Biostatistics/Epidemiology Training Grants in AIDS
 


Fellows






FELLOWS

Current Fellows (2012-2013)

Sarah Anoke is a first-year student in the Biostatistics doctoral program (academic advisor: Marcello Pagano) whose main focus is completing her core coursework. Her research interests are in Causal Inference and its application to observational studies in HIV.

Katherine Evans is a first-year student in the Biostatistics doctoral program (academic advisor: Judith Lok) whose main focus is completing her core coursework. Her research interests are the application of causal inference to infectious disease epidemiology. Because of her prior Master's degree, she took and passed the departmental written qualifying exam in early 2013 (during her first year here).

Emily Smith is a first-year student in the Global Health and Population doctoral program (academic advisor: Wafaie Fawzi) whose main focus is completing her core coursework. In addition Emily is involved in two research projects. She is designing a protocol to collect HIV status information for women and infant that are currently enrolled in an individually randomized, double blind, placebo controlled trial in Tanzania that is designed to assess the efficacy of neonatal vitamin A supplementation given within the first three days of life in reducing mortality in the period from supplementation to 6 months of age. She is also working on an analysis of baseline ferritin status and HIV progression among participants in a randomized double blinded placebo controlled trial to assess the efficacy of multivitamin supplementation in HIV infected adults initiating antiretroviral therapy in Uganda in achieving immune reconstitution, weight gain, and improved quality of life.

Yared Gurmu is a second-year student in the Biostatistics doctoral program (dissertation advisor: Victor DeGruttola) whose main focus is completing his core coursework. He recently passed the departmental written qualifying exam. In addition, Yared has been reviewing the literature for methods of nonparametric survival analysis so that he can implement and extend currently existing methods for nonparametric estimation of a distribution. Yared's ultimate goal is to develop a methodology that permits accurate estimation of joint distribution of start time and duration of relationships and apply this methodology on HIV surveillance dataset. The methodology will also be extended to examine the impact of age, gender and treatment status on the distribution of start times and duration of relationships. In addition, the effect of relationship type (cohabitation, regular partner, casual partner,etc) on the distribution of the duration will be investigated.

Denis Agniel is a third-year student in the Biostatistics doctoral program (dissertation advisor: Tianxi Cai). He has completed his course work and is working on his dissertation. Denis has worked on multiple research projects in support of his dissertation over the past year. On one project he worked with Tianxi Cai to identify so-called "master regulators," or predictors (often genetic) that are associated with multiple related outcomes using a wide class of models including semi-parametric regression models. They used this to try to identify a common genetic basis for autoimmune disease (in one dataset) and for drug resistance to entire classes of drugs in HIV (in another dataset). On another project with Dr. Cai they're working to identify SNPs that affect CD4 count over time using functional principal components analysis. The functional PCA approach will allow us to detect more complex effects than would be possible in conventional longitudinal analyses. He presented findings from this research, "Assessing the global null in large-scale multiple testing for arbitrary correlation structures, "at the Correlated and High Dimensional Data Working Group in the Department of Biostatistics in May of 2012. Denis has also been selected as a finalist for the David P. Byar Young Investigator Award and will present, "Identifying master regulators in semi-parametric regression models," at the Joint Statistical Meeting that will be held in Quebec in August.

Caleb Miles is a third-year student in the Biostatistics doctoral program (dissertation advisor: Eric Tchetgen Tchetgen). He has completed his course work and is working on his dissertation. Caleb's current research focuses on development of identification and estimation of a causal contrast in the field of mediation analysis. This contrast is of particular interest in settings where there may be both confounders of the effect of the exposure on the outcome as well as confounders of the effect of the mediator on the outcome that are affected by the exposure. One such setting is where there is interest in how adherence to a drug regimen mediates the effect of prescription to an anti-retroviral therapy on the outcome, virologic suppression. In addition to confounding variables on the effect of the ART on virologic suppression, it is also important to account for potential toxicity due to exposure to the ART, which could affect both adherence and the outcome. The causal contrast Caleb is studying captures specifically the effect of the exposure on the outcome exclusively through the mediator and not through the post-exposure confounders. He is developing identification assumptions for this contrast, and using a semiparametric approach to produce an estimator that is both efficient and multiply robust. He presented findings from this research, "Background & Recent Developments in Causal Mediation Analysis," at the Joint Statistical Meeting that was held in San Diego, CA in July of 2012.

Elizabeth Smoot is a third-year student in the Biostatistics doctoral program (dissertation advisor: Sebastien Haneuse). She has completed her course work and is working on her dissertation. Beth is working on building on the hybrid design for combining ecological and case-control proposed by Haneuse and Wakefield. A main obstacle to the applicability of the hybrid design is its large computational burden. A potential solution to this is to use an alternative decomposition of the likelihood (into case-control and ecological sans case control) and then exploit the independence of case-control and ecological-sans-case control datasets by approximating the ecological portion of the likelihood, and a second potential solution is to use calibration methods in conjunction with influence functions.

Chris Sudfeld is a fourth-year student enrolled in the Epidemiology doctoral program (dissertation advisor: Wafaie Fawzi). He has completed his coursework and is involved in multiple research projects. Chris has worked on numerous projects examining the contributions of nutrition to clinical management of HIV. He has completed studies of vitamin D, serum albumin, and weight change on HIV progression among adults for my dissertation. Chris is currently completing the final study for his dissertation on the effect of micronutrient supplementation on measles vaccine response among HIV-infected and HIV-exposed uninfected Tanzanian infants. He presented findings from this research, "Vitamin D and HIV disease progression among adults initiating antiretroviral therapy in Tanzania," at the AIDS 2012 meeting that was held in Washington, DC in July of 2012. Chris also plans to present his poster, "Weight Change at One Month of Antiretroviral Therapy is Associated with Subsequent Mortality and Morbidity among a Tanzanian HIV-infected Adult Cohort, " at the CROI 2013 that will be held in Atlanta, GA in March.

Natalie Exner is a fourth-year student in the Biostatistics doctoral program (dissertation advisor: Marcello Pagano). She has completed her course work and is working on her dissertation. Natalie is currently working on two projects related to her thesis work. The first project relates to HIV incidence estimation using cross-sectional viral genetic diversity. The goal is to construct an algorithm for incidence estimation using a measure of within-host genetic variability. This algorithm is designed to adjust for the presence of multiple infections. They will evaluate this algorithm using a Subtype C incidence cohort from Botswana. The second project with the World Health Organization is designing a draft guidance for HIV drug resistance surveillance in low- and middle-income countries. In the guidance, they design surveys to address four major outcomes related to HIV drug resistance. The goal is to create a general survey design that will work well for a variety of countries. Natalie's responsibilities include estimating design effect due to clustering and disproportionate weighting, calculating sample size requirements, designing a sampling frame, limiting bias, and providing alternative designs to improve statistical efficiency in countries with more clinic- and patient-level information. She will travel to present the design at regional workshops in Asia and maybe South America and Africa.

Rebecca Payne is a fourth-year student in the Biostatistics doctoral program (dissertation advisor: Tianxi Cai). Her research focuses on developing methods for the analysis of cohort studies with two-phase sampling designs. These methods have a broad range of applicability but are particularly useful for testing biomarker and genetic effects because they can take advantage of the natural grouping in such markers. We are also interested in using similar methods to allow for data sampled from a cohort with respect to one outcome to be used in future studies examining other outcomes. Such procedures provide a valid way to combine data across studies with different outcome-dependent sampling schemes, an increasingly important topic as researchers in many fields are being encouraged to share data.

Brian Sharkey is a fifth-year student in the Biostatistics doctoral program (dissertation advisors: Judith Lok / Michael Hughes). He has completed his course work and is working on his dissertation. Brian's research interests are in competing risks. This work is motivated by a desire to better understand the relative balance of safety outcomes (treatment limiting adverse events) and efficacy outcomes (virologic failure, or lack thereof) for specific HIV treatments in a study, and how this balance evolves with time on treatment and compares among treatments. This is a key issue in HIV research given the plethora of treatments with similar effects in suppressing HIV-1 RNA and the desire to better understand adverse effects of specific regimens. They have developed new methods to this end and are currently developing methods for how to properly power and design a study to answer these specific questions.

Miguel Marino was a postdoctoral research fellow. He terminated early to start an assistant professor position in the Department of Family Medicine at Oregon Health Science University. During his appointment Miguel began working on risk prediction methods and missing data methods dealing with survey nonresponse from Demographic and Health surveys in Sub-Saharan Africa to estimate national HIV prevalence. While researching, he also received training on his teaching skills by teaching the ID538: Foundation in Public Health course at HSPH. During this short period, Miguel won an ENAR Fostering Diversity in Biostatistics Workshop Travel Award (Washington DC). He also was awarded a HSPH Robert Wood Johnson Foundation Seed Grant to do work in risk prediction.