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Title: Predictive modelling of ovine haemonchosis risk based on the effects of climate on the free-living stages of H. contortus
Author: Bolajoko , Muhammad-Bashir
ISNI:       0000 0004 5372 6892
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2014
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The gastrointestinal nematode parasite Haemonchus contortus is responsible for substantial global disease and production loss in small ruminants. These losses may be exacerbated by climate change, and by increasingly widespread resistance to anthelmintics. Development of successful integrated-sustainable parasite control (IPC) requires adequate knowledge of how climate drives the population dynamics of H. contortus and the seasonal occurrence of ovine haemonchosis. Therefore a simple model based on climate that is able to predict future challenge and risk resulting from H. contortus could greatly contribute to sustainable control. This thesis set forth to develop a simple, universally-applicable and useful model of H. contortus transmission to sheep; with focus on the effects that changes in climate have on the availability of infective larvae. The study aimed to (i) analyse and predict the effect(s) that changes in climate will have on H. contortus infection pressure in sheep across different geo-climatic zones; (ii) map the risk and geographical distribution of H. contortus infection pressure over time; and (iii) provide farmers with useful information on risk of infection to make cost-effective farm management decisions for sustainable control of H contortus. South Africa and the United Kingdom are the study locations. Time series analyses (TSA) was first used, as a purely statistical approach and starting point to assess the seasonal forcing influence that climate (rainfall and temperature) has on the pattern and incidence of haemonchosis. This aimed to find out if a statistical approach can identify valid climatic predictors of the risk of haemonchosis across different geo-climatic zones. Thereafter, a second model, based on the basic reproduction quotient (Qo), which is a process-based mechanistic approach, was employed to understand the effects of changes in climate on the population dynamics (i.e. transmission potential) of the free-living stages, and to predict E-[. contortus infection pressure across different geo-climatic zones. The model tries to replicate and summarize the underlying mechanisms that drive the response of parasite populations to changes in prevailing climatic variables. Finally, the use of the Qo model as a decision SUppOlt tool on farms was assessed by comparing predictions to observed faecal egg counts in south-west England over the course of a grazing season. Results suggest that TSA is able to predict the relationship between prevailing climatic conditions and the incidence of haemonchosis in a given area. However, the climatic predictors and best-fit-model were not transferable across different geo-climatic zones. Local data are needed in order to estimate coefficients for climatic predictors, such that extrapolation beyond the observed range becomes problematic and cumbersome. The Qo model, on the other hand, was able to capture the effects of seasonal variation in the prevailing climate on the pattern and incidence of haemonchosis across different geoclimatic locations. The model was spatially extended within a geographic information system (GIS) to produce Qo -based haemonchosis risk maps. The risk maps display the capability of Qo as a spatial predictor of haemonchosis risk across different geo-climatic zones over time. These risk maps have potential as spatial platforms for decision support systems, in support of integrated, sustainable control of H. contortus.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available