Classical mathematical models with enhanced flexibility have been used extensively to simulate and analyse the course and effect of intervention programmes on the dynamics of several infectious diseases. Lassa fever is one of such diseases whose outbreak is often witnessed in West Africa. This work presents a mathematical model that investigates the impact of awareness levels of susceptible individuals as well as the diagnosis and treatment of both symptomatic and asymptomatic individuals on the transmission dynamics of Lassa fever in a population. The model developed in this paper divided the host population into two: the human host population and the non-human primates (animal reservoirs). The total human host population was further sub-divided into eight human compartments according to the prevailing level of awareness, diagnostic status and the resulting treatment action plan. Our analysis showed that the model has a disease-free equilibrium (DFE), which is locally asymptotically stable whenever the reproduction number is less than unity. Numerical simulations of the model, using relevant demographic data from Nigeria, revealed that increasing the fraction of susceptible individuals with reasonable awareness will help in reducing the cumulative number of new Lassa fever cases. The simulation also suggests that increasing the fraction of symptomatic individuals that are diagnosed, isolated and treated will result in the reduction of the number of individuals infected with the disease in the population. However, the impact of diagnosis will be more positively felt if there are robust treatment and isolation policies that will allow for increased treatment rates for diagnosed infections.