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    The spatio-temporal epidemiology of Bovine spongiform encephalopathy and Foot-and-mouth disease in Great Britain : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Massey University
    (Massey University, 2003) Stevenson, Mark Anthony
    Great Britain suffered two of the most globally notable animal disease epidemics of recent decades — the bovine spongiform encephalopathy (BSE) epidemic which began in November 1986, and the foot-and-mouth disease (FMD) epidemic which lasted from February to September 2001. This thesis applies various analytical techniques to these two quite different epidemics: a rapidly spreading highly contagious disease for which urgent decisions are essential (FMD), and a feed-borne non-contagious disease with an exceptionally long incubation period (BSE). The BSE epidemic, in particular, presented major investigational challenges because its recent emergence meant that its epidemiological features were not yet fully clear. The studies of BSE reported here showed that the control measures recommended as a consequence of the first epidemiological study of the new disease were remarkably effective. The July 1988 meat and bone meal ban resulted in a 60% reduction in BSE risk for cattle born in the first 12 months after its introduction. Descriptive spatial analyses, using kernel density and regression techniques showed a marked concentration of BSE risk in the south of Great Britain. Following the July 1988 meat and bone meal ban BSE risk shifted to the east of the country, an effect partly explained by cross contamination of cattle feed with high-protein concentrates destined for the pig and poultry industry. Detailed investigation of the earliest BSE-exposed farm holdings identified the south of England as an area of excess exposure density. While interpretation of these findings is complicated by the fact that the disease must have been present for some years before it was first diagnosed, the evidence suggests initial amplification in the south provided risk material which progressively distributed the disease to the rest of the country. In contrast to BSE, FMD presents different challenges, in that affected farms can be diagnosed rapidly, but it is difficult to accurately evaluate the relative importance of the different mechanisms of transmission, and hence determine how best to apply control efforts. Foci of FMD infection of matched size in the English counties of Cumbria and Devon were compared to dissect out factors contributing to the two quite different epidemic patterns in these areas. This analysis showed evidence of strong spatio-temporal interaction of infection risk in Cumbria, due initially to cattle herds as the dominant influence, with a later growth in the role of sheep as a source of infection. During the FMD epidemic a stochastic spatial simulation model was used extensively as an aid for decision making. After the epidemic was over the predictive accuracy of earlier real-time modelling was assessed for the whole of Britain and the most concentrated focus of disease in Cumbria. The model predicted the temporal epidemic curve closely at both levels, and predicted the national spatial pattern of infection with high specificities (over 99%) and useful sensitivities (37% to 71%). It was concluded that the model predicted FMD-infected locations within 0 to 14 days after simulation start date with sufficient accuracy to guide surveillance activities and to provide estimates of resources required for contingency planning. The spatial accuracy of predictions might be further improved through the use of a series of sub-regional models, better-capturing the characteristics of individual outbreak foci that typically emerge during extended large scale, multicentred epidemics. The studies presented in this thesis demonstrate that the application of temporal, spatial and spatio-temporal analytical methods can enhance the understanding of the epidermiological features of diseases in animal populations. The value in applying these methods of analysis comes from the ability to identify high and low disease-risk time frames and locations, allowing more focused allocation of investigative resources.
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    Risk-based suveillance in animal health : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Massey University, Palmerston North, New Zealand
    (Massey University, 2009) Prattley, Deborah Jayne
    Animal health surveillance is an important part of animal health care, particularly in countries dependent on livestock for food production and international trade. There are two major issues related to the provision of e®ective surveillance activities. Firstly, for good information to become available, the design and conduct of data collection activ- ities should be carried out following sound statistical principles. In reality, constraints such as imperfect tests and unavoidably-biased sampling strategies hinder straightfor- ward analysis and interpretation of survey results. Risk-based surveillance is used to target high-risk sub-populations to increase e±ciency of disease detection; however, biased datasets are generated. This thesis develops methodologies to design risk-based surveillance systems and al- low statistically valid analysis of the inherently biased data they generate. The ¯rst example describes the development of a method to analyse surveillance data gathered for bovine spongiform encephalopathy (BSE). The data are collected from four dif- ferent surveillance streams of animals tested for BSE, with each stream containing unavoidable biases and limitations. In the BSurvE model, these data are combined with demographic information for each birth cohort to estimate the proportion of each birth cohort infected with BSE. The prevalence of BSE in a national herd can then be estimated using the method of moments, whereby the observed number of infected animals is equated with the expected number. The upper 95% con¯dence limit for the prevalence is estimated both for infected countries and for those where no BSE has previously been detected. A similar approach to that used in BSurvE is then applied to surveillance data for trichinellosis, for which risk-based post-mortem testing is also performed. Negative results from multiple species using di®erent, imperfect tests are combined to give an estimate of the upper 95% con¯dence limit of the national prevalence of trichinellosis in a reference population. This method is used to provide support for freedom from trichinellosis in Great Britain. A di®erent approach to risk-based surveillance is explored as the surveillance strategy for detection of exotic causes of abortion in sheep and goats in New Zealand is examined. Using a geographic information system (GIS) maps of disease risk factors were overlain to produce a risk landscape for the lower North Island. This was used to demonstrate how areas of high- and low-risk of disease occurrence can be identi¯ed and used to guide the design of a risk-based surveillance programme. Secondly, within one surveillance objective there may be many ways in which the available funds or human resources could be distributed. This thesis develops a method to assess BSE surveillance programmes, and provides tools to facilitate BSE detection on the basis of infection risk and to increase the e±ciency of surveillance strategies. A novel approach to allocation of resources is developed, where portfolio theory con- cepts from ¯nance are applied to animal health surveillance. The example of surveil- lance for exotic causes of sheep and goat abortion is expanded upon. Risk of disease occurrence is assessed for a population over di®erent time periods and geographical areas within a country, and portfolio theory used to allocate the number of tests to be carried out within each of these boundaries. This method is shown to be more likely to detect disease in a population when compared to proportional allocation of the available resources. The studies presented here show new approaches that allow better utilisation of imperfect data and more e±cient use of available resources. They allow development of surveillance programmes containing an appropriate balance of scanning and targeted surveillance activities. Application of these methods will enhance the implementation and value of surveillance in animal health.