In this paper, I build epidemiological model to investigate the dynamics of spread of denguernfever in human population. I study the demographic factors that influence equilibrium prevalence,rnand perform a sensitivity analysis on the basic reproduction number. Among several interventionrnmeasures, the effects of two potential control methods for dengue fever are estimated:rnintroducing educate and treat the population. A stochastic model for transmission of denguernfever is also built to explore the effect of some demographic factors and review a number ofrncompartmental models in epidemiology which leads to a nonlinear system of ordinary differentialrnequations. I focus an SEIRS epidemic models with and without education and treatment.rnA threshold parameter R0 is identified which governs the spread of diseases,and this parameterrnis known as the basic reproductive number. The models have at least two equilibria, anrnendemic equilibrium and the disease-free equilibrium. We demonstrate that the disease will diernout, if the basic reproductive number R0 < 1. This is the case of a disease-free state, with norninfection in the population. Otherwise the disease may become endemic if the basic reproductivernnumber R0 is bigger than unity. Furthermore, stability analysis for both endemic and disease-freernsteady states are investigated and we also give some numerical simulations.rnThe second part of this dissertation deals with optimal education and treatment by drug strategyrnin epidemiology. We use optimal control technique on education and treatment to minimizernthe impact of the disease. Hereby we mean minimizing the spread of the disease in the population,rnwhile also minimizing the effort on education and treatment roll-out. We do this optimizationrnfor the cases of SEIRS models, and show how optimal strategies can be obtained whichrnminimize the damage caused by the dengue fever disease. Finally, we describe the numericalrnsimulations using the fourth-order Runge-Kutta method.rnComputational Science program, AAU i Dengue FeverrnApplication of Optimal Control