Time filter

Source Type

Fort Collins, CO, United States

Ruder M.G.,Manhattan College | Lysyk T.J.,Agriculture and Agri Food Canada | Stallknecht D.E.,University of Georgia | Foil L.D.,Louisiana State University | And 4 more authors.
Vector-Borne and Zoonotic Diseases | Year: 2015

Bluetongue virus (BTV) and epizootic hemorrhagic disease virus (EHDV) are arthropod-transmitted viruses in the genus Orbivirus of the family Reoviridae. These viruses infect a variety of domestic and wild ruminant hosts, although the susceptibility to clinical disease associated with BTV or EHDV infection varies greatly among host species, as well as between individuals of the same species. Since their initial detection in North America during the 1950s, these viruses have circulated in endemic and epidemic patterns, with occasional incursions to more northern latitudes. In recent years, changes in the pattern of BTV and EHDV infection and disease have forced the scientific community to revisit some fundamental areas related to the epidemiology of these diseases, specifically in relation to virus-vector-host interactions and environmental factors that have potentially enabled the observed changes. The aim of this review is to identify research and surveillance gaps that obscure our understanding of BT and EHD in North America. © Copyright 2015, Mary Ann Liebert, Inc. Source

Karreman G.,Veterinary and Regulatory Affairs | Klotins K.,Canadian Food Inspection Agency | Bebak J.,Aquaculture Biosecurity LLC | Gustafson L.,Center for Epidemiology and Animal Health | And 4 more authors.
Journal of Applied Aquaculture | Year: 2015

Few papers focus on the application of biosecurity principles to the daily operations at aquatic facilities. This discussion will address the gap by presenting a case study idealized from a real-life situation. A large North American salmon farm company requested assistance to prevent the introduction of Viral Hemorrhagic Septicemia Virus (VHSV) into one of its Atlantic salmon (Salmo salar) hatcheries. A systematic, disciplined approach was used that included risk assessment and infectious disease control principles. The hatchery’s operations were analyzed for potential pathogen (VHSV) introduction using knowledge of the facility’s physical layout and the operational process flow. Possible routes of introduction were identified by tracing the typical movements of animals (fish, eggs), water, fomites, vectors, and feed. Mitigation measures for identified gaps were proposed that were based on pathogen characteristics. Copyright © Taylor & Francis Group, LLC. Source

Holtkamp D.J.,Iowa State University | Kliebenstein J.B.,Iowa State University | Neumann E.J.,Massey University | Zimmerman J.J.,Iowa State University | And 6 more authors.
Journal of Swine Health and Production | Year: 2013

Objective: To estimate the current annual economic impact of porcine reproductive and respiratory syndrome virus (PRRSV) on the US swine industry. Materials and methods: Data for the analysis was compiled from the US Department of Agriculture, a survey of swine veterinarians on the incidence and impact of PRRSV, and production records (2005 to 2010) from commercial farms with known PRRSV status. Animal-level economic impact of productivity losses and other costs attributed to PRRSV were estimated using an enterprise budgeting approach and extrapolated to the national level on the basis of the US breedingherd inventory, number of pigs marketed, and number of pigs imported for growing. Results: The total cost of productivity losses due to PRRSV in the US national breeding and growing-pig herd was estimated at US $664 million annually, an increase from the US $560 million annual cost estimated in 2005. The 2011 study differed most significantly from the 2005 study in the allocation of losses between the breeding and the growing-pig herd. Losses in the breeding herd accounted for 12% of the total cost of PRRSV in the 2005 study, compared to 45% in the current analysis. Implications: Despite over 25 years of experience and research, porcine reproductive and respiratory syndrome remains a costly disease of pigs in the United States. Since 2005, some progress has been made in dealing with the cost of productivity losses due to the disease in the growing pig, but these were offset by greater losses in the breeding herd. Source

Mu J.E.,Oregon State University | McCarl B.A.,Texas A&M University | Hagerman A.,Center for Epidemiology and Animal Health | Bessler D.,Texas A&M University
Journal of Integrative Agriculture | Year: 2015

This paper examines the U.S. meat demand impacts of the announced outbreaks of bovine spongiform encephalopathy (BSE) and avian influenza (AI). Findings indicate that beef and chicken demand was negatively affected by BSE and AI disease outbreaks. Specifically, in the short run, U.S. consumers shift demand due to both outbreaks but more so due to domestic disease outbreaks than for outbreaks occurring overseas-the impact of U.S. AI outbreaks is about 0.5% for beef and the impact of U.S. BSE cases is around -0.42% for beef and 0.4% for pork, respectively. Regarding the BSE shock on meat demand, there is a high rate of beef demand adjusted from disturbance to the long-run equilibrium and a lower adjustment rate for chicken demand because of the repeated outbreaks of AI worldwide. In the long run, information related to severe, persistently recurring overseas animal disease outbreaks changes U.S. consumers' meat consumption patterns. Although effects of animal diseases on U.S. meat demand were statistically significant, the magnitudes were small-the impact of WHO reported human death numbers for AI is 0.005% for beef, -0.002% for pork, and -0.006% for chicken and the impact of U.S. BSE cases is 1.1% for pork and -0.7% for chicken. © 2015 Chinese Academy of Agricultural Sciences. Source

News Article
Site: http://www.scientificcomputing.com/rss-feeds/all/rss.xml/all

Computer scientists and statisticians at Colorado State University are turning disease outbreak planning exercises into a game. They’re creating powerful new software that can predict, simulate and analyze a major disease outbreak — all in the form of an intuitive, multiplayer game. Researchers led by Shrideep Pallickara, associate professor of computer science in the College of Natural Sciences, are in year one of a three-year, $2.04 million Department of Homeland Security Science and Technology Directorate grant. The project is aimed at connecting the latest, greatest computing and data management technology to the fight against widespread livestock disease. Livestock disease outbreaks can spread far and fast across the U.S. From foot and mouth disease in cattle to avian influenza, the illnesses can wreak havoc on animals, the industrial food system and the economy. “When a disease breaks out, you need to know — how severe is it? How long will it last? How many field personnel do you need? What are the economic consequences? How will commodity prices be affected? What will happen if you start vaccinating?” Pallickara said. Computer scientists are used to dealing with hundreds or thousands of variables and running what-if scenarios. The Department of Homeland Security, the U.S. Department of Agriculture/Center for Epidemiology and Animal Health, and other outbreak specialists such as the Federal Emergency Management Agency, respond to emergencies by identifying a handful of scenarios. Then they can change parameters for each scenario — adjusting variables including disease biology and virulence — to help determine action plans for things like vaccine stockpiles, vaccine efficacy and deploying field personnel. But that whole process can take hours or days; meanwhile, the disease spreads. “In these cases, sometimes hours elapse between modifying your scenario, running it and getting your response back,” Pallickara said. “What we do instead is, given a national scale outbreak scenario, we generate 100,000 variants, run them in a computing cloud that generates several billion files, and then do the analytics on all this data. So, even if a user is trying to change something in real time, we have already learned what will happen. This involves a lot of back-end processing, which allows us to make real-time predictions.” Group gaming and why it works Disease planners often work in isolation and don’t understand each other’s rationale or how decisions affect one another. This project tackles that problem by enabling collaborative decisions, allowing epidemiologists and state and federal officials to work together using a unique real-time planning tool — a multiplayer computer game called “Symphony.” A single-player version called “Sonata” will be released first. Why use group gaming to plan for disease outbreaks? Because concepts tend to “stick” better when people use them in game playing, the researchers say. The idea is to put different decision makers — from policymakers to field agent and veterinarians — in each others’ shoes. The researchers envision all these constituents together in a virtual room, doing a planning exercise with the game and real-time visualizations, such as heat maps of potential danger zones. Also on the team is Sangmi Pallickara, an assistant professor in Computer Science, who is leading the big data component of the project — the management of about 1 trillion files. Jay Breidt, professor in statistics, will provide statistical models and expertise. Others on the team include a veterinary epidemiologist and an economist from Kansas State University, and a disease spread model designer. “From a computer scientist’s perspective, creating a disease outbreak planning tool introduces a host of interesting challenges,” Shrideep Pallickara said. Machine learning, statistical models and ensemble learning all become part of the process. And lots of computing power to crunch a petabyte of information over 10 million hours of CPU computing time. “It is not enough for our tool to be accurate. It has to be useful. It has to be in real time,” Pallickara said. “The players — the DHS, the USDA, CEAH, state and federal officials — need to see a response in less than 100 milliseconds.”

Discover hidden collaborations