Emergency departments (EDs) are an ideal venue to conduct screening for both HIV and HCV, given the high prevalence of HIV and HCV risk-taking behaviors among ED patients (e.g., sexual risk and drug use, particularly injection-drug use during the current opioid epidemic in the US); the known feasibility and acceptability of HIV and HCV screening in this setting; the proven yield of identifying those with undiagnosed infections in the ED; and the ability to link those with infections to subsequent care after the ED visit.

The collaborative research study “Real Time Phylogeny and Contact Tracing to Disrupt HIV Transmission” is conducted to evaluate the benefits of integrating different methods - contact tracing used to obtain social information from HIV-infected persons, and phylogenetics used to compare HIV between infected persons - to disrupt HIV transmission in the state of Rhode Island.

This collaborative research will generate new information on the development of treatment failure and drug resistance among a large, well-characterized cohort of HIV-infected children in western Kenya who receive common medications, using detailed, longitudinal, clinical, adherence, and drug concentration data. The proposed research is relevant to public health since such information is limited in the scientific literature, and withot it we cannot accurately assess treatment failure and drug resistance in HIV-infected children, which can lead to sickness and death.

By increasing understanding of how excessive alcohol consumption and interventions to reduce excessive drinking can impact HIV-related health outcomes and sexual behavior that transmits HIV, this program project can contribute greatly to efforts to reduce alcohol use and improve the health of those living with HIV and to reduce the spread of HIV.

The overall goal of the Fogarty HIV Research Training (HIVRT) Program is to strengthen the scientific capacity of institutions in low- and middle-income countries (LMICs) to conduct HIV research on the evolving HIV epidemic in their countries. Trainees will be jointly trained by the biostatistics program at Brown and by experts in a broad domain of HIV research. Trainees are expected to contribute their knowledge and assist with the buildup of scientific programs to reduce HIV pandemic in LMICs. 

Effective use of antiretroviral therapy is critical for managing and preventing the spread of HIV in the developing world. Research in this domain includes developing methods that make optimal use of diagnostic tests having limited availability to monitor the effectiveness of therapy and to prompt a change in regimen when it is warranted. Machine learning methods can be used to derive the best strategies to treat HIV along the HIV treatment cascade.  Successful implementation is expected to improve patient outcomes and help to prevent the spread of treatment-resistant strains of HIV.

The interaction of human papillomavirus (HPV) with human immunodeficiency virus (HIV) represents one of the most "dangerous liaisons" for women in Sub-Saharan Africa. Almost all cervial cancers are caused by persistent high-risk HPV. Persistent HR-HPV infection is more common among women with HIV comnpared to HIV-negative women. Understanding the prevalence and persistence of HPV infection and addressing the modifiable co-factors could have profound implications on strategies to treat the infection and reduce cervical cancer.