Dose–response modelling of infectious animal diseases coupled with computational fluid dynamics: A simulation of airborne porcine reproductive and respiratory syndrome virus. (August 2021)

• Record Type: Journal Article
• Authors: La, Amy; Zhang, Qiang; Cicek, Nazim; Levin, David B.; Coombs, Kevin M.
• Is Part Of: Biosystems engineering. Volume 208(2021)
• Page Start: 58
• Page End: 78
• Publication Date: 2021-08
• Subjects: Animal diseases -- Computational fluid dynamics -- Dose–response modelling -- Transmission routes; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2021.05.005
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Dose–response modelling was performed for several infectious disease viruses using the exponential, exact beta-Poisson, and approximate beta-Poisson models using existing datasets of animal infections. The exact beta-Poisson model was found to provide the best fit of the three models. The aerosol transmission route was found to require the lowest dose to cause infection compared to the intra-nasal and oral transmission routes for porcine reproductive and respiratory syndrome virus (PRRSV) and H9N2 avian influenza virus. Foot and mouth disease virus required lower doses with the aerosol transmission route than the intra-nasal transmission route. Liquid oral transmission required lower doses than feed transmission to cause infection for African swine fever virus and overall oral transmission required low doses to cause infection by porcine epidemic and diarrhoea virus. A computational fluid dynamics simulation was coupled with the dose–response modelling to simulate aerosol transmission of PRRSV in two experimental case studies. The coupled model predicted a probability of infection between 82% and 100% using the exact beta-Poisson model, which was in good agreement with the observed rate of infections in the two experimental case studies (84% and 90%). Highlights: Stochastic dose–response modelling was used to predict virus infection for animals. CFD was coupled with dose–response models to predict aerosol transmission of viruses. The probability of PRRSV infection was adequately predicted compared to published data.