Predicting infection risk of airborne foot-and-mouth disease

Abstract

Foot-and-mouth disease is a highly contagious disease of cloven-hoofed animals, the control and eradication of which is of significant worldwide socio-economic importance. The virus may spread by direct contact between animals or via fomites as well as through airborne transmission, with the latter being the most difficult to control. Here, we consider the risk of infection to flocks or herds from airborne virus emitted from a known infected premises. We show that airborne infection can be predicted quickly and with a good degree of accuracy, provided that the source of virus emission has been determined and reliable geo-referenced herd data are available. A simple model provides a reliable tool for estimating risk from known sources and for prioritizing surveillance and detection efforts. The issue of data information management systems was highlighted as a lesson to be learned from the official inquiry into the UK 2007 foot-and-mouth outbreak: results here suggest that the efficacy of disease control measures could be markedly improved through an accurate livestock database incorporating flock/herd size and location, which would enable tactical as well as strategic modelling.

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies

“…The simplest way to retrieve a dose is to assume the dose is equal to the modelled concentration. However, since not all pathogens are inhaled, variables like inhalation rate and exposure duration might better be included for a more detailed dose estimation (Casal et al, 1997;Dungan, 2014;Li et al, 2013;Low et al, 2007;Schley et al, 2009;Sørenson et al, 2000, Ssematimba et al, 2012Stellacci et al, 2010). Dosimetry models can also include particle size distribution and deposition (Isukapalli et al, 2008).…”

“…They discussed that other actual atmospheric stability conditions could explain misclassified farms. Schley et al (2009) used the Numerical Atmospheric-dispersion Modelling Environment (NAME) and did, however, go further by applying an exponential dose-response model. As one of the few, they assessed the quality of their predicted infection risks by calculating a specificity and sensitivity rate, being 82% and 94% respectively regarding the farms' infectivity status.…”

Farm size as a factor in hydrodynamic transmission of pathogens in aquaculture fish production

“…For robust pathogens, risk may exist over very large hydrographic distances similar to transmission distances for airborne pathogens in terrestrial systems of 300 km (Sørensen et al 2000) with recorded transmission up to 200 km (Schley et al 2009). However, the risk in aquaculture could be considered as a worse case scenario as it is dependent on persistent, reasonably high velocity currents for prolonged periods without deposition or non-linear dispersion, and without sufficient turbulent mixing.…”

Developing models for investigating the environmental transmission of disease-causing agents within open-cage salmon aquaculture

“…The fluidity of the aquatic environment may result in greater connectivity between fish farm sites over large distance, much greater than those in terrestrial animal production systems. However, it must be noted that occasionally some airborne pathogens can be transmitted over large distances as was the case for Foot-and-mouth disease virus (Schley et al 2009) and vector borne pathogens such as Bluetongue virus (Szmaragd et al 2009). Within both terrestrial systems and aquaculture, infection occurs through the introduction of an infected individual and localised transmission.…”

“…However, to develop specific dispersal characteristics, the derivation of β can become complex and requires additional modelling. For example, establishing that the transmission of Foot-and-mouth disease virus was transmitted aerially in terrestrial animal production (Schley et al 2009) required combining meteorology and epidemiology, whilst for specific dispersal in aquatic environments, detailed oceanographic particle dispersal models are required to, for instance, assess the dispersal of parasitic sea lice in a small sea loch, fjords and archipelagos (Amundrud & Murray 2009, Asplin et al 2011, Stucchi et al 2011). Using such methods highlights the potential long-distance dispersal of infectious agents, without the presence of an infected class of individuals in close proximity to a susceptible population, and allows for identification of where risk of transmission may occur, should a susceptible class be present.…”