Patrick M. Grace

Predictive modelling and risk assessment of BSE: a review

Predictive models have been used to monitor and analyse the future course of bovine spongiform encephalopathy (BSE) and provide estimates of biological parameters to assess the risks to both animal and human health. Risk assessment models have illustrated that oral transmission is the primary cause of BSE (90% of cases) and have shown that horizontal transmission of infection may be responsible for the persistence and clustering of the disease. Best-fit risk assessment models have shown that maternal transmission occurs at a rate of 9.6% with 95% confidence limits of 5.1–14.2. There is an age-dependent susceptibility to infection. Risk models have estimated that bovine susceptibility to BSE, and hence risk of infection, peaks at 1.31 years of age and rapidly decreases in subsequent years. An animals infectiousness (and hence risk to cause disease) is mainly confined to the end of the incubation period with a peak when clinical signs appear. BSE models have shown that the optimal culling policy to minimize BSE cases is a combination of herd targeting plus a policy that targets bovines potentially exposed through the maternal transmission route. Back calculation methods have concentrated primarily on epidemiological parameter estimation while other risk assessment modelling techniques have focused on predictive studies and on the evaluation of different BSE control strategies. Predictive modelling and risk assessments have enabled a more accurate description of the underlying parameters effecting BSE disease incidence and the associated risks.

Detection of glass contamination in horticultural peat with dual-energy X-ray absorptiometry (DXA)

The application of dual-energy X-ray absorptiometry (DXA) to the detection of glass contamination in horticultural peat was studied using contaminated peat specimens, imaged with X-ray energies of 40 and 70 kVp and without any physical disruption of the peat samples. The source was an uncollimated beam from an industrial X-ray non-destructive testing system. X-ray transmission characteristics of peat and glass were determined from chemical composition data using XCOM software. The DXA images were analysed for detectivity figure (DF), signal-to-noise ratio (SNR) and contrast. These quantities were compared with those of the unprocessed 40 kVp images. There was >75% detection of glass presence if thicker than 3 mm, but 100% detection of glass fragments thicker than 1 mm. It was not possible to distinguish between glass and stone. DF values were dependent on peat and glass type, and contrast more than doubled with the DXA-derived images compared with their 40 kVp counterparts. Comparison with reported figures for a luggage inspection system shows that this system performs better than expected for commercial security systems. Better DXA results may be possible using simultaneous energy detection, and such a multi-energy sensing system could allow glass/stone detection as part of peat quality assurance, and the determination of peat chemical composition.

Human Risks from the Combustion of SRM-Derived Tallow in Ireland

The identification of meat and bone meal (MBM) as a significant factor in the spread of bovine spongiform encephalopathy (BSE) has resulted in the introduction of restrictions on the use and movement of MBM and tallow. This has led to a requirement for alternative uses for these products. This paper reports on a risk assessment performed on the use of tallow as a fuel oil extender in diesel engines. With up to 4000 tonnes of tallow being produced each year in Ireland, combustion with energy recovery represents a viable, cost-efficient utilization route. A stochastic (Latin Hypercube sampling) simulation model was developed to assess the infectiv-ity risk to humans associated with potential airborne exposure to the combustion products when using tallow as a combustion fuel in diesel engines. The model simulates the potential infectivity pathways that tallow follows, including its production from animals with potentially subclinical BSE and processing the tallow with segregation and heat treatments. The model uses probability distributions for the most important input parameters. The assessment takes into account a number of epidemiological parameters that include tissue infectivity, species barrier, disease incidence, and heat inactivation. Two scenarios, reflecting the infectivity risk in different animal tissues defined by the European Commissions Scientific Steering Committee (SSC), were performed. It is seen from the model results that the risk of a human contracting variant Creutzfeldt-Jakob Disease (vCJD) from potential airborne exposure to BSE, resulting from the combustion of tallow, is extremely small even when model uncertainty is taken into account (mean individual risk values ranging from 10-11.43 to 10-7.23 per year/person). The risks are a number of orders of magnitude less than the sporadic annual incidence level of Creutzfeldt-Jakob Disease 9CJD) in Europe (approximately 10-6)

Quantitative Exposure Assessment for the Combustion of Meat and Bone Meal Derived from Specified Risk Material in the Context of BSE in Ireland

The probability and severity of an adverse event can be analyzed by quantitative exposure assessment (QEA). This methodology was applied to model the human health risks associated with the combustion of specified risk material (SRM) derived meat and bone meal (MBM) in a combustion facility. The identification of MBM and SRM as significant factors in the spread of bovine spongiform encephalopathy (BSE) has resulted in restrictions on their use and movement, and this has led to a requirement for alternative end-uses for these products. A stochastic (Latin Hypercube sampling) simulation model was developed to assess the exposure and hence the risks associated with the use of SRM-derived MBM in a combustion facility. The model simulates the potential infectivity pathways that SRM-derived MBM follows, including its production from animals potentially infected with sub-clinical BSE and subsequent processing of the material with segregation and heat treatments. A failure probability was included to take account of sub-optimal operating conditions. Two scenarios, reflecting the infectivity risk in different animal tissues as defined by the European Commissions scientific steering committee (SSC), were performed with 100,000 iterations of the model. Model results showed that the societal exposure to humans resulting from the combustion of SRM-derived MBM is extremely small (mean values ranging from 7.57 x 10(-6) ID50/year to 8.38 x 10(-5) ID50/year). The resulting societal risks are significantly less than the background societal risk of approximately 2.5 cases of sporadic CJD in Ireland each year. A sensitivity analysis revealed that the species barrier had a large impact on exposure calculations and hence should be the focus of further scientific investigation to reduce our uncertainty about this parameter. The model predicts that material spillage into untreated effluent represents the biggest risk to humans, indicating that efforts for risk mitigation should be focused on reducing the potential for spillage.