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      Risk factors for Echinococcus coproantigen positivity in dogs from the Alay valley, Kyrgyzstan

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          Abstract

          Echinococcosis, caused by the zoonotic cestodes Echinococcus granulosus (sensu lato) and Echinococcus multilocularis, is highly endemic in the Central Asian Republic of Kyrgyzstan, and is being identified increasingly as a public health problem, especially amongst pastoral communities. As domestic dogs are considered to be the main source of human infection, the identification of potential transmission pathways is of relevance when considering implementing an echinococcosis control scheme. The current report describes the results of an analytical study of canine Echinococcus coproantigen enzyme-linked immunosorbent assay (ELISA) prevalence in the Alay valley of southern Kyrgyzstan prior to the commencement of regular praziquantel dosing of dogs. A logistic regression model using a form of Bayes modal estimation was used to identify possible risk factors for coproantigen positivity, and the output was interpreted in a Bayesian context (posterior distributions of the coefficients of interest). The study found that sheepdogs had lower odds of coproantigen positivity, as did dogs in households with donkeys, where owners had knowledge of echinococcosis, and households which engaged in home slaughtering. Surprisingly, there was no evidence of an association between free roaming or previous praziquantel dosing and coproantigen positivity, as has been found in previous studies. Possible reasons for these findings are discussed in the context of the epidemiology of echinococcosis and potential intervention approaches.

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          Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.

          The clinical performance of a laboratory test can be described in terms of diagnostic accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy refers to the quality of the information provided by the classification device and should be distinguished from the usefulness, or actual practical value, of the information. Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Furthermore, ROC plots occupy a central or unifying position in the process of assessing and using diagnostic tools. Once the plot is generated, a user can readily go on to many other activities such as performing quantitative ROC analysis and comparisons of tests, using likelihood ratio to revise the probability of disease in individual subjects, selecting decision thresholds, using logistic-regression analysis, using discriminant-function analysis, or incorporating the tool into a clinical strategy by using decision analysis.
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            Index for rating diagnostic tests.

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              Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests.

              We review the principles and practical application of receiver-operating characteristic (ROC) analysis for diagnostic tests. ROC analysis can be used for diagnostic tests with outcomes measured on ordinal, interval or ratio scales. The dependence of the diagnostic sensitivity and specificity on the selected cut-off value must be considered for a full test evaluation and for test comparison. All possible combinations of sensitivity and specificity that can be achieved by changing the test's cut-off value can be summarised using a single parameter; the area under the ROC curve. The ROC technique can also be used to optimise cut-off values with regard to a given prevalence in the target population and cost ratio of false-positive and false-negative results. However, plots of optimisation parameters against the selected cut-off value provide a more-direct method for cut-off selection. Candidates for such optimisation parameters are linear combinations of sensitivity and specificity (with weights selected to reflect the decision-making situation), odds ratio, chance-corrected measures of association (e. g. kappa) and likelihood ratios. We discuss some recent developments in ROC analysis, including meta-analysis of diagnostic tests, correlated ROC curves (paired-sample design) and chance- and prevalence-corrected ROC curves.
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                Author and article information

                Journal
                J Helminthol
                J. Helminthol
                JHL
                Journal of Helminthology
                Cambridge University Press (Cambridge, UK )
                0022-149X
                1475-2697
                November 2015
                : 89
                : 6
                : 655-663
                Affiliations
                [ 1 ]Cestode Zoonoses Research Group, School of Environment and Life Sciences, University of Salford, Salford , M5 4WT, UK
                [ 2 ]Department of Psychology, University of Michigan , 1012 East Hall, 530 Church Street, Ann Arbor, MI, 48109-1043, USA
                [ 3 ]Section of Epidemiology, Vetsuisse Faculty, University of Zürich , Switzerland
                [ 4 ]Parasitology group, Kyrgyz Veterinary Research Institute , Togolok Moldo 60, Bishkek, Kyrgyzstan
                Author notes
                Article
                S0022149X15000590 00059
                10.1017/S0022149X15000590
                4700908
                26442706
                2604afce-48ba-49d8-a4ab-4e53c0b01494
                © Cambridge University Press 2015

                This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 06 March 2015
                : 06 June 2015
                Categories
                Research Papers

                Parasitology
                Parasitology

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