Multilayer network analysis unravels haulage vehicles as a hidden threat to the British swine industry

Transboundary and Emerging Diseases

When assessing the role of live animal trade networks in the spread of infectious diseases in livestock, attention has focused mainly on direct movements of animals between premises, whereas the role of haulage vehicles used during transport, an indirect route for disease transmission, has largely been ignored.

Here, we have assessed the impact of sharing haulage vehicles from livestock transport service providers on the connectivity between farms as well as on the spread of swine infectious diseases in Great Britain (GB).

Using all pig movement records between April 2012 and March 2014 in GB, we built a series of directed and weighted static multiplex networks consisting of two layers of identical nodes, where nodes (farms) are linked either by (1) the direct movement of pigs and (2) the shared use of haulage vehicles. The haulage contact definition integrates the date of the move and the duration Δs that lorries are left contaminated by pathogens, hence accounting for the temporal aspect of contact events. For increasing Δs, descriptive network analyses were performed to assess the role of haulage on network connectivity. We then explored how viruses may spread throughout the GB pig sector by computing the reproduction number R.

Our results showed that sharing haulage vehicles increases the number of contacts between farms by > 50% and represents an important driver of disease transmission. In particular, sharing haulage vehicles, even if < Δs1 day, will limit the benefit of the standstill regulation, increase the number of premises that could be infected in an outbreak, and more easily raise R above 1. This work confirms that sharing haulage vehicles has significant potential for spreading infectious diseases within the pig sector. The cleansing and disinfection process of haulage vehicles is therefore a critical control point for disease transmission risk mitigation.

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Prof. Thibaud Porphyre

Quantitative Epidemiologist,