Comparison of histologic techniques for the diagnosis of bovine tuberculosis in the framework of eradication programs Abstract Rapid diagnosis of tuberculosis in cattle reacting positive in antemortem assays is crucial in countries where eradication programs are operated to confirm the presence of the infection in tuberculosis-free herds. This study evaluated the accuracy of histopathologic examination by hematoxylin and eosin and Ziehl-Neelsen (ZN) staining applied in this framework, when suspected lesions are caused by low infectious doses and are detected in early stages of the disease. For this purpose, histologic methods were compared with mycobacterial culture as reference test on suspected lymph node samples from 173 cattle reacting positive in antemortem tests. Histopathology demonstrated high sensitivity (93.4%) and specificity (92.3%), while ZN sensitivity and specificity were respectively 33.9% and 100%. Introduction Bovine tuberculosis caused by Mycobacterium bovis remains a significant disease of cattle and other species in many countries. Materials and methods Histopathologic examination
Eurosurveillance, Volume 14, Issue 26, 02 July 2009 Eurosurveillance, Volume 14, Issue 26, 02 July 2009 Table of Contents Rapid communications by L Marinova, M Kojouharova, Z Mihneva After seven years without indigenous transmission of measles in Bulgaria, an increasing number of cases have been reported since 15 April 2009. By 19 June, the total number of notifications reached 84(...) show more... After seven years without indigenous transmission of measles in Bulgaria, an increasing number of cases have been reported since 15 April 2009. Hide text by A Tarantola, T Mollet, J Gueguen, P Barboza, E Bertherat Plague is circulating regularly in localised areas worldwide, causing sporadic cases outside Africa and remains endemic or causes limited outbreaks in some African countries. Plague is circulating regularly in localised areas worldwide, causing sporadic cases outside Africa and remains endemic or causes limited outbreaks in some African countries. by N Wilson, MG Baker Research articles by M Camitz News by MJ van de Laar , J Fontaine
PLOS 13/08/12 Impact of Imperfect Test Sensitivity on Determining Risk Factors: The Case of Bovine Tuberculosis Citation: Szmaragd C, Green LE, Medley GF, Browne WJ (2012) Impact of Imperfect Test Sensitivity on Determining Risk Factors: The Case of Bovine Tuberculosis. PLoS ONE 7(8): e43116. doi:10.1371/journal.pone.0043116 Editor: Frank Emmert-Streib, Queen’s University Belfast, United Kingdom Received: May 30, 2012; Accepted: July 16, 2012; Published: August 13, 2012 Copyright: © Szmaragd et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was funded by Defra (http:\\www.defra.gov.uk) under the Animal Health and Welfare call (project number SE3239). Competing interests: The authors have declared that no competing interests exist. Materials and Methods Rationale Data Background Multiple data sources were used to construct the response variable and the different predictors. Table 1. Figure 1.
PLOS 14/02/12 Modelling the Wind-Borne Spread of Highly Pathogenic Avian Influenza Virus between Farms Abstract A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Citation: Ssematimba A, Hagenaars TJ, de Jong MCM (2012) Modelling the Wind-Borne Spread of Highly Pathogenic Avian Influenza Virus between Farms. Editor: Alessandro Vespignani, Northeastern University, United States of America Copyright: © 2012 Ssematimba et al. Introduction
Bull World Health Organ vol.90 no.4 Genebra Apr. 2012 Epidemic and intervention modelling - a scientific rationale for policy de Epidemic and intervention modelling - a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic Épidémie et modélisation d'intervention - une justification scientifique aux décisions politiques? Modelización epidémica e intervencionista - ¿ un fundamento científico para la toma de decisiones? Maria D Van Kerkhove*; Neil M Ferguson Imperial College London, MRC Centre for Outbreak Analysis and Modelling, W2 1PG London, England PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. PROBLÈME: L'analyse de l'apparition d'une pandémie et sa modélisation mathématique sont cruciales pour la planification des réponses de santé publique à l'apparition de maladies infectieuses, d'épidémies et de pandémies. Background Pre-pandemic planning Modelling during the 2009 pandemic School closure was a policy option considered in some countries. Lessons and challenges References
Procedia Environmental Sciences Volume 7, 2011, Pages 104–109 Spatio-temporal model of avian influenza spread risk Volume 7, 2011, Pages 104–109 Spatial Statistics 2011: Mapping Global Change Edited By Alfred Stein, Edzer Pebesma and Gerard Heuvelink Abstract HPAI virus has caused significant economic losses in the poultry industry. Backyard and outdoor poultry farms (BOPF) can play an important role in the spread of the disease. Keywords spatial analysis; avian influenza; risk factors; modelling diseases; multicriteria decision; scan statistics References Conclusions of Council of the European Union about Animal Disease Surveillance systems in the EU Seminar Conclusions. 9547/10. D.E.
Veterinary Research 2013, 44:97 (16 October 2013) Age-dependent patterns of bovine tuberculosis in cattle Data Great Britain has a rich BTB dataset dating back to the 1950s when the first test-and-slaughter scheme was introduced to control disease . Herd-level test results for test-negative herds and animal-level test results for reactor cattle, inconclusive reactor cattle and tests resulting from contact tracing are contained in the database VetNet, collated and managed by the Animal Health and Veterinary Laboratories Agency (AHVLA), which is part of the UK department for Food, the Environment and Rural Affairs (Defra). Cattle demographic and movement data are contained within Cattle Tracing System (CTS). Herd test types All herds in GB are subject to regular SICCT testing at a frequency determined by the local incidence of infection [6,15]. Reactor data The number of reactors was collated directly from the “animal” table in VetNet. Inferring negative tests In general, there is no historic information in VetNet about cattle that tested negative to the SICCT test. Reactor rates Modelling BTB
BIOMED 14/06/13 A global model of avian influenza prediction in wild birds Keiko Herrick and colleagues at the University of Alaska Fairbanks have put forward a model of avian influenza virus (AIV) prediction in wild birds, published yesterday in Veterinary Research. This is the first large-scale large ecological niche model for avian influenza in wild birds based on machine-learning algorithms. The authors mined surveillance data for 2005-2010 from the Influenza Research Database, which yielded a large set of georeferenced sample points, complete with AIV detection status, viral subtype and other related parameters. The sampling data was then layered into ArcMap, along with 41 predictor layers – accounting for environmental and anthropogenic variables such as geographic elevation, adjusted mean temperatures and human population density – all obtained from open source projects. The model of avian influenza prediction reached by the authors, while not definitive, is a first accurate and global-scale predictive model.