Dr Angus McLure
Areas of expertise
- Epidemiology 111706
- Epidemiological Modelling 420205
- Applied Mathematics 4901
Research interests
- Mathematical modelling of infectious diseases
- Molecular xenomontoring
- Surveillance and interventions in the endgame of elimination campagins
- Source attribution of foodborne pathogens
Biography
Dr McLure is mathematical modeller of infectious diseases. His current research includes modelling the transmission and elimination of lymphatic filariasis; the design and analysis of molecular xenomonitoring surveys (catching disease vectors such as mosquitos to detect the presence of a disease); and source attribution modelling of foodborne disease. Angus has worked on projects across a wide range of diseases and pathogens including, lymphatic filariasis, C. difficile, Dengue, Campylobacter, Salmonella, and many other foodborne diseases. Angus McLure developed and maintains an R package, PoolTestR, for the analysis of molecular xenomonitoring data and other applications where data are tested in pools: https://github.com/AngusMcLure/PoolTestR
Researcher's projects
- Developing statistical methods and software for the analysis of molecular xenomonotring data
- Modelling interventions for the elimination of Lymphatic filariasis
- Experimental design for molecular xenomonitoring data or other data tested in pools
- Improving source attribution models for foodborne diseases
- Source attribution of Australian Campylobacter spp. infections (part of the CampySource project)
Publications
- McLure, A, Shadbolt, C, Desmarchelier, P et al. 2022, 'Source attribution of salmonellosis by time and geography in New South Wales, Australia', BMC Infectious Diseases, vol. 22, no. 1.
- McLure, A, Graves , P, Lau, C et al. 2022, 'Modelling lymphatic filariasis elimination in American Samoa: GEOFIL predicts need for new targets and six rounds of mass drug administration', Epidemics, vol. 40.
- Cribb, D, Varrone, L, Wallace, R et al. 2022, 'Risk factors for campylobacteriosis in Australia: outcomes of a 2018-2019 case-control study', BMC Infectious Diseases, vol. 22, no. 586.
- McLure, A, O'Neill, B, Mayfield, H et al. 2021, 'PoolTestR: An R package for estimating prevalence and regression modelling for molecular xenomonitoring and other applications with pooled samples', Environmental Modelling and Software, vol. 145.
- Wallace, R, Bulach, D, McLure, A et al. 2020, 'Antimicrobial Resistance of Campylobacter spp. Causing Human Infection in Australia: An International Comparison', Microbial Drug Resistance, vol. 27, no. 4, pp. 518-528.
- McLure, A & Glass, K 2020, 'Some simple rules for estimating reproduction numbers in the presence of reservoir exposure or imported cases', Theoretical Population Biology, vol. 134, pp. 182-194.
- Wallace, R, Bulach, D, Jennison, A et al. 2020, 'Molecular characterization of Campylobacter spp. recovered from beef, chicken, lamb and pork products at retail in Australia', PLOS ONE (Public Library of Science), vol. 15, no. 7, pp. 1-18.
- McLure, A, Lau, C & Furuya Kanamori, L 2020, 'Has the effectiveness of Australia's travel bans against China on the importation of COVID-19 been overestimated?', Journal of Travel Medicine, vol. 28, no. 2.
- McLure, A, Clements, A, Kirk, M et al. 2019, 'Modelling diverse sources of Clostridium difficile in the community: importance of animals, infants and asymptomatic carriers', Epidemiology and Infection, vol. 147, no. e152, pp. 1-9.
- McLure, A, Furuya Kanamori, L, Clements, A et al. 2019, 'Seasonality and community interventions in a mathematical model of Clostridium difficile transmission', Journal of Hospital Infection, vol. 102, no. 2, pp. 157-164.
- McLure, A, Clements, A, Kirk, M et al. 2018, 'Clostridium difficile classification overestimates hospital acquired infections', Journal of Hospital Infection, vol. 99, no. 4, pp. 453-460pp.
- McLure, A, Clements, A, Kirk, M et al. 2017, 'Healthcare-Associated Clostridium difficile Infections are Sustained by Disease from the Community', Bulletin of Mathematical Biology, vol. 79, no. 10, pp. 2242-2257.
Projects and Grants
Grants information is drawn from ARIES. To add or update Projects or Grants information please contact your College Research Office.
- Combining Expert Elicitation Data and Cost of Illness Modelling (Secondary Investigator)
- Attributing the Source of Foodborne Salmonellosis in NSW (Primary Investigator)
