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Modeling nation-wide U.S. swine movement networks at the resolution of the individual premises.
Sellman, Stefan; Beck-Johnson, Lindsay M; Hallman, Clayton; Miller, Ryan S; Owers Bonner, Katharine A; Portacci, Katie; Webb, Colleen T; Lindström, Tom.
Afiliación
  • Sellman S; Department of Physics, Chemistry and Biology, Division of Ecological and Environmental Modeling, Linköping University, Sweden. Electronic address: stefan.sellman@liu.se.
  • Beck-Johnson LM; Department of Biology, Colorado State University, United States of America.
  • Hallman C; USDA APHIS Veterinary Services, Center for Epidemiology and Animal Health, United States of America.
  • Miller RS; USDA APHIS Veterinary Services, Center for Epidemiology and Animal Health, United States of America.
  • Owers Bonner KA; Department of Biology, Colorado State University, United States of America.
  • Portacci K; USDA APHIS Veterinary Services, Center for Epidemiology and Animal Health, United States of America.
  • Webb CT; Department of Biology, Colorado State University, United States of America.
  • Lindström T; Department of Physics, Chemistry and Biology, Division of Ecological and Environmental Modeling, Linköping University, Sweden.
Epidemics ; 41: 100636, 2022 12.
Article en En | MEDLINE | ID: mdl-36274568
The spread of infectious livestock diseases is a major cause for concern in modern agricultural systems. In the dynamics of the transmission of such diseases, movements of livestock between herds play an important role. When constructing mathematical models used for activities such as forecasting epidemic development, evaluating mitigation strategies, or determining important targets for disease surveillance, including between-premises shipments is often a necessity. In the United States (U.S.), livestock shipment data is not routinely collected, and when it is, it is not readily available and mostly concerned with between-state shipments. To bridge this gap in knowledge and provide insight into the complete livestock shipment network structure, we have developed the U.S. Animal Movement Model (USAMM). Previously, USAMM has only existed for cattle shipments, but here we present a version for domestic swine. This new version of USAMM consists of a Bayesian model fit to premises demography, county-level livestock industry variables, and two limited data sets of between-state swine movements. The model scales up the data to simulate nation-wide networks of both within- and between-state shipments at the level of individual premises. Here we describe this shipment model in detail and subsequently explore its usefulness with a rudimentary predictive model of the prevalence of porcine epidemic diarrhea virus (PEDv) across the U.S. Additionally, in order to promote further research on livestock disease and other topics involving the movements of swine in the U.S., we also make 250 synthetic premises-level swine shipment networks with complete coverage of the entire conterminous U.S. freely available to the research community as a useful surrogate for the absent shipment data.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedades de los Porcinos / Enfermedades Transmisibles / Virus de la Diarrea Epidémica Porcina / Epidemias Tipo de estudio: Prognostic_studies / Risk_factors_studies País/Región como asunto: America do norte Idioma: En Revista: Epidemics Año: 2022 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedades de los Porcinos / Enfermedades Transmisibles / Virus de la Diarrea Epidémica Porcina / Epidemias Tipo de estudio: Prognostic_studies / Risk_factors_studies País/Región como asunto: America do norte Idioma: En Revista: Epidemics Año: 2022 Tipo del documento: Article