United Kingdom Dataset Research Articles

DODGE: automated point source bacterial outbreak detection using cumulative long term genomic surveillance.

The reliable and timely recognition of outbreaks is a key component of public health surveillance for foodborne diseases. Whole genome sequencing (WGS) offers high resolution typing of foodborne bacterial pathogens and facilitates the accurate detection of outbreaks. This detection relies on grouping WGS data into clusters at an appropriate genetic threshold. However, methods and tools for selecting and adjusting such thresholds according to the required resolution of surveillance and epidemiological context are lacking. Here we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), an algorithm to dynamically select and compare these genetic thresholds. DODGE can analyse expanding datasets over time and clusters that are predicted to correspond to outbreaks (or "investigation clusters") can be named with established genomic nomenclature systems to facilitate integrated analysis across jurisdictions. DODGE was tested in two real-world Salmonella genomic surveillance datasets of different duration, 2 months from Australia and 9 years from the United Kingdom. In both cases only a minority of isolates were identified as investigation clusters. Two known outbreaks in the United Kingdom dataset were detected by DODGE and were recognized at an earlier timepoint than the outbreaks were reported. These findings demonstrated the potential of the DODGE approach to improve the effectiveness and timeliness of genomic surveillance for foodborne diseases and the effectiveness of the algorithm developed. DODGE is freely available at https://github.com/LanLab/dodge and can easily be installed using Conda.

Statistical analysis of Saudi Arabia and UK Covid-19 data using a new generalized distribution

In this article, we extended the Topp–Leone distribution to create the Odd-Topp–Leone–Gompertz-G distribution, a new family of distributions. We were motivated by the limitations of classical models in modeling real life datasets hence, the creation of a new flexible distribution. Expansion of density, distribution of order statistics, Rényi entropy, moments, quantile, generating functions, residual life function and reverse residual life function, and reliability model are some of its structural aspects that are obtained. We looked at some special cases of the new distribution and concluded that our new model can handle both highly skewed data and non-monotonic hazard rate functions. The maximum likelihood estimation technique was used to estimate the model parameters. A simulation exercise was carried out to evaluate the performance of the proposed family of distribution. The article used the Saudi Arabia and United Kingdom dataset to demonstrate the utility of the new model and it was found that the new model performs better in modeling these datasets as compared to non-nested models presented in this article.

An exploratory analysis of the cybersecurity threat landscape for Botswana

Investigating the cybersecurity threat landscape is important as it increases situational awareness and defensive agility. Therefore, in this study the cybersecurity threat landscape for Botswana was investigated from the perspective of Information Technology (IT) and Cybersecurity professionals in Botswana. Since Botswana has no publicized empirical data on cyber threats, a cybersecurity incidences dataset from the United Kingdom (UK) was first analyzed to understand cybersecurity trends there. Insights obtained from the UK dataset were used as a baseline to design a questionnaire which was sent out to 31 participants from 20 organizations in Botswana. The findings obtained from the questionnaire were analyzed and compared to findings from the UK. This work showed that a coordinated response to cybersecurity and collection of information related to threats and mitigations can help improve situational awareness and defensive agility.

The Association Between Childhood Leukemia and Population Mixing

Studies investigating the population-mixing hypothesis in childhood leukemia principally use two analytical approaches: (1) nonrandom selection of areas according to specific characteristics, followed by comparisons of their incidence of childhood leukemia with that expected based on the national average; and (2) regression analyses of region-wide data to identify characteristics associated with the incidence of childhood leukemia. These approaches have generated contradictory results. We compare these approaches using observed and simulated data. We generated 10,000 simulated regions using the correlation structure and distributions from a United Kingdom dataset. We simulated cases using a Poisson distribution with the incidence rate set to the national average assuming the null hypothesis that only population size drives the number of cases. Selection of areas within each simulated region was based on characteristics considered responsible for elevated infection rates (population density and inward migration) and/or elevated leukemia rates. We calculated effect estimates for 10,000 simulations and compared results to corresponding observed data analyses. When the selection of areas for analysis is based on apparent clusters of childhood leukemia, biased assessments occur; the estimated 5-year incidence of childhood leukemia ranged between zero and eight per 10,000 children in contrast to the simulated two cases per 10,000 children, similar to the observed data. Performing analyses on region-wide data avoids these biases. Studies using nonrandom selection to investigate the association between childhood leukemia and population mixing are likely to have generated biased findings. Future studies can avoid such bias using a region-wide analytical strategy. See video abstract at, http://links.lww.com/EDE/B431.

Older people and Social Quality – what difference does income make?

AbstractThis article explores the relationship between Social Quality and income in later life and represents the first application of the concept to a United Kingdom data-set with an explicit focus on older people. In order to undertake this analysis, confirmatory factor analysis models are employed in conjunction with the British Household Panel Survey (BHPS). This enables various dimensions or domains of Social Quality to be measured and then subjected to further scrutiny via regression analysis. Initially, the paper explores links between low income, poverty and older people, prior to outlining the concept of Social Quality and its four conditional factors. Following the methodology, the impact of income on Social Quality domains is explored. We identify that differences in income in older age provide a partial explanation of differences in individual Social Quality. While there is a statistically significant relationship between income and certain aspects of Social Quality such as economic security, altruism, social networks and culture/participation, other factors such as health, identity and time did not have a statistically significant relationship with income. This indicates that improvements in the income of older people are likely to positively impact on aspects of their Social Quality. Finally, some policy implications of the finding are outlined with particular reference to the potential role for pensions in enhancing aspects of Social Quality in retirement.

Valuation of preference-based measures: can existing preference data be used to generate better estimates?

BackgroundExperimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. There is a scope utilize the evidence in one country to help with the design and the analysis of a study in another, for this to enable the generation of utility estimates of the second country much more precisely than would have been possible when collecting and analyzing the country’s data alone.MethodsWe analyze SF-6D valuation data elicited from representative samples corresponding to the Hong Kong (HK) and United Kingdom (UK) general adult populations through the use of the standard gamble technique to value 197 and 249 health states respectively. We apply a nonparametric Bayesian model to estimate a HK value set using the UK dataset as informative prior to improve its estimation. Estimates are compared to a HK value set estimated using HK values alone using mean predictions and root mean square error.ResultsThe novel method of modelling utility functions permitted the UK valuations to contribute significant prior information to the Hong Kong analysis. The results suggest that using HK data alongside the existing UK data produces HK utility estimates better than using the HK study data by itself.ConclusionThe promising results suggest that existing preference data could be combined with valuation study in a new country to generate preference weights, making own country value sets more achievable for low and middle income countries. Further research is encouraged.

Dental age assessment of southern Chinese using the United Kingdom Caucasian reference dataset

Dental age assessment is one the most accurate methods for estimating the age of an unknown person. Demirjian's dataset on a French-Canadian population has been widely tested for its applicability on various ethnic groups including southern Chinese. Following inaccurate results from these studies, investigators are now confronted with using alternate datasets for comparison. Testing the applicability of other reliable datasets which result in accurate findings might limit the need to develop population specific standards. Recently, a Reference Data Set (RDS) similar to the Demirjian was prepared in the United Kingdom (UK) and has been subsequently validated. The advantages of the UK Caucasian RDS includes versatility from including both the maxillary and mandibular dentitions, involvement of a wide age group of subjects for evaluation and the possibility of precise age estimation with the mathematical technique of meta-analysis. The aim of this study was to evaluate the applicability of the United Kingdom Caucasian RDS on southern Chinese subjects. Dental panoramic tomographs (DPT) of 266 subjects (133 males and 133 females) aged 2-21 years that were previously taken for clinical diagnostic purposes were selected and scored by a single calibrated examiner based on Demirjian's classification of tooth developmental stages (A-H). The ages corresponding to each stage of tooth developmental stage were obtained from the UK dataset. Intra-examiner reproducibility was tested and the Cohen kappa (0.88) showed that the level of agreement was 'almost perfect'. The estimated dental age was then compared with the chronological age using a paired t-test, with statistical significance set at p<0.01. The results showed that the UK dataset, underestimated the age of southern Chinese subjects by 0.24 years but the results were not statistically significant. In conclusion, the UK Caucasian RDS may not be suitable for estimating the age of southern Chinese subjects and there is a need for an ethnic specific reference dataset for southern Chinese.

Host Association of Campylobacter Genotypes Transcends Geographic Variation

Genetic attribution of bacterial genotypes has become a major tool in the investigation of the epidemiology of campylobacteriosis and has implicated retail chicken meat as the major source of human infection in several countries. To investigate the robustness of this approach to the provenance of the reference data sets used, a collection of 742 Campylobacter jejuni and 261 Campylobacter coli isolates obtained from United Kingdom-sourced chicken meat was established and typed by multilocus sequence typing. Comparative analyses of the data with those from other isolates sourced from a variety of host animals and countries were undertaken by genetic attribution, genealogical, and population genetic approaches. The genotypes from the United Kingdom data set were highly diverse, yet structured into sequence types, clonal complexes, and genealogical groups very similar to those seen in chicken isolates from the Netherlands, the United States, and Senegal, but more distinct from isolates obtained from ruminant, swine, and wild bird sources. Assignment analyses consistently grouped isolates from different host animal sources regardless of geographical source; these associations were more robust than geographic associations across isolates from three continents. We conclude that, notwithstanding the high diversity of these pathogens, there is a strong signal of association of multilocus genotypes with particular hosts, which is greater than the geographic signal. These findings are consistent with local and international transmission of host-associated lineages among food animal species and provide a foundation for further improvements in genetic attribution.

Complex insertion/deletion polymorphism in NOD1 (CARD4) is not associated with inflammatory bowel disease susceptibility in East Anglia panel

Genetic association between inflammatory bowel disease (IBD) and NOD1 (CARD4) has recently been reported. This gene has structural similarity to NOD2 (CARD15), a confirmed susceptibility gene for Crohn"s disease (CD). The NOD1 association was strongest at novel complex indel ND1 + 32656. Our aim was to ascertain the contribution of ND1 + 32656 variants to IBD in a large independent United Kingdom dataset and to identify any subphenotype association within CD and ulcerative colitis (UC). The presence of the ND1 + 32656 variant in our panel was confirmed by direct resequencing in 96 cases. One thousand three hundred seventy unrelated white IBD subjects (671UC, 645 CD, 54 indeterminate) and 760 regionally matched controls were then genotyped for the ND1 + 32656 variant. Data were analyzed by logistic regression methods within STATA software. There was no association between ND1 + 32656 and IBD in our panel. There was no heterogeneity between UC and CD, nor within the CD subgroup when conditioned by subphenotype or the presence of NOD2 variants. There was no overall evidence of association between IBD and the reported NOD1 susceptibility variant ND1 + 32656 in our panel. The discrepancy with the earlier report may reflect a smaller effect size than previously predicted, a false-positive result in the index study, or population heterogeneity.

Systematic review and validation of prognostic models in liver transplantation

A model that can accurately predict post-liver transplant mortality would be useful for clinical decision making, would help to provide patients with prognostic information, and would facilitate fair comparisons of surgical performance between transplant units. A systematic review of the literature was carried out to assess the quality of the studies that developed and validated prognostic models for mortality after liver transplantation and to validate existing models in a large data set of patients transplanted in the United Kingdom (UK) and Ireland between March 1994 and September 2003. Five prognostic model papers were identified. The quality of the development and validation of all prognostic models was suboptimal according to an explicit assessment tool of the internal, external, and statistical validity, model evaluation, and practicality. The discriminatory ability of the identified models in the UK and Ireland data set was poor (area under the receiver operating characteristic curve always smaller than 0.7 for adult populations). Due to the poor quality of the reporting, the methodology used for the development of the model could not always be determined. In conclusion, these findings demonstrate that currently available prognostic models of mortality after liver transplantation can have only a limited role in clinical practice, audit, and research.

Predicting Customer Satisfaction from ATMs: A Cross Country Study

ABSTRACT This research study uses an ordered probability model (commonly referred to as an ordered probit model, see Aldrich & Nelson, 1984) to predict customer overall satisfaction gained from the use of ATMs, using two different countries namely the United Kingdom and Hungary. Overall satisfaction is seen in this study as the end result of a combined number of antecedents. This model expands on the work of Goode and Moutinho (1996) and Peel, Goode and Moutinho (1998) which linked a number of antecedent variables to customers' overall satisfaction using a United Kingdom data set. Hungary was randomly selected to test whether this model could be generalised across European countries. Identical methodology and questionnaire design was used to collect the data in Hungary (with the questionnaire being translated into Hungarian). The research is based on the analysis of personal interviews with a total sample of 482 individuals, 380 consumers from the UK and 102 consumers from Hungary. A joint model utilising...

A Test of the Persistence in the Performance of UK Managed Funds

We employ a United Kingdom data set of weekly returns from a sample of investment trust companies available on the Datastream database. We analyse the relative performance of the funds and determine whether a ‘good’ (above‐median), past‐performance is indicative of future performance. Our study focuses on within sample relative performance. We examine persistence in performance in the short and long run based on a number of tests. Overall we find that both raw and risk‐adjusted returns exhibit evidence of persistence in performance in the long run but not in the very short run.

Optimal Estimation of Spherical Harmonic Components from a Sample with Spatially Nonuniform Covariance Statistics

Abstract An optimal estimation technique is presented to estimate spherical harmonic coefficients. This technique is based on the minimization of the mean square error. This optimal estimation technique consists of computing optimal weights for a given network of sampling points. Empirical orthogonal functions (E0Fs) are an essential ingredient in formulating the estimation technique of the field of which the second-moment statistics are non-uniform over the sphere. The EOFs are computed using the United Kingdom dataset of global gridded temperatures based on station data. The utility of the technique is further demonstrated by computing a set of spherical harmonic coefficients from the 100-yr long surface temperature fluctuations of the United Kingdom dataset. Next, the validity of the mean-square error formulas is tested by actually calculating an ensemble average of mean-square estimation error. Finally, the technique is extended to estimate the amplitudes of the EOFS.