Background
Michele is a postdoc at CRID under the African Consortium in Modelling for Effective Vector Control (ACoMVeC). Michele has a Msc and a Ph.D. in Bioinformatic and Biostatistic at University of Douala in Cameroon where she worked on use of Statistical and Machine Learning methods for plants identification encountered in Cameroon. The skills gain in Data Analysis, Mathematics and Biological system help her to move on malaria mathematical modelling where she aim to modelling the impact of insecticide resistance on the effectiveness of control tools (LLINs, IRS, Larvicides). The results of her work will help to inform public health decision makers on the measures to be taken for the effective management of existing or new controls tools to fight against malaria.
Research:
Using mathematical modelling to capture important biological informations on malaria vector insecticide resistance, elucidate the impact of such resistance on the dynamics of evolution of vector and human populations.
- Areas of interest:
| Mathematical modelling, Insecticide resistance, |
Data analysis and Machine Learning
