Academic literature on the topic 'Cattle Communicable diseases in animals Veterinary epidemiology'
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Journal articles on the topic "Cattle Communicable diseases in animals Veterinary epidemiology"
Dutra, Iveraldo S., Axel Colling, David Driemeier, Marilene F. Brito, Daniel G. Ubiali, Ana Lucia Schild, Franklin Riet-Correa, and Claudio S. L. Barros. "Jürgen Döbereiner: a life dedicated to science." Pesquisa Veterinária Brasileira 39, no. 1 (January 2019): 1–11. http://dx.doi.org/10.1590/1678-5150-pvb-6293.
Full textMunyeme, Musso, Hetron Mweemba Munang’andu, Andrew Nambota, John Bwalya Muma, Andrew Malata Phiri, and King Shimumbo Nalubamba. "The Nexus between Bovine Tuberculosis and Fasciolosis Infections in Cattle of the Kafue Basin Ecosystem in Zambia: Implications on Abattoir Surveillance." Veterinary Medicine International 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/921869.
Full textKhimich, M. S., O. T. Piven, O. M. Gorobey, V. Z. Salata, D. V. Freiuk, and O. V. Naidich. "The analysis of the dynamics of detection animal’s invasive diseases during veterinary expertise." Scientific Messenger of LNU of Veterinary Medicine and Biotechnology 21, no. 93 (April 2, 2019): 149–54. http://dx.doi.org/10.32718/nvlvet9326.
Full textSERRANO, E., P. C. CROSS, M. BENERIA, A. FICAPAL, J. CURIA, X. MARCO, S. LAVÍN, and I. MARCO. "Decreasing prevalence of brucellosis in red deer through efforts to control disease in livestock." Epidemiology and Infection 139, no. 10 (May 31, 2011): 1626–30. http://dx.doi.org/10.1017/s0950268811000951.
Full textEJIDOKUN, O. O., A. WALSH, J. BARNETT, Y. HOPE, S. ELLIS, M. W. SHARP, G. A. PAIBA, M. LOGAN, G. A. WILLSHAW, and T. CHEASTY. "Human Vero cytotoxigenic Escherichia coli (VTEC) O157 infection linked to birds." Epidemiology and Infection 134, no. 2 (September 7, 2005): 421–23. http://dx.doi.org/10.1017/s0950268805004917.
Full textTerfa, Waktole, Bersissa Kumsa, Dinka Ayana, Anna Maurizio, Cinzia Tessarin, and Rudi Cassini. "Epidemiology of Gastrointestinal Parasites of Cattle in Three Districts in Central Ethiopia." Animals 13, no. 2 (January 13, 2023): 285. http://dx.doi.org/10.3390/ani13020285.
Full textSabah Fakhry, Saad, Zainab Noori Hammed, Wasan Abdul - elah Bakir, and Bahaa Abdullah Laftaah ALRubaii. "Identification of methicillin-resistant strains of Staphylococcus aureus isolated from humans and food sources by use mecA 1 and mecA 2 genes in Pulsed-field gel electrophoresis technique." Bionatura 7, no. 2 (May 15, 2022): 1–5. http://dx.doi.org/10.21931/rb/2022.07.02.44.
Full textSavitskaya, T. A., V. A. Trifonov, I. V. Milova, G. Sh Isaeva, I. D. Reshetnikova, I. V. Serova, D. V. Lopushov, and V. B. Ziatdinov. "Anthrax in the Republic of Tatarstan (1920–2020)." Problems of Particularly Dangerous Infections, no. 3 (October 30, 2022): 129–36. http://dx.doi.org/10.21055/0370-1069-2022-3-129-136.
Full textDakic, Zorica, Nikola Indjic, Branko Milosevic, Jasmina Poluga, Zoran Kulisic, Milos Korac, Novica Stajkovic, Irena Ofori-Belic, and Milos Pavlovic. "Epidemiology and diagnostics of human fasciolosis." Veterinarski glasnik 64, no. 1-2 (2010): 127–36. http://dx.doi.org/10.2298/vetgl1002127d.
Full textBradley, R. "Transmittable diseases: the lessons from bovine spongiform encephalopathy (BSE)." BSAP Occasional Publication 17 (January 1993): 19–29. http://dx.doi.org/10.1017/s0263967x00001245.
Full textDissertations / Theses on the topic "Cattle Communicable diseases in animals Veterinary epidemiology"
Shephard, Richard William. "The development of a syndromic surveillance system for the extensive beef cattle producing regions of Australia." University of Sydney, 2006. http://hdl.handle.net/2123/2210.
Full textAll surveillance systems are based on an effective general surveillance system because this is the system that detects emerging diseases and the re-introduction of disease to a previously disease free area. General surveillance requires comprehensive coverage of the population through an extensive network of relationships between animal producers and observers and surveillance system officers. This system is under increasing threat in Australia (and many other countries) due to the increased biomass, animal movements, rate of disease emergence, and the decline in resource allocation for surveillance activities. The Australian surveillance system is state-based and has a complex management structure that includes State and Commonwealth government representatives, industry stakeholders (such as producer bodies) and private organisations. A developing problem is the decline in the effectiveness of the general surveillance system in the extensive (remote) cattle producing regions of northern Australia. The complex organisational structure of surveillance in Australia contributes to this, and is complicated by the incomplete capture of data (as demonstrated by slow uptake of electronic individual animal identification systems), poorly developed and integrated national animal health information systems, and declining funding streams for field and laboratory personnel and infrastructure. Of major concern is the reduction in contact between animal observers and surveillance personnel arising from the decline in resource allocation for surveillance. Fewer veterinarians are working in remote areas, fewer producers use veterinarians, and, as a result, fewer sick animals are being investigated by the general surveillance system. A syndrome is a collection of signs that occur in a sick individual. Syndromic surveillance is an emerging approach to monitoring populations for change in disease levels and is based on statistical monitoring of the distribution of signs, syndromes and associations between health variables in a population. Often, diseases will have syndromes that are characteristic and the monitoring of these syndromes may provide for early detection of outbreaks. Because the process uses general signs, this method may support the existing (struggling) general surveillance system for the extensive cattle producing regions of northern Australia. Syndromic surveillance systems offer many potential advantages. First, the signs that are monitored can be general and include any health-related variable. This generality provides potential as a detector of emerging diseases. Second, many of the data types used occur early in a disease process and therefore efficient syndromic surveillance systems can detect disease events in a timely manner. There are many hurdles to the successful deployment of a syndromic surveillance system and most relate to data. An effective system will ideally obtain data from multiple sources, all data will conform to a standard (therefore each data source can be validly combined), data coverage will be extensive (across the population) and data capture will be in real time (allowing early detection). This picture is one of a functional electronic data world and unfortunately this is not the norm for either human or animal heath. Less than optimal data, lack of data standards, incomplete coverage of the population and delayed data transmission result in a loss of sensitivity, specificity and timeliness of detection. In human syndromic surveillance, most focus has been placed on earlier detection of mass bioterrorism events and this has concentrated research on the problems of electronic data. Given the current state of animal health data, the development of efficient detection algorithms represents the least of the hurdles. However, the world is moving towards increased automation and therefore the problems with current data can be expected to be resolved in the next decade. Despite the lack of large scale deployment of these systems, the question is becoming when, not whether these system will contribute. The observations of a stock worker are always the start of the surveillance pathway in animal health. Traditionally this required the worker to contact a veterinarian who would investigate unusual cases with the pathway ending in laboratory samples and specific diagnostic tests. The process is inefficient as only a fraction of cases observed by stock workers end in diagnostic samples. These observations themselves are most likely to be amenable to capture and monitoring using syndromic surveillance techniques. A pilot study of stock workers in the extensive cattle producing Lower Gulf region of Queensland demonstrated that experienced non-veterinary observers of cattle can describe the signs that they see in sick cattle in an effective manner. Lay observers do not posses a veterinary vocabulary, but the provision of a system to facilitate effective description of signs resulted in effective and standardised description of disease. However, most producers did not see personal benefit from providing this information and worried that they might be exposing themselves to regulatory impost if they described suspicious signs. Therefore the pilot study encouraged the development of a syndromic surveillance system that provides a vocabulary (a template) for lay observers to describe disease and a reason for them to contribute their data. The most important disease related drivers for producers relate to what impact the disease may have in their herd. For this reason, the Bovine Syndromic Surveillance System (BOSSS) was developed incorporating the Bayesian cattle disease diagnostic program BOVID. This allowed the observer to receive immediate information from interpretation of their observation providing a differential list of diseases, a list of questions that may help further differentiate cause, access to information and other expertise, and opportunity to benchmark disease performance. BOSSS was developed as a web-based reporting system and used a novel graphical user interface that interlinked with an interrogation module to enable lay observers to accurately and fully describe disease. BOSSS used a hierarchical reporting system that linked individual users with other users along natural reporting pathways and this encouraged the seamless and rapid transmission of information between users while respecting confidentiality. The system was made available for testing at the state level in early 2006, and recruitment of producers is proceeding. There is a dearth of performance data from operational syndromic surveillance systems. This is due, in part, to the short period that these systems have been operational and the lack of major human health outbreaks in areas with operational systems. The likely performance of a syndromic surveillance system is difficult to theorise. Outbreaks vary in size and distribution, and quality of outbreak data capture is not constant. The combined effect of a lack of track record and the many permutations of outbreak and data characteristics make computer simulation the most suitable method to evaluate likely performance. A stochastic simulation model of disease spread and disease reporting by lay observers throughout a grid of farms was modelled. The reporting characteristics of lay observers were extrapolated from the pilot study and theoretical disease was modelled (as a representation of newly emergent disease). All diseases were described by their baseline prevalence and by conditional sign probabilities (obtained from BOVID and from a survey of veterinarians in Queensland). The theoretical disease conditional sign probabilities were defined by the user. Their spread through the grid of farms followed Susceptible-Infected-Removed (SIR) principles (in herd) and by mass action between herds. Reporting of disease events and signs in events was modelled as a probabilistic event using sampling from distributions. A non-descript disease characterised by gastrointestinal signs and a visually spectacular disease characterised by neurological signs were modelled, each over three outbreak scenarios (least, moderately and most contagious). Reports were examined using two algorithms. These were the cumulative sum (CuSum) technique of adding excess of cases (above a maximum limit) for individual signs and the generic detector What’s Strange About Recent Events (WSARE) that identifies change to variable counts or variable combination counts between time periods. Both algorithms detected disease for all disease and outbreak characteristics combinations. WSARE was the most efficient algorithm, detecting disease on average earlier than CuSum. Both algorithms had high sensitivity and excellent specificity. The timeliness of detection was satisfactory for the insidious gastrointestinal disease (approximately 24 months after introduction), but not sufficient for the visually spectacular neurological disease (approximately 20 months) as the traditional surveillance system can be expected to detect visually spectacular diseases in reasonable time. Detection efficiency was not influenced greatly by the proportion of producers that report or by the proportion of cases or the number of signs per case that are reported. The modelling process demonstrated that a syndromic surveillance system in this remote region is likely to be a useful addition to the existing system. Improvements that are planned include development of a hand-held computer version and enhanced disease and syndrome mapping capability. The increased use of electronic recording systems, including livestock identification, will facilitate the deployment of BOSSS. Long term sustainability will require that producers receive sufficient reward from BOSSS to continue to provide reports over time. This question can only be answered by field deployment and this work is currently proceeding.
Rodriguez-Palacios, Alexander. "Ecology and Epidemiology of Human Pathogen Clostridium difficile in Foods, Food Animals and Wildlife." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313582304.
Full textBooks on the topic "Cattle Communicable diseases in animals Veterinary epidemiology"
Thrusfield, Michael. Veterinary epidemiology. 2nd ed. Oxford: Blackwell Science, 1995.
Find full textThrusfield, M. V. Veterinary epidemiology. 3rd ed. Ames, Iowa: Blackwell Science, 2005.
Find full textInstitute for International Cooperation in Animal Biologics, ed. Emerging and exotic diseases of animals. 3rd ed. Ames, Iowa: Institute for International Cooperation in Animal Biologics, Iowa State University, College of Veterinary Medicine, 2008.
Find full textT︠S︡ėvėgmėd, G. Mal, amʹtny khaldvart takhal ȯvchin: Unshikh bichig. Ulaanbaatar: Monsudar Khėvlėliĭn Gazar, 2000.
Find full textBlancou, Jean. History of the surveillance and control of transmissible animal diseases. Paris: Office International des Epizooties, 2003.
Find full textPonpu, Korea (South) Nongnim Susan Kŏmyŏk Kŏmsa. Kach'uk chŏnyŏmpyŏng yŏkhak chosa chich'im. Kyŏnggi-do Anyang-si: Nongnim Susan Kŏmyŏk Kŏmsa Ponbu, 2012.
Find full textInternational Symposium on Veterinary Epidemiology and Economics (4th 1985 Singapore). Proceedings of the 4th International Symposium on Veterinary Epidemiology & Economics: 18-22 November 1985, Singapore. Singapore: Singapore Veterinary Association, 1986.
Find full textReports on the topic "Cattle Communicable diseases in animals Veterinary epidemiology"
Klement, Eyal, Elizabeth Howerth, William C. Wilson, David Stallknecht, Danny Mead, Hagai Yadin, Itamar Lensky, and Nadav Galon. Exploration of the Epidemiology of a Newly Emerging Cattle-Epizootic Hemorrhagic Disease Virus in Israel. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7697118.bard.
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