Using Viral Dynamics to connect clinical markers of disease progression to sequence evolution during HIV-1 infection

HIV-1 remains a global health challenge, with over 35 million people infected. The high rates of turnover and evolutionary adaptability exhibited by HIV-1 pose a particular challenge to HIV-1 vaccine development. We developed a dynamic model of HIV-1 infection that uses equilibration, adaptation, and inheritance to model the initial infection and successive generations of viral lineages. The model allows viruses to generate new lineages in proportion to their viral load. These lineages compete for immune cells to infect. We use this model to demonstrate how viruses with a sufficiently high mutation rate could overcome the immune system, even when most changes are expected to be detrimental to viral fitness. We have calibrated our model to match averages of CD4+ T cells/mm^3 and HIV-1 RNA/ml derived from 91 HIV-infected individuals studied longitudinally during various disease stages. We also explore the use of phylogenies to validate the underlying composition of viral load.