Ramsès Djidjou Demasse
AgreenSkills session, year: 1st session, 2015
Receiving laboratory: SAVE Vine Health and Agroecology, Bordeaux, Aquitaine
Country of origin : Cameroon
Evolutionary Epidemiology of vine diseases: data and models to sustainably manage varietal resistance to mildew.
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 hold a PhD in Mathematics (option Dynamical Systems and Modeling) of the University of Yaoundé 1. My research interest focuses on the modeling of complex systems (epidemiology, population dynamics, evolutionary biology of plant pathogens). 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.
I work in close collaboration with scientists from different disciplines, mathematics and human, animal and plant epidemiology. During my PhD, I was interested by the human infectious diseases (malaria, tuberculosis, hepatitis B virus and HIV). I also held a position of visitor scientist at some institutions like the Institut Pasteur of Paris, Université De Lorraine and Université de Bordeaux. I have some years of teaching experience of Scientific Computing and Mathematics to undergraduate students of The National Advanced School of Engineering and The Higher Teacher’s Training College of The University of Yaoundé 1.
Since April 2015, I’m enrolled in a multidisciplinary project for plant infectious diseases funded by the CIVB (Conseil Interprofessionnel du Vin de Bordeaux) and the AgreenSkills+ postdoctoral grant. 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 and thus reduce the pesticide use.
(*) R. Djidjou-Demasse, B. Moury, F. Fabre. Mosaics of plant disease resistance genes are a more versatile means of achieving disease control than pyramids in most agricultural landscapes. (to appear in New Phytologist).
(*) R. Djidjou-Demasse, A. Ducrot, F. Fabre. Steady state concentration for a phenotypic structured problem modelling the evolutionary epidemiology of spore producing pathogens. Mathematical Models and Methods in Applied Sciences, 2016.
(*) R. Djidjou Demasse, J.J. Tewa, S. Bowong, Y. Emvudu. Optimal control of an age-structured model for the transmission of hepatitis B with differential infectivity. Journal Of Mathematical Biology, Vol. 73(2):305-33, 2016.
P. Tchinda, R. Djidjou Demasse, J.J. Tewa, M.A. Aziz-Alaoui. Bifurcation analysis and optimal harvesting of a delayed predator-prey model. International Journal of Bifurcation and Chaos, Vol. 25 (1), 2015.
R. Djidjou Demasse, J.J. Tewa, S. Bowong. Analysis of an Age-structured SIL model with demographics process and vertical transmission, ARIMA Journal, Vol. 17:23-52, 2014.
(*) R. Djidjou Demasse, A. Ducrot. An age-structured within-host model for multi-strain malaria infections. SIAM Journal on Applied Mathematics, Vol. 73(1):572-593, 2013.
J.J.Tewa, R. Djidjou Demasse, S. Bowong. Predator-prey model with prey harvesting, Holling response function of type III and SIS disease. Biomath 1, 2012.
Y. Emvudu, R. Djidjou Demasse, D. Djeudeu. Optimal Control of the Lost to Follow Up in a Tuberculosis Model. Computational and Mathematical Methods in Medicine, Vol. 2011.
(*) Y. Emvudu, R. Djidjou Demasse, D. Djeudeu. Optimal control using state dependent Riccati equations in a tuberculosis model. Computational and Applied Mathematics, 32(2), 191-210,2013.
R. Djidjou Demasse, A. Mendy, Lam Mountaga, J. J. Tewa. Analysis of an Age-Structured SEIL Model with Demographics Process and Lost of Sight Individuals. R. Brewer (Ed.). (2015). Ordinary and Partial Differential Equations [Chapter 2].