Prof. Iain McKendrick

As co-director of EPIC, I am responsible for Quantitative Innovation and Operations. I specialise in animal health and welfare and coordinate the work of EPIC's quantitative scientists, while also supporting activities that promote information sharing and collaboration across different partner organizations. Aside from EPIC's corporate governance, I worked with the Scottish Environment, Food, and Agriculture Research Institutes, as well as participated in work on other projects and centres funded by the Scottish Government's Rural and Environment Science and Analytical Services Division. Within EPIC, I lead Challenge 6 which focuses on data management.


Mathematical modelling of livestock diseases sparked my interest as an undergraduate mathematician, and my PhD project examined models for the spread of rabies, particularly the issue of incorporating spatial-temporal aspects. Prior to joining Biomathematics and Statistics Scotland in 1996, I worked for three years on disease diagnosis in East African livestock. With key partners such as Moredun Research Institute and SRUC, I led all BioSS activities related to animal health and welfare from 2006. As Head of Consultancy at BioSS, I've recently handed over responsibility for animal welfare and health to others.

Developing BioSS expertise in quantitative veterinary epidemiology has been an essential activity for me. In 2006, I became a founding member of EPIC after analysing and modelling E. coli O157 dynamics and ovine pulmonary adenocarcinoma. During my time at EPIC, I have built statistical models linking different sources of epidemiologically significant data, modelled and parameterized models of pathogen spread, developed scenario planning methodologies for future policy-oriented issues, and designed more effective statistical methods for syndromic surveillance. The current EPIC programme (2022-25) involves developing models for integrating different datasets and sources of disease freedom information, managing provenances and other types of metadata when delivering policy-relevant quantitative science, and creating a framework for formulating scientific research proposals that are relevant to policy.

In addition to my work with EPIC, I am progressing with a long-term project to promote a better interpretation of veterinary anthelmintic test results using a comprehensive, 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. These guidelines will be aimed at the interpretation of test data when seeking to identify anthelmintic resistance.