A Brief Chronicle of CD4 as a Biomarker for HIV/AIDS: A Tribute to the Memory of John L. Fahey.

Foundational cellular immunology research of the 1960s and 1970s, together with the advent of monoclonal antibodies and flow cytometry, provided the knowledge base and the technological capability that enabled the elucidation of the role of CD4 T cells in HIV infection. Research identifying the sources and magnitude of variation in CD4 measurements, standardized reagents and protocols, and the development of clinical flow cytometers all contributed to the feasibility of widespread CD4 testing. Cohort studies and clinical trials provided the context for establishing the utility of CD4 for prognosis in HIV-infected persons, initial assessment of in vivo antiretroviral drug activity, and as a surrogate marker for clinical outcome in antiretroviral therapeutic trials. Even with sensitive HIV viral load measurement, CD4 cell counting is still utilized in determining antiretroviral therapy eligibility and time to initiate therapy. New point of care technologies are helping both to lower the cost of CD4 testing and enable its use in HIV test and treat programs around the world.

Evaluating the Impact of the Positive Choices Intervention on Substance Use, Psychological, and Care Engagement Outcomes Relevant to Current National HIV Prevention Goals

The HIV epidemic in the United States continues to be a significant public health problem, with approximately 50,000 new infections occurring each year. National public health priorities have shifted in recent years towards targeted HIV prevention efforts among people living with HIV/AIDS (PLWHA) that include: increasing engagement in and retention in care, improving HIV treatment adherence, and increasing screening for and treatment of substance use and psychological difficulties. This study evaluated the efficacy of Positive Choices (PC), a brief, care-based, theory-driven, 3-session counseling intervention for newly HIV-diagnosed men who have sex with men (MSM), in the context of current national HIV prevention priorities. The study involved secondary analysis of data from a preliminary efficacy trial of the PC intervention (n=102). Descriptive statistics examined baseline substance use, psychological characteristics and strategies, and care engagement and HIV-related biological outcomes. Generalized Estimating Equations (GEE) examined longitudinal changes in these variables by study condition. Results indicated that PC improved adherence to HIV treatment, but increased use of illicit drugs, specifically amyl nitrates and other stimulant drugs; additionally, moderation analyses indicated differences in patterns of change over time in viral load by baseline depression status. Implications of the findings and suggestions for future research are discussed.

Drivers of Dengue Within-Host Dynamics and Virulence Evolution

Dengue is an important vector-borne virus that infects on the order of 400 million individuals per year. Infection with one of the virus's four serotypes (denoted DENV-1 to 4) may be silent, result in symptomatic dengue 'breakbone' fever, or develop into the more severe dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS). Extensive research has therefore focused on identifying factors that influence dengue infection outcomes. It has been well-documented through epidemiological studies that DHF is most likely to result from a secondary heterologous infection, and that individuals experiencing a DENV-2 or DENV-3 infection typically are more likely to present with more severe dengue disease than those individuals experiencing a DENV-1 or DENV-4 infection. However, a mechanistic understanding of how these risk factors affect disease outcomes, and further, how the virus's ability to evolve these mechanisms will affect disease severity patterns over time, is lacking. In the second chapter of my dissertation, I formulate mechanistic mathematical models of primary and secondary dengue infections that describe how the dengue virus interacts with the immune response and the results of this interaction on the risk of developing severe dengue disease. I show that only the innate immune response is needed to reproduce characteristic features of a primary infection whereas the adaptive immune response is needed to reproduce characteristic features of a secondary dengue infection. I then add to these models a quantitative measure of disease severity that assumes immunopathology, and analyze the effectiveness of virological indicators of disease severity. In the third chapter of my dissertation, I then statistically fit these mathematical models to viral load data of dengue patients to understand the mechanisms that drive variation in viral load. I specifically consider the roles that immune status, clinical disease manifestation, and serotype may play in explaining viral load variation observed across the patients. With this analysis, I show that there is statistical support for the theory of antibody dependent enhancement in the development of severe disease in secondary dengue infections and that there is statistical support for serotype-specific differences in viral infectivity rates, with infectivity rates of DENV-2 and DENV-3 exceeding those of DENV-1. In the fourth chapter of my dissertation, I integrate these within-host models with a vector-borne epidemiological model to understand the potential for virulence evolution in dengue. Critically, I show that dengue is expected to evolve towards intermediate virulence, and that the optimal virulence of the virus depends strongly on the number of serotypes that co-circulate. Together, these dissertation chapters show that dengue viral load dynamics provide insight into the within-host mechanisms driving differences in dengue disease patterns and that these mechanisms have important implications for dengue virulence evolution.