Simulation models for between farm transmission of PRRS virus in Canadian swine herds

Abstract

Porcine reproductive and respiratory syndrome (PRRS) is a viral disease of pigs, which affects all production stages and has severe economic consequences for the swine industry. The virus is primarily spread between farms through direct and indirect contacts. A limited number of studies have been carried out to understand the between-farm transmission dynamics of the virus. The objectives of this thesis were to explore the contact structures among swine farms in Canada and to use these contact structures to better understand the pattern and dynamics of between-farm spread of PRRS virus among Canadian swine herds. Four different studies were designed and implemented to achieve these objectives. The first study used network analysis tools to analyse pig movement data which revealed characteristics of contact patterns between swine herds and suggested a hierarchical structure within the Canadian swine industry, where pigs typically move in a unidirectional manner from one production stage to another. The median in-degree and out-degree for farms in this study was 1 and ranged between 0-26 and 0-10 respectively for the overall network. The degree distributions demonstrated characteristics of a power-law distribution, suggesting the presence of scale-free structure while the size of clustering coefficient suggested presence of small-world structure in the swine movement network. Additionally, high levels of truck sharing between farms were noted in this study, with a typical truck, during the study period, being shared among four different farms. The second and third studies simulated the between farm spread of the PRRS based on the movement of pigs and the sharing of trucks among swine farms, using the North American Animal Disease Spread Model and the network-based models respectively. These studies provided a means to assess the relative importance of direct and indirect contact via truck sharing on between farm spread of PRRS virus. By including the transmission by trucks in the model, the median number of infected farms increased by 18% and the median epidemic size increased by 44% in the spatial model. Furthermore, with the addition of trucks in the model, the hierarchical structure of the industry was significantly altered and multidirectional disease spread was observed. On the other hand, the network-based models assessed the impact of scale-free, small-world and random network structures on the between farm spread of PRRS virus and demonstrated the influence these network structures can have on the spread of the virus. The spread on scale-free networks resulted in the smallest stochastic die-out percentage with highest epidemic sizes compared to spread on small-world or random networks. Similarly, the incorporation of transmission by trucks in the model had the highest impact on small-world and random networks, where the epidemic size doubled, compared to scale-free networks, where it increased by 20-29%. Given the importance of transmission of the virus via truck (e.g. indirect contacts) identified in the previous studies, the last chapter aims at (i) quantifying the likelihood that a pig transport truck shared among farms could remain contaminated with PRRS virus at the end of Day 1 and to (ii) evaluate the efficacy of commonly used cleaning and disinfection protocols in eliminating the virus from these trucks. The results of this study suggested, when no cleaning and disinfection protocol is applied, that it is moderately likely that the truck could become contaminated and remain infected with the PRRS virus (mean probability ranged between 0.338-0.352, when the truck was shared between two farms), and that this risk marginally increased with an increase in the number of farms the truck was shared among. This final study also suggested that once contaminated, most of the contaminated trucks would likely remain infected for more than one day. The studies presented in this thesis have not only provided a clearer insight into the pattern of contacts between farms, and the impact these contacts can have on PRRS virus spread, but have also highlighted the importance of including data on the sharing of trucks among farms, since trucks will tend to connect farms which would otherwise share no connection. Moreover, the studies in this thesis have reinforced the importance of the proper cleaning and disinfection of trucks between successive shipments, as the findings presented here suggest that with an increasing level of truck sharing between farms, shared trucks are likely to remain contaminated with the virus and sharing of trucks significantly increased the risk of between farm spread of PRRS virus. Not only do the shared trucks have a high probability of becoming contaminated with the virus, but once contaminated, they are likely to remain infected for a comparatively long period particularly in the absence of adequate disinfection. It should be noted that the pig movement data used in this study was not very recent and consisted of movements reported for only four months time period. Additionally, the described models could not be validated due to unavailability of data is another noteworthy limitation of the studies described in this thesis