Doctor of Philosophy (Ph.D.)
Mathematics
Howard University
2017
Moussa Doumbia, Ph.D. is a faculty in the department of Mathematics at Howard University in Washington, DC. He earned his Ph.D. in Mathematics from Howard University of Washington, DC. Prior to coming to Howard, he earned a bachelor's degree in Mathematics (Magna cum laude) from the University of the District of Columbia (2004-2007). As an undergraduate, he did some research work about the cyclotomic points on a curve under the direction of Dr. Vernise Steadman.
He graduated from UDC a semester early. While in undergraduate school, he enjoyed the vibrant atmosphere of working through statistical and mathematical problems and in particular, the applications of ordinary differential equations. He is interested in a wide variety of equations that define dynamical systems, including difference equations, matrix equations, ordinary and partial differential equations, and delay equations. His work focuses on theoretical investigations and modeling of infectious diseases such as Malaria, TB, H1N1, Ebola… etc. He also maintains a great interest in data sciences. He speaks English, French, Mandingo and limited knowledge in Spanish. He enjoys running, traveling, and public speaking.
Mathematics
Howard University
2017
Mathematics
University of the District of Columbia
2007
Research day at Howard University
South Africa-US Conference in Mathematical Methods in Systems Biology and Population Dynamics, Cape Town
In this paper, we extend the mathematical model framework of Dembele et al. (2009), and use it to study malaria disease transmission dynamics and control in irrigated and non-irrigated villages of Niono in Mali. In case studies, we use our "fitted" models to show that in support of the survey studies of Dolo et al., the female mosquito density in irrigated villages of Niono is much higher than that of the adjacent non-irrigated villages. Many parasitological surveys have observed higher incidence of malaria in non-irrigated villages than in adjacent irrigated areas. Our "fitted" models support these observations. That is, there are more malaria cases in non-irrigated areas than the adjacent irrigated villages of Niono. As in Chitnis et al., we use sensitivity analysis on the basic reproduction numbers in constant and periodic environments to study the impact of the model parameters on malaria control in both irrigated and non-irrigated villages of Niono.