Biomathematics & Statistics Scotland
Statistical and mathematical modelling of nematode infection in lamb
The roundworm Teladorsagia circumcincta infection is an endemic problem in sheep in the temperate region of the world, and it is currently a major cause of parasitic gastroenteritis in sheep populations across UK. Apart from being an important disease from animal welfare perspective, it reduces the efficiency of production system resulting significant economic loss. Currently, control is achieved by administration of anthelmintics to susceptible animals but the problem is further aggravated due to the development of drug resistant parasite. This has also an impact on sustainability of sheep production system.
A sustainable sheep production system therefore would need to include animals with a better ability to cope with infection. This can be achieved by incorporating both non-genetic and genetic control strategies. Researchers at Roslin Institute have carried out extensive research to investigate genetic basis of disease resistance of sheep against roundworm infection. Researchers at Moredun Research Institute are currently exploring different non-genetic control strategies through extensive experimental work on T. circumcincta infection in lambs, investigating the effects of various anthelmintic treatment strategies on variables of economic interests. Different treatment strategies including targeted treatment of individual animal and whole flock treatments in combination with appropriate time intervals are investigated. Several physiological, immunological and molecular variables are measured at individual level and some relevant variables are also measured at pasture levels. Many of these variables are also temporal and spatial in nature.
The experimental dataset will form the basis of the proposed research programme. Initially, data will be analysed using appropriate linear and non-linear mixed effects model. The objective is to identify the genetic and non-genetic factors that contribute to the variation in different economic and indicator traits in lambs. At the second phase, an integrated process model will be developed in a Bayesian inferential framework borrowing information from different sources (for example, at the animal and pasture level). This will allow devising of a biologically driven model that provides full assessment of different sources of variation and their possible interaction with the variables of interest. Finally, an epidemiological model of nematode infection in sheep will be developed in a deterministic / stochastic framework incorporating both genetic and non-genetic mechanisms. Statistical analyses from the available data and published literature information will be used to parameterise and validate the developed model. The validated model will be explored in silico under different scenarios of genetic and non-genetic control strategies and appropriate mechanisms that would reduce the severity of disease in the flock and optimise the production system will be identified.
The project will be jointly supervised by Dr. Mintu Nath (BioSS), Prof. Steve Bishop (Edinburgh University) and Dr. Fiona Kenyon (Moredun Research Institute). The student will be based at BioSS unit in Edinburgh. Applicants should be numerate, have good mathematical and/or statistical knowledge and be interested in the application of statistical methods to complex data sets from biological research.
For further details, contact Mintu Nath
