CameroonCountry of destination:
Modeling evolution of pathogens has long been addressed through analysis of invasibility assuming that epidemiological and evolutionary time scales are distinct. These approaches assumed that selection take place at a much shorter time scale than the mutation. Assuming the population is at equilibrium, the analysis ignore short-term evolutionary and epidemiological dynamics despite their major interests for deriving management policies. Deriving managements policies of resistance gene to plant pathogens is one of the many examples where one want to make quantitative predictions about the transient evolutionary dynamics of strain frequencies when the epidemiological dynamics are not at equilibrium. Moreover, most models dealing with the theory of adaptation for understanding pathogens adaptation to Resistance (R) genes consider the case of qualitative R genes while quantitative R genes are much more available in genetics resources. It is an interdisciplinary project between the team of applied mathematicians at the Mathematical Institute of Bordeaux (IMB UMR CNRS 5251) and a team of biologists at INRA Bordeaux (SAVE UMR INRA 1065). The objectives of the project are 1) to develop epidemiological models adapted to the spore-producing pathogens in agro-ecosystems. We will particularly integrate in the model the life-history traits of pathogens typically measured in plant pathology (latency time; sporulation rate; …), 2) to analyze these models using both mathematical and scientific computing methods, to yield practical insights on the optimal deployment in time and space of resistant hosts in the vineyards and 3) to use the model and it simulation tool in participatory studies involving stakeholders.
I holds a PhD in Mathematics (Dynamical Systems and Modeling) of the University of Yaoundé. My research interest focuses on the modeling of complex systems (epidemiology, population dynamics, evolutionary biology). This leads most often to Ordinary Differential Equations systems, Differential Equations with Delays and / or Partial Differential Equations. The Mathematics / Computer Science tools are the different methods used to explore and analyze our models according to their level of complexity.
During my PhD, I held a position of visitor scientist at some institutions like the Institut Pasteur of Paris, Université De Lorraine and Université de Bordeaux. I have many years of teaching experience of Scientific Computing and Mathematics to undergraduate.
From September 2015 to November 2017, I was recruited on a multidisciplinary project between INRA and IMB funded by the CIVB and the AgreenSkills postdoctoral grant in SAVE (Vineyard Agroecology and Plant Health) research unit in Bordeaux. The project aims to: (i) modeling the evolutionary and epidemiological dynamics of downy mildew and (ii) study optimal strategies for deployment of resistance varieties in agro-ecosystems to manage the sustainability of quantitative resistance. Since December 2017, I am a postdoc at INSERM in IAME Lab in Paris. The project is focused on decision analysis tools to evaluate interventions designed for infectious diseases prevention, control, and care.
R. Djidjou-Demasse, B. Moury, F. Fabre. 2017. Mosaics of plant disease resistance genes are a more versatile means of achieving disease control than pyramids in most agricultural landscapes. New Phytologist, 216(1), 239-253.
R. Djidjou-Demasse, A. Ducrot, F. Fabre, 2017. Steady state concentration for a phenotypic structured problem modelling the evolutionary epidemiology of spore producing pathogens. Mathematical Models and Methods in Applied Sciences, 27, 385-426.
R. Djidjou-Demasse, J.J. Tewa, S. Bowong, Y. Emvudu. 2016. Optimal control of an age-structured model for the transmission of hepatitis B with differential infectivity. J. Math. Biol. 73(2):305-33. Doi: 10.1007/s00285-0150952-6.
P. Tchinda, R. Djidjou Demasse, J.J. Tewa and M.A. AzizAlaoui, 2015. Bifurcation analysis and optimal harvesting of a delayed predator-prey model. International J. of Bifurcation and Chaos, 25, 1550012. Doi 10.1142/ S0218127415500121.
R. Djidjou-Demasse and A. Ducrot, An age-structured within-host model for multi-strain malaria infections. SIAM Journal on Applied Mathematics, 73, 572-59.