Staff, Students, and Associates

Professor Iain McKendrick
Head of Consultancy

PhD

Biomathematics and Statistics Scotland
JCMB, The King's Buildings,
Peter Guthrie Tait Road,
EDINBURGH, EH9 3FD, Scotland, UK.

Tel: +44 (0)131 650 4894
Publications:

Consultancy

I am the Head of Consultancy for BioSS.  My role is to promote and lead all strategic application-led activities in the organisation.  Although a major part of my remit is to deliver and manage statistical, mathematical modelling and bioinformatics advice and support to partner organisations and collaborators (what most people would understand as 'consultancy'), my staff and I also lead on work which would more conventionally be described as research.  BioSS delivers novel applied research, where sometimes the novelty is in the methodology, sometimes in the application, and sometimes both.  So my remit includes research projects where the impetus comes from the application topic.  The work we do will draw on our areas of methodological expertise, and will typically focus on applications in the areas in which we actively seek to collaborate.  If you are keen to collaborate with BioSS, and are unsure whether your application area will be of interest to us, please feel free to contact me to discuss your ideas.

I manage a team of Principal Consultants, each of whom leads work in one of our key application areas: Sarah Brocklehurst in Animal Health and Welfare, Nick Schurch in Ecology and Environment Sciences, Katharine Preedy in Plant and Crop Science, and Graham Horgan in Human Health and Nutrition.

I project manage BioSS consultancy inputs to the Strategic Research Programme funded by the Rural and Environment Science and Analytical Services Division of the Scottish Government. If you are looking for consultancy support for your work in this programme, please find contact details here

We also provide quantitative consultancy on an ad hoc basis, although we prefer to collaborate on larger projects over the long term: this allows us to be more effective in helping you meet your objectives. In recent years our clients have included scientists in the University of Edinburgh, NatureScot, and a number of commercial companies.  My team of BioSS consultants and I have extensive experience in the design and analysis of epidemiological and clinical studies, field trials, surveys and field studies across our key application areas, using both statistical, mathematical modelling and bioinformatics techniques. If you need input from trained statisticians and mathematicians, please feel free to contact me, or one of the Principal Consultants listed above to discuss your needs.

 

Personal Research Interests

I have 33 years of postdoctoral experience in the fields of statistics and mathematical modelling, mostly focussing on animal health and welfare applications, with some work on environmental and ecological applications.  I have a deep understanding of the theory of mathematical modelling, and extensive experience of applying these models to a range of pathogen systems, including rabies, Johne’s Disease, E. coli O157 transmission dynamics, Ovine Pulmonary Adenomatosis and Foot and Mouth Disease, both in UK and African farming systems. 

I am a Visiting Professor in the School of Biodiversity, One Health and Veterinary Medicine at the University of Glasgow.

Much of the work carried out my myself or in my group in recent years has focussed on statistical methods; I have a broad knowledge of statistical methodologies relevant to epidemiological problems, applying methods such as generalised linear mixed modelling, zero inflated modelling and mixture modelling to a variety of problems in veterinary epidemiology, most notably E. coli O157, bovine TB, and OPA.  More innovative statistical work has been carried out in collaboration with animal-health collaborators, with the work on non-‘gold standard’ methods for diagnostic test evaluation, and work on methods to integrate cross-sectional disease prevalence data with administrative cattle movement data within a Gaussian Markov random field framework being particularly valuable (both with Giles Innocent.

More recently I have been progressing a long-term project to promote better interpretation of veterinary anthelmintic test results using a new, statistically coherent, framework. These ideas have been adopted as part of new guidelines to be issued by the World Association for the Advancement of Veterinary Parasitology for the interpretation of test data when seeking to identify anthelmintic resistance, and are described in a paper recently published by Veterinary Parasitology.

I have also led collaborative work in the use of ‘futures’-methodologies to capture qualitative uncertainty and provide a mechanism for structured horizon scanning, and have published on the ethical issues arising from the use of quantitative models to support decision making, proposing a framework in which to assess the ethical impact of mathematical and statistical models.  My current research plans include work to more fully integrate ‘futures’ methods and ethical assessment into processes to evaluate quantitative epidemiological models.

I have also recently gained funding to develop a process model to integrate expert opinion and observed data when quantifying the probability of ‘freedom from disease’ after a disease incursion/when seeking disease eradication.  Work in the EPIC Centre of Expertise (see below) will seek to apply this method at a UK-wide policy level, while I will also consider potential uses for farm-level eradication of OPA, sheep scab and BVDv.

Much work over the past 3 years has focused on the development of the ‘FAIR data pipeline’ with collaborators at the University of Glasgow.  This is a collaborative project, aiming to develop a software infrastructure to support application of FAIR principles in epidemiological modelling, where my specific focus has been on the development of metadata standards and a registry to store these metadata.  The aim is to develop a system which will make it easier for quantitative modellers to maintain a clear audit trail for the provenance of their outputs, ensuring that results provided to policy customers will have associated metadata that delivers FAIR-ness, while also increasing the scientific transparency of results and facilitating better quality management.  With my collaborators I now anticipate rolling out the FAIR data pipeline for use in veterinary epidemiological modelling, and for other, environment and ecologically focussed, quantitative applications across BioSS, in the hope that the evidence accrued from these activities will help unlock further funding for the pipeline project.

If you are interested in any of these activities, and would like to explore opportunities to collaborate, I am keen to talk with you.

 

EPIC Centre of Expertise

EPIC is the Scottish Government-funded Centre of Expertise in Animal Disease Outbreaks.  I am the Director of Quantitative Innovation and Operations, leading this virtual centre in concert with two other Co-Directors. The remit of the centre is to support Scottish Government in preparing for future incursions of exotic disease into Scottish livestock, and to improve surveillance of livestock on an ongoing basis.  The work carried out depends on the succesful integration of expertise in veterinary epidemiology with skills in statistics and mathematical modelling.  It draws on the expertise of researchers from six universities and research institutes: it has been in operation since 2006, when I was a founder member of the consortium.  As my job title suggests, I have a specific role in co-ordinating the work of the quantitative scientists in EPIC, supporting activities which promote sharing of information and new and effective collaborations across different partner organisations.  More information about EPIC is available here.  BioSS work within EPIC is led by Dr Giles Innocent; if you want to discuss aspects of EPIC work specific to BioSS, please contact him.  If you want to discuss EPIC as a consortium, and the work we do as a collective, please feel free to contact me.