Modelling aerosol transmission of porcine reproductive and respiratory syndrome virus between buildings using computational fluid dynamics.

An integrated computational fluid dynamics (CFD) model was developed to simulate aerosol transmission of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) from a source to recipient building using a previously published experimental study as a test case. The integrated model consisted of CFD simulations of PRRSV aerosol movement in the atmosphere and within the recipient building, viral infectivity decay, and infection dose-response. Specific hours with the appropriate wind direction during two days (June 6 and 7, 2006) were simulated, based on historical weather data. For a given airborne PRRSV concentration exhausted from the source building, the model predicted the PRRSV distribution, infectivity decay, and probability of infection in the recipient building. Simulations indicated that wind affected the aerosol entry into the recipient building, with more stable and continuous aerosol entry at lower wind speed conditions on June 7. Elevated aerosol and PRRSV concentrations on June 7 resulted in pigs being exposed to higher doses of PRRSV than on June 6, but this only made a difference in probability of infection when there was a moderate level of PRRSV (500 TCID m−3) exhausted from the source building. At this level, there was a difference in exposure dose for pigs at different locations (pens). Overall, the positive PRRSV air sample on the morning of June 7 in the previously reported experimental study confirmed the adequacy of the model simulations, which predicted the aerosol transmission event that infected pigs in the recipient building was likely to have occurred on June 7, 2006. • Model simulates aerosol transmission of animal diseases between buildings. • Model integrates CFD with infectivity decay and dose-response for PRRS virus in pigs. • Model able to account for virus levels in infected building and wind conditions. • Model adequately predicted infection probability in a neighbouring building. [ABSTRACT FROM AUTHOR]