Dr. Antoine Barreaux is a Visiting Scientist under the Animal Health Theme and is based at the Duduville Campus.

He holds a Ph.D. in biology from the University of Neuchâtel, Switzerland.

In addition to joining icipe, Antoine is working as an epidemiologist and mathematical modeler in the mixed research unit Intertryp, department BIOS, at CIRAD (French Agricultural Research Centre for International Development), France. His previous engagements include a Senior Research Associate and a Research Associate position at the University of Bristol, UK, in the Schools of Biological Sciences and Veterinary Sciences, and a Postdoctoral Scholar position at Penn State University, US, in the Department of Entomology and the Centre for Infectious Disease Dynamics.

Antoine is a member of Isaac Newton Institute for Mathematical Sciences, Cambridge/ the Royal Society of Tropical Medicine and Hygiene/the European Society of Evolutionary Biology/ Evolutionary Demography Society/the British Society of Ecology/ Association for the Study of Animal Behaviour/ Multilateral Initiative on Malaria Society/ and American Society of Naturalists.

Some of his professional achievements are in the areas of Animal African Trypanosomiasis control, Human African Trypanosomiasis elimination, the development of mathematical frameworks to understand host-microbiome-pathogen interactions, and scientific outreach with the development and implementation of a board game aimed at educating primary-school aged children about arthropod disease vectors, pathogens they transmit, and approaches to combating infectious diseases in the UK & Zimbabwe.

His research aims to reduce vector-borne disease transmission by integrating translational and basic science in control programs and to inform policy. Antoine integrates experimental, field, and theoretical approaches to improve disease models and contribute to the implementation of improved or novel interventions. He is also developing species distribution models, robust data analysis pipelines and models of optimal decision-making under uncertainty.