This chapter discusses the dynamics of infectious diseases, emphasizing the importance of understanding the complex interactions between pathogens, hosts, and the environment. It highlights that over 25% of global deaths are caused by infectious diseases, including HIV/AIDS, SARS, Hantavirus, Lyme disease, Ebola, BSE/vCJD, STDs, West Nile, and the plague. The chapter also addresses the impact of these diseases on both human and animal populations, noting that humans are not the ultimate predators despite their ability to decimate populations. The chapter introduces simple models of epidemics, such as the constant infection model, which assumes a constant rate of infection and cure. This model has a single stable equilibrium, indicating that the disease will persist in the population. More complex models, like the SIR model (Susceptible, Infected, Removed), are discussed, which incorporate the dynamics of infection and recovery, and can predict epidemic thresholds and dynamics. The chapter then delves into the biology and epidemiology of HIV/AIDS, explaining how HIV attacks helper T cells, leading to a gradual depletion of the immune system. It provides historical context, noting that since its discovery in 1981, HIV/AIDS has infected 37.8 million people, with significant impacts on population demography and life expectancy in affected regions. The chapter also explores modeling approaches for HIV/AIDS, including statistical fitting, individual-based models (IBMs), and compartment models. It introduces the Simple IC Model (sIC), which simplifies the dynamics of sexually transmitted diseases by considering age and gender. The sIC model is used to analyze the effects of condom use and sexual partner mixing on HIV prevalence. Finally, the chapter discusses the full IC model, which is more complex, incorporating multiple age classes, stages of HIV infection, and sexual activity groups. This model is used to predict HIV prevalence over time and across different age groups, providing insights into the dynamics of the epidemic and the effectiveness of various intervention strategies.This chapter discusses the dynamics of infectious diseases, emphasizing the importance of understanding the complex interactions between pathogens, hosts, and the environment. It highlights that over 25% of global deaths are caused by infectious diseases, including HIV/AIDS, SARS, Hantavirus, Lyme disease, Ebola, BSE/vCJD, STDs, West Nile, and the plague. The chapter also addresses the impact of these diseases on both human and animal populations, noting that humans are not the ultimate predators despite their ability to decimate populations. The chapter introduces simple models of epidemics, such as the constant infection model, which assumes a constant rate of infection and cure. This model has a single stable equilibrium, indicating that the disease will persist in the population. More complex models, like the SIR model (Susceptible, Infected, Removed), are discussed, which incorporate the dynamics of infection and recovery, and can predict epidemic thresholds and dynamics. The chapter then delves into the biology and epidemiology of HIV/AIDS, explaining how HIV attacks helper T cells, leading to a gradual depletion of the immune system. It provides historical context, noting that since its discovery in 1981, HIV/AIDS has infected 37.8 million people, with significant impacts on population demography and life expectancy in affected regions. The chapter also explores modeling approaches for HIV/AIDS, including statistical fitting, individual-based models (IBMs), and compartment models. It introduces the Simple IC Model (sIC), which simplifies the dynamics of sexually transmitted diseases by considering age and gender. The sIC model is used to analyze the effects of condom use and sexual partner mixing on HIV prevalence. Finally, the chapter discusses the full IC model, which is more complex, incorporating multiple age classes, stages of HIV infection, and sexual activity groups. This model is used to predict HIV prevalence over time and across different age groups, providing insights into the dynamics of the epidemic and the effectiveness of various intervention strategies.