemic model to couple epidemic trajectories under different control strategies. This induces strong positive correlations between the epidemic outcomes under the respective controls, serving to reduce both the variance of the difference in outcomes and, consequently, the need for extensive simulation.
Journal of Mathematical Biology, 2020
One of the most important issues in the critical assessment of spatio-temporal stochastic models ... more One of the most important issues in the critical assessment of spatio-temporal stochastic models for epidemics is the selection of the transmission kernel used to represent the relationship between infectious challenge and spatial separation of infected and susceptible hosts. As the design of control strategies is often based on an assessment of the distance over which transmission can realistically occur and estimation of this distance is very sensitive to the choice of kernel function, it is important that models used to inform control strategies can be scrutinised in the light of observation in order to elicit possible evidence against the selected kernel function. While a range of approaches to model criticism is in existence, the field remains one in which the need for further research is recognised. In this paper, building on earlier contributions by the authors, we introduce a new approach to assessing the validity of spatial kernels—the latent likelihood ratio tests—which us...
PLOS ONE, 2020
Reliable modelling of the dynamics of cancer morbidity risk is important, not least due to its si... more Reliable modelling of the dynamics of cancer morbidity risk is important, not least due to its significant impact on healthcare and related policies. We identify morbidity trends and regional differences in England for all-cancer and type-specific incidence between 1981 and 2016. We use Bayesian modelling to estimate cancer morbidity incidence at various age, year, gender, and region levels. Our analysis shows increasing trends in most rates and marked regional variations that also appear to intensify through time in most cases. All-cancer rates have increased significantly, with the highest increase in East, North West and North East. The absolute difference between the rates in the highest-and lowest-incidence region, per 100,000 people, has widened from 39 (95% CI 33-45) to 86 (78-94) for females, and from 94 (85-104) to 116 (105-127) for males. Lung cancer incidence for females has shown the highest increase in Yorkshire and the Humber, while for males it has declined in all regions with the highest decrease in London. The gap between the highest-and lowestincidence region for females has widened from 47 (42-51) to 94 (88-100). Temporal change in in bowel cancer risk is less manifested, with regional heterogeneity also declining. Prostate cancer incidence has increased with the highest increase in London, and the regional gap has expanded from 33 (30-36) to 76 (69-83). For breast cancer incidence the highest increase has occurred in North East, while the regional variation shows a less discernible increase. The analysis reveals that there are important regional differences in the incidence of all-type and type-specific cancers, and that most of these regional differences become more pronounced over time. A significant increase in regional variation has been demonstrated for most types of cancer examined here, except for bowel cancer where differences have narrowed.
Journal of the Royal Society, Interface, 2017
The control of highly infectious diseases of agricultural and plantation crops and livestock repr... more The control of highly infectious diseases of agricultural and plantation crops and livestock represents a key challenge in epidemiological and ecological modelling, with implemented control strategies often being controversial. Mathematical models, including the spatio-temporal stochastic models considered here, are playing an increasing role in the design of control as agencies seek to strengthen the evidence on which selected strategies are based. Here, we investigate a general approach to informing the choice of control strategies using spatio-temporal models within the Bayesian framework. We illustrate the approach for the case of strategies based on pre-emptive removal of individual hosts. For an exemplar model, using simulated data and historic data on an epidemic of Asiatic citrus canker in Florida, we assess a range of measures for prioritizing individuals for removal that take account of observations of an emerging epidemic. These measures are based on the potential infecti...
International journal of environmental research and public health, Jan 9, 2018
It has been hypothesised that environmental air pollution, especially airborne particles, is a ri... more It has been hypothesised that environmental air pollution, especially airborne particles, is a risk factor for type 2 diabetes mellitus (T2DM) and neurodegenerative conditions. However, epidemiological evidence is inconsistent and has not been previously evaluated as part of a systematic review. Our objectives were to carry out a systematic review of the epidemiological evidence on the association between long-term exposure to ambient air pollution and T2DM and neurodegenerative diseases in adults and to identify if workplace exposures to particles are associated with an increased risk of T2DM and neurodegenerative diseases. Assessment of the quality of the evidence was carried out using the GRADE system, which considers the quality of the studies, consistency, directness, effect size, and publication bias. Available evidence indicates a consistent positive association between ambient air pollution and both T2DM and neurodegeneration risk, such as dementia and a general decline in c...
PLoS computational biology, 2017
In recent years there has been growing availability of individual-level spatio-temporal disease d... more In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the me...
Risk analysis : an official publication of the Society for Risk Analysis, Jul 14, 2017
Societies worldwide are investing considerable resources into the safe development and use of nan... more Societies worldwide are investing considerable resources into the safe development and use of nanomaterials. Although each of these protective efforts is crucial for governing the risks of nanomaterials, they are insufficient in isolation. What is missing is a more integrative governance approach that goes beyond legislation. Development of this approach must be evidence based and involve key stakeholders to ensure acceptance by end users. The challenge is to develop a framework that coordinates the variety of actors involved in nanotechnology and civil society to facilitate consideration of the complex issues that occur in this rapidly evolving research and development area. Here, we propose three sets of essential elements required to generate an effective risk governance framework for nanomaterials. (1) Advanced tools to facilitate risk-based decision making, including an assessment of the needs of users regarding risk assessment, mitigation, and transfer. (2) An integrated model...
British Actuarial Journal, 2015
Critical illness (CI) insurance involves cover that pays out on the diagnosis of an illness which... more Critical illness (CI) insurance involves cover that pays out on the diagnosis of an illness which is deemed to be critical. Estimation and graduation of CI insurance claim rates has been challenging, partly because of the diagnosis of the insured event often being unclear or not recorded. This introduces additional uncertainties in the evaluation of claim rates. In this work, which was funded by an Institute and Faculty of Actuaries research grant, we have addressed the issue of model and parameter uncertainty in claim rate estimation, when the date of diagnosis is missing, aiming at obtaining graduated rates that can be applied to estimate the future cash flow of CI policies and determine insurers’ liability more accurately. Better understanding of uncertainty in rate graduation and pricing is important for insurers, not least because of future changes in the interpretation of the “definition” of an illness or advances in medical practice leading to more efficient diagnosis and tre...
PLoS computational biology, 2015
Genetic sequence data on pathogens have great potential to inform inference of their transmission... more Genetic sequence data on pathogens have great potential to inform inference of their transmission dynamics ultimately leading to better disease control. Where genetic change and disease transmission occur on comparable timescales additional information can be inferred via the joint analysis of such genetic sequence data and epidemiological observations based on clinical symptoms and diagnostic tests. Although recently introduced approaches represent substantial progress, for computational reasons they approximate genuine joint inference of disease dynamics and genetic change in the pathogen population, capturing partially the joint epidemiological-evolutionary dynamics. Improved methods are needed to fully integrate such genetic data with epidemiological observations, for achieving a more robust inference of the transmission tree and other key epidemiological parameters such as latent periods. Here, building on current literature, a novel Bayesian framework is proposed that infers s...
Diabetes technology & therapeutics, 2011
The aim of the present study was to examine symptoms of hypoglycemia, to develop a method to quan... more The aim of the present study was to examine symptoms of hypoglycemia, to develop a method to quantify individual differences in the consistency of symptom reporting, and to investigate which factors affect these differences. Participants recorded their symptoms with every episode of hypoglycemia over a 9-12-month period. A novel logistic-type latent variable model was developed to quantify the consistency of each individual's symptom complex and was used to analyze data from 59 subjects (median age, 57.5 years [range, 22-74 years], 65% male, 77% type 1 diabetes) who had experienced 19 or more hypoglycemic episodes. The association between the calculated consistency parameter and age, sex, type and duration of diabetes, and C-peptide and serum angiotensin converting enzyme concentration was examined using a generalized linear model. Analyses were performed under a Bayesian framework, using Markov chain Monte-Carlo methodology. Individuals exhibited substantial differences in betw...
In this paper we apply Markov chain Monte Carlo (MCMC) algorithms developed by Leuwattanachotinan... more In this paper we apply Markov chain Monte Carlo (MCMC) algorithms developed by Leuwattanachotinan et al. (2012) to calibrate the two-factor Cairns term structure model (Cairns, 2004) with monthly UK Strips data. We first estimate the model parameters and latent state variables and then assess the goodness of fit of the model. Consequently, the model is used for forecasting the yield curves and annuity prices where the impact of parameter uncertainty is also investigated. Additionally, the two-factor Vasicek term structure model is also fitted for comparison. We conclude that our algorithms work reasonably well for estimating both models with the UK market data. The models are found to produce reasonable fits for medium-and long-term yields, but we also conclude that some improvement may be required for the short-end of the yield curves.
Scandinavian Journal of Statistics, 2002
A single-population Markovian stochastic epidemic model is defined so that the underlying social ... more A single-population Markovian stochastic epidemic model is defined so that the underlying social structure of the population is described by a Bernoulli random graph. The parameters of the model govern the rate of infection, the length of the infectious period, and the probability of social contact with another individual in the population. Markov chain Monte Carlo methods are developed to facilitate Bayesian inference for the parameters of both the epidemic model and underlying unknown social structure. The methods are applied in various examples of both illustrative and real-life data, with two different kinds of data structure considered.
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Papers by george streftaris