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Adapting an Atmospheric Dispersion Model to Assess the Risk of Windborne Transmission of Porcine Reproductive and Respiratory Syndrome Virus between Swine Farms.
Kanankege, Kaushi S T; Graham, Kerryne; Corzo, Cesar A; VanderWaal, Kimberly; Perez, Andres M; Durr, Peter A.
Afiliação
  • Kanankege KST; Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St Paul, MN 55108, USA.
  • Graham K; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian Centre for Disease Preparedness, Geelong, VIC 3219, Australia.
  • Corzo CA; Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St Paul, MN 55108, USA.
  • VanderWaal K; Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St Paul, MN 55108, USA.
  • Perez AM; Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St Paul, MN 55108, USA.
  • Durr PA; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian Centre for Disease Preparedness, Geelong, VIC 3219, Australia.
Viruses ; 14(8)2022 07 28.
Article em En | MEDLINE | ID: mdl-36016281
ABSTRACT
Modeling the windborne transmission of aerosolized pathogens is challenging. We adapted an atmospheric dispersion model (ADM) to simulate the windborne dispersion of porcine reproductive and respiratory syndrome virus (PRRSv) between swine farms. This work focuses on determining ADM applicable parameter values for PRRSv through a literature and expert opinion-based approach. The parameters included epidemiological features of PRRSv, characteristics of the aerosolized particles, and survival of aerosolized virus in relation to key meteorological features. A case study was undertaken to perform a sensitivity analysis on key parameters. Farms experiencing ongoing PRRSv outbreaks were assigned as particle emitting sources. The wind data from the North American Mesoscale Forecast System was used to simulate dispersion. The risk was estimated semi-quantitatively based on the median daily deposition of particles and the distance to the closest emitting farm. Among the parameters tested, the ADM was most sensitive to the number of particles emitted, followed by the model runtime, and the release height was the least sensitive. Farms within 25 km from an emitting farm were at the highest risk; with 53.66% being within 10 km. An ADM-based risk estimation of windborne transmission of PRRSv may inform optimum time intervals for air sampling, plan preventive measures, and aid in ruling out the windborne dispersion in outbreak investigations.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vírus da Síndrome Respiratória e Reprodutiva Suína / Síndrome Respiratória e Reprodutiva Suína Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vírus da Síndrome Respiratória e Reprodutiva Suína / Síndrome Respiratória e Reprodutiva Suína Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Ano de publicação: 2022 Tipo de documento: Article