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Support for Safe Generations Plus Project(NYC-3)

June 1, Length: 2-3 months

Location: New York, NY

The Safe Generations Plus project is an implementation science study that aims to understand how to improve retention in care and treatment services for HIV-positive pregnant women and their babies in Swaziland. The study will evaluate outcomes of patients who are lost-to-follow-up (LTF) under a new approach for prevention of mother-to-child transmission (PMTCT) called Option B+, where all HIV-positive pregnant women initiate lifelong antiretroviral therapy (ART) regardless of their disease stage. The goal is to understand the outcomes of patients who are LTF from care, and the reasons for disengagement from care in the context of PMTCT in order to inform efforts to improve retention in care among patients under Option B+.

Scope of Work
The student will be expected to work with study investigators to identify a set of high-priority questions and then explore these questions through data analysis. The student will work with investigators to develop table shells to help operationalize the analytic approach; conduct data analyses to develop these study results; and collaborate with the investigators to provide oral and written updates on progress. The student will share all codes, tables and descriptive interpretations used for the analysis with the study investigators.

The student will work closely with the Principal Investigator on data analysis for the study, including but not limited to the following:

  • Summarize and compare reasons for patient disengagement from care at points throughout the PMTCT cascade
  • Compare self-reported patient outcomes with outcomes collected from clinic records
  • Use study data to quantify the impact of gaps in the Swaziland monitoring and evaluation system on routine measures of patient outcomes
  • Explore the impact of using a “fuzzy matching” approach to classify patient outcomes
  • Use data visualization approaches (i.e., heat maps) and tabulations, with accompanying descriptions, to summarize patient visit adherence and retention and interpret findings



  • Research experience and/or global health experience
  • Expertise in quantitative data cleaning and management, data analysis, and data visualization using SAS, STATA, or other software


  • Experience with study monitoring (data quality assurance, adherence to protocol, etc.)