Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St Paul, MN 55108, USA.
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian Centre for Disease Preparedness, Geelong, VIC 3219, Australia.
Viruses. 2022 Jul 28;14(8):1658. doi: 10.3390/v14081658.
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.
模拟气溶胶化病原体的风传是具有挑战性的。我们改编了一个大气扩散模型(ADM),以模拟猪繁殖与呼吸综合征病毒(PRRSv)在养猪场之间的风传扩散。这项工作主要集中在通过文献和专家意见的方法确定适用于 PRRSv 的 ADM 参数值。这些参数包括 PRRSv 的流行病学特征、气溶胶化颗粒的特征以及与关键气象特征相关的气溶胶化病毒的存活。进行了一项案例研究,对关键参数进行了敏感性分析。正在经历持续 PRRSv 暴发的农场被指定为颗粒排放源。使用北美中尺度预报系统的风数据来模拟扩散。根据颗粒的每日沉积中位数和到最近排放源的距离,对风险进行半定量估计。在所测试的参数中,ADM 对排放的颗粒数量最敏感,其次是模型运行时间,释放高度最不敏感。距离排放源 25 公里以内的农场风险最高;其中 53.66%在 10 公里以内。基于 ADM 的 PRRSv 风传风险估计可用于通知最佳空气采样时间间隔、计划预防措施,并有助于在暴发调查中排除风传扩散。