Angus McLure

Dr Angus McLure is a Research Fellow at the National Centre for Epidemiology and Population Health at The Australian National University. His work focuses on mathematical modeling of infectious diseases, with particular expertise in lymphatic filariasis elimination, molecular xenomonitoring, and foodborne disease source attribution. He has developed analytical tools including the R package PoolTestR for molecular xenomonitoring data analysis and has collaborated extensively with researchers like Katie Glass and Martyn Kirk across multiple disease systems.

Dr McLure completed his PhD in Epidemiology at ANU from 2015 to 2019, following a Bachelor of Philosophy (Honours) in Science from 2011 to 2014. His academic journey at ANU has positioned him as a key contributor to infectious disease modeling research within the Centre of Epidemiology for Policy and Practice and the Infectious Diseases and Modelling Group.

His research spans multiple infectious disease domains with a strong emphasis on mathematical modeling approaches. Dr McLure has made significant contributions to understanding lymphatic filariasis transmission dynamics and elimination pathways, as well as foodborne disease epidemiology. His work addresses critical public health questions related to disease elimination strategies, surveillance methods, and source attribution across pathogens including Campylobacter, Salmonella, C. difficile, and Dengue.

His publication record shows a strong focus on lymphatic filariasis elimination strategies and foodborne disease modeling, with 24 research outputs between 2017-2025. The articles demonstrate expertise in mathematical modeling, molecular epidemiology, and public health intervention evaluation, often bridging theoretical modeling with practical public health applications in disease elimination and food safety contexts.

Dr McLure is actively involved in multiple research projects including 'New tools to accelerate elimination of the preventable parasite disease lymphatic filariasis' (2025-2028), 'Estimate the cost of foodborne illness by food commodities and pathogens' (2023), and previous projects on foodborne illness source attribution. His h-index of 9 reflects his growing impact in the field of infectious disease epidemiology and mathematical modeling.