TB policy and the badger culling trials.
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Biomedical subjects
Publications and source records attributed to D R Cox.
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Human and livestock diseases can be difficult to control where infection persists in wildlife populations. For three decades, European badgers (Meles meles) have been culled by the British government in a series of attempts to limit the spread of Mycobacterium bovis, the causative agent of bovine tuberculosis (TB), to cattle. Despite these efforts, the incidence of TB in cattle has risen consistently, re-emerging as a primary concern for Britain's cattle industry. Recently, badger culling has attracted controversy because experimental studies have reached contrasting conclusions (albeit using different protocols), with culled areas showing either markedly reduced or increased incidence of TB in cattle. This has confused attempts to develop a science-based management policy. Here we use data from a large-scale, randomized field experiment to help resolve these apparent differences. We show that, as carried out in this experiment, culling reduces cattle TB incidence in the areas that are culled, but increases incidence in adjoining areas. These findings are biologically consistent with previous studies but will present challenges for policy development.
As an aid to the study of bovine tuberculosis (TB), a simple model has been developed of an epidemic involving two species, cattle and badgers. Each species may infect the other. The proportion of animals affected is assumed relatively small so that the usual nonlinear aspects of epidemic theory are avoided. The model is used to study the long-run and transient effect on cattle of culling badgers and the effect of a period without routine testing for TB, such as occurred during the 2001 epidemic of foot-and-mouth disease in Great Britain. Finally, by examining the changes in cattle TB over the last 15 years, and with some other working assumptions, it is estimated that the net reproduction number of the epidemic is approximately 1.1. The implications for controlling the disease are discussed.
During the course of an epidemic of a potentially fatal disease, it is important that the case fatality ratio be well estimated. The authors propose a novel method for doing so based on the Kaplan-Meier survival procedure, jointly considering two outcomes (death and recovery), and evaluate its performance by using data from the 2003 epidemic of severe acute respiratory syndrome in Hong Kong, People's Republic of China. They compare this estimate obtained at various points in the epidemic with the case fatality ratio eventually observed; with two commonly quoted, naïve estimates derived from cumulative incidence and mortality statistics at single time points; and with estimates in which a parametric mixture model is used. They demonstrate the importance of patient characteristics regarding outcome by analyzing subgroups defined by age at admission to the hospital.
Social class differentials in educational attainment have been extensively studied in numerous countries. In this paper, we begin by examining class differentials in the progression to higher secondary education among 16-year-old children in England and Wales. As has been shown for other countries, the differentials result both from the primary effects of differing levels of academic performance of children of different class background and from the secondary effects of differences in the educational choices that these children make at given levels of performance. Through counterfactual analyses in which the performance distribution of one class is combined with the choice distribution of another, primary and secondary effects are decomposed and the former are shown to be roughly three times the size of the latter.
Suppose measurements of a particular feature are collected at baseline and at a number of subsequent time points and that for each individual there is a roughly linear trend in time. This paper takes three approaches to testing whether there is a relation between the initial value and the slope. It also considers whether the initial value for an individual is a useful predictor of the slope for that individual. The problems are formulated in terms of regression models with random coefficients. The solutions are illustrated using data from an observational study of clinical correlates of disability and progression in Huntington's disease.
A case-control study of the factors associated with the risk of a bovine tuberculosis (TB) breakdown in cattle herds was undertaken within the randomized badger culling trial (RBCT). TB breakdowns occurring prior to the 2001 foot-and-mouth disease epidemic in three RBCT triplets were eligible to be cases; controls were selected from the same RBCT area. Data from 151 case farms and 117 control farms were analysed using logistic regression. The strongest factors associated with an increased TB risk were movement of cattle onto the farm from markets or farm sales, operating a farm over multiple premises and the use of either covered yard or 'other' housing types. Spreading artificial fertilizers or farmyard manure on grazing land were both associated with decreased risk. These first case-control results from the RBCT will be followed by similar analyses as more data become available.
Simple tests are given for consistency of the data with additive and with multiplicative effects of two risk factors on a binary outcome. A combination of the procedures will show whether data are consistent with neither, one or both of the models of no additive or no multiplicative interaction. Implications for the size of the study needed to detect differences between the models are also addressed. Because of the simple form of the test statistics, combination of evidence from different studies or strata is straightforward. Illustration of how the method could be extended to data from a 2xRxC table is also given.
The application of regular herd testing to identify and remove infected animals has proved to be a highly successful method of controlling bovine tuberculosis (TB) in many parts of the world. However, in some countries, notably the United Kingdom, Ireland and New Zealand, the disease has continued to pose a significant problem, despite intensive herd testing. Persistence of disease in these countries is associated with the presence of wildlife reservoirs of infection. Attempts to control bovine TB by culling of wildlife have been, at best, only partially successful and have proved difficult to sustain. This has led to considering of vaccination either of wildlife or cattle as a potential control measure. However, there are a number of obstacles that need to be overcome before vaccination can be considered a practical option. Vaccine efficacy, methods used for vaccine delivery in wildlife, potential interference of vaccination with diagnostic tests for cattle and appropriate design of field trials are among the issues that need to be addressed.
Pathogens that are transmitted between wildlife, livestock and humans present major challenges for the protection of human and animal health, the economic sustainability of agriculture, and the conservation of wildlife. Mycobacterium bovis, the aetiological agent of bovine tuberculosis (TB), is one such pathogen. The incidence of TB in cattle has increased substantially in parts of Great Britain in the past two decades, adversely affecting the livelihoods of cattle farmers and potentially increasing the risks of human exposure. The control of bovine TB in Great Britain is complicated by the involvement of wildlife, particularly badgers (Meles meles), which appear to sustain endemic infection and can transmit TB to cattle. Between 1975 and 1997 over 20,000 badgers were culled as part of British TB control policy, generating conflict between conservation and farming interest groups. Here we present results from a large-scale field trial that indicate that localized badger culling not only fails to control but also seems to increase TB incidence in cattle.
This paper deals with the synthesis of information from different studies when there is lack of independence in some of the contrasts to be combined. This problem can arise in several different situations in both case-control studies and clinical trials. For efficient estimation we appeal to the method of generalized least squares to estimate the summary effect and its standard error. This method requires estimates of the covariances between those contrasts that are not independent. Although it is not possible to estimate the covariance between effects that have been adjusted for confounding factors we present a method for finding upper and lower bounds for this covariance. In the simplest discussion homogeneity of the relative risks is assumed but the method is then extended to allow for heterogeneity in an overall estimate. We then illustrate the method with several examples from an analysis in which case-control studies of cervical cancer and oral contraceptive use are synthesized.
Some of the many statistical aspects of floods are discussed and some new results are given on a number of features. The probability theory of extreme values is briefly reviewed and its potential for applications outlined. The peaks-over-threshold method of estimation is compared with the direct use of annual maxima and some theoretical comparisons of efficiency are given. The effect of trend on the distribution of maxima is analysed in terms of a simple theoretical model distinguishing the effects of trend in mean level and of trend in dispersion. An empirical Bayes method for pooling information from a number of sources is described and illustrated, and related to the procedures recommended in the Flood estimation handbook. In the final section, a range of further issues is outlined.
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Global patterns of human DNA sequence variation (haplotypes) defined by common single nucleotide polymorphisms (SNPs) have important implications for identifying disease associations and human traits. We have used high-density oligonucleotide arrays, in combination with somatic cell genetics, to identify a large fraction of all common human chromosome 21 SNPs and to directly observe the haplotype structure defined by these SNPs. This structure reveals blocks of limited haplotype diversity in which more than 80% of a global human sample can typically be characterized by only three common haplotypes.
The mineralocorticoid hormone, aldosterone, is known to play a role in sodium homeostasis. We serendipitously found, however, highly significant association between single-nucleotide polymorphisms in the aldosterone synthase gene and plasma glucose levels in a large population of Chinese and Japanese origin. Two polymorphisms--one in the putative promoter (T-344C) and another resulting in a lysine/arginine substitution at amino acid 173, which are in complete linkage disequilibrium in this population--were associated with fasting plasma glucose levels (P = 0.000017) and those 60 (P = 0.017) and 120 (P = 0.0019) min after an oral glucose challenge. A C/T variant in intron 1, between these polymorphisms, was not associated with glucose levels. Arg-173 and -344C homozygotes were most likely to be diabetic [odds ratio 2.51; 95% confidence interval (C.I.) 1.39-3.92; P = 0.0015] and have impaired fasting glucose levels (odds ratio 3.53; 95% C.I. 2.02-5.5; P = 0.0000036). These results suggest a new role for aldosterone in glucose homeostasis.
Comparison of genomic DNA sequences from human and mouse revealed a new apolipoprotein (APO) gene (APOAV) located proximal to the well-characterized APOAI/CIII/AIV gene cluster on human 11q23. Mice expressing a human APOAV transgene showed a decrease in plasma triglyceride concentrations to one-third of those in control mice; conversely, knockout mice lacking Apoav had four times as much plasma triglycerides as controls. In humans, single nucleotide polymorphisms (SNPs) across the APOAV locus were found to be significantly associated with plasma triglyceride levels in two independent studies. These findings indicate that APOAV is an important determinant of plasma triglyceride levels, a major risk factor for coronary artery disease.
The kidney, by regulating the volume of fluid in the body, plays a key role in regulating blood pressure (BP). The kidney uses primarily sodium and, to a lesser extent, urea to maintain the appropriate volume of fluid. Genetic variation in proteins that determine sodium reabsorption and excretion is known to significantly influence BP. However, the influence of genetic variation in urea transporters on BP has not been examined. We determined therefore whether nucleotide variation in the kidney-specific human urea transporter, HUT2, is associated with variation in BP. After determining the genomic structure of the coding sequence, seven single nucleotide polymorphisms (SNPs) were identified. Two of the SNPs result in Val/Ile and Ala/Thr amino acid substitutions at positions 227 and 357 in the HUT2 open reading frame, respectively. Another SNP is silent and four others are in introns or the 3' untranslated region. Over 1000 hypertensive and low-normotensive individuals of Chinese origin were typed for five of these SNPs using a high-throughput genotyping method. The Ile227 and Ala357 alleles were associated with low diastolic BP in men but not women, with odds ratios 2.1 [95% confidence interval (CI) 1.5-2.7, P < 0.001] and 1.5 (95% CI 1.2-1.8, P < 0.001), respectively. There was a similar trend for systolic BP, and odds ratios for the Ile227 and Ala357 alleles were 1.7 (95% CI 1.2-2.3, P = 0.002) and 1.3 (95% CI 1.1-1.6, P = 0.007), respectively, in men.