Descriptive and risk analysis of vehicle movements linked to porcine reproductive and respiratory syndrome and porcine epidemic diarrhea transmission in US commercial swine farms

TL;DR

The analysis revealed that vehicle contact history play a crucial role in the transmission of PRRS and PED, and can provide insights to develop more target strategies aimed at reducing the transmission and outbreaks linked to vehicle movements in swine production.

Abstract

Vehicle movements, including vehicle cabs and trailers, play a role in disseminating disease in swine production. However, there are many information gaps about vehicle movements patterns that increase the probability of disease transmission, which is crucial in developing better preventive strategies. In this study we described the movement pattern of vehicle cabs and trailers and identified risk factors for porcine reproductive and respiratory syndrome (PRRS) and porcine epidemic diarrhea (PED) farm's infectious status. We collected global positioning system (GPS) movement data from vehicle cabs and trailers for 18 months and basic information for 6621 farms in the U.S. For the vehicle movement data, we estimated 66 variables and evaluate their association with farms PRRS and PED status. Our univariate analysis showed that 56 variables were significant associated (p < 0.05) to PED and PRRS farm status. Within these variables, vehicle visit frequency and previous exposition to positive farms were the main risk factors for both diseases. Otherwise, increased vehicle cab and trailer loyalty for farm shipments and vehicle cleaning and disinfection events were protective factors. In the multivariate model, each additional weekly visit by a vehicle cab that had been exposed to a positive farm one day before the shipment was associated with a 234\% and 243\% increase in the odds of a farm testing PRRS- and PED-positive, respectively. Our analysis revealed that vehicle contact history play a crucial role in the transmission of PRRS and PED. These findings can provide insights to develop more target strategies aimed at reducing the transmission and outbreaks linked to vehicle movements in swine production.

Figures (2)

• Figure 1: Vehicles can visit farms, slaughterhouses, or clean stations. A subsequent visit to farm $j$ creates a network edge ($E_{i,j}$) between farms, with a weight determined by the estimated pathogen stability. The edge weight was calculated as $E_{i,j} = \exp\!\left(-\lambda \, \omega_{i,j} \, \Gamma_{i,j}\right)$ if $d > X \sim U(0,1)$, where $\Gamma_{i,j}$ is the cumulative elapsed time between farms $i$ and $j$, $\omega_{i,j}$ is the average temperature between farms $i$ and $j$, and $\lambda$ is the pathogen stability decay rate for each $\omega$. If a movement to a cleaning station was recorded before visiting farm $j$, the edge in the network was recorded only if the cleaning effectiveness $d$ was higher than a random value $X$ drawn from a uniform distribution $U(0,1)$.
• Figure 2: Assumed stability curves for porcine epidemic diarrhea (PED) and porcine reproductive and respiratory syndrome (PRRS) viruses across time and temperature. Each line represents the decay in pathogen stability at a specific temperature, modeled using an exponential distribution. Line types (solid and dashed) indicate the infectious period, marked by a vertical line that denotes the threshold beyond which the pathogens are considered non-infectious.