This dissertation focuses on immunological, epidemiological, and economic modeling of HIV, influenza, and fungal meningitis, and includes three research studies. In the first study on HIV, the study objective is to analyze the dynamics of HIV-1, CD4+ T cells and macrophages during the acute, clinically latent and late phases of HIV infection in order to predict their dynamics from acute infection to clinical latency and finally to AIDS in treatment naive HIV-infected individuals. The findings of the study show that the peak in viral load during acute HIV infection is due to virus production by infected CD4+ T cells, while during the clinically latent and late phases of infection infected macrophages dominate the overall viral production. This leads to the conclusion that macrophage-induced virus production is the significant driver of HIV progression from asymptomatic phase to AIDS in HIV-infected individuals. In the second study on influenza, the study objective is to estimate the direct and indirect epidemiological and economic impact of vaccine interventions during an influenza pandemic in Chicago, and assist in vaccine intervention priorities. Population is distributed among high-risk and non-high risk within 0-19, 20-64 and 65+ years subpopulations. The findings show that based on risk of death and return on investment, high-risk groups of the three age group subpopulations can be prioritized for vaccination, and the vaccine interventions are cost-saving for all age and risk groups. In the third study on fungal meningitis, the study objective is to evaluate the effectiveness and cost of the fungal meningitis outbreak response in New River Valley of Virginia during 2012-2013, from the local public health department and clinical perspectives. We estimate the epidemiological effectiveness of this outbreak response to be 153 DALYs averted among the patients, and the costs incurred by the local health department and clinical facilities to be $30,413 and $39,580 respectively. Moving forward, multi-scale analysis of infectious diseases connecting the different scales of evolutionary, immunological, epidemiological, and economic dynamics has good potential to derive meaningful inferences for decision making in clinical and public health practice, and improve health outcomes.