@article {Cummins:2001:1366-9877:251,
title = "Predictive modelling and risk assessment of BSE: a review",
journal = "Journal of Risk Research",
parent_itemid = "infobike://routledg/rjrr",
publishercode ="routledg",
year = "2001",
volume = "4",
number = "3",
publication date ="2001-07-01T00:00:00",
pages = "251-274",
itemtype = "ARTICLE",
issn = "1366-9877",
eissn = "1466-4461",
url = "https://www.ingentaconnect.com/content/routledg/rjrr/2001/00000004/00000003/art00005",
doi = "doi:10.1080/13669870152023809",
author = "Cummins, Enda J. and Grace, Patrick M. and McDonnell, Kevin P. and Ward, Shane M. and Fry, D. John",
abstract = "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 5.114.2. 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 animal's 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.",
}