Data Science and Analytical Core [Parent Title: PREVENTING INFANT INFECTIONS WITH IMPLEMENTATION SCIENCE IN MALAWI]

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Data Science and Analytical Core – Summary Achieving elimination of mother to child transmission (EMTCT) will depend on successful collaboration of scientists and practitioners from diverse fields. Essential among these fields are analytical disciplines, especially epidemiology, biostatistics, and implementation science. These disciplines are dedicated to applying appropriate conceptual frameworks and analytical methods to ensure accurate measurement and valid inference in health research. The goal of the Data Science and Analytical Core is to ensure that synergies across the research projects are realized by collaborating with the investigators and developing capacity to produce and manage high quality data for evaluating perinatal HIV transmission, ART uptake and adherence, and PrEP uptake and adherence through the following specific aims: Aim 1. Develop data management systems and support data management activities for the three program research projects. The UNC Project Malawi (UNC-PM) has an established data department responsible for managing data for large NIH funded clinical trials networks, observational cohorts, Implementation research, and registries. The data department has consistently achieved outstanding evaluations of all data metrics, while meeting external monitoring criteria. UNC Project has successfully extracted routine data from MOH electronic databases and paper-based registers and linking the same to research data when implementing some of its studies.The Data Science and Analytical Core will utilize these skills to support the projects by designing data collection tools, creating and managing databases, extracting routine data from MOH databases, and setting up data quality assurance and control systems. Aim 2. Support analytical aspects of the research projects from design to dissemination. The research projects proposed in this application are thematically focused on EMTCT but require a broad range of analytical aptitudes to assess data from diverse sources. All projects require cross-cutting analytical competencies The Data Science and Analytical Core and UNC-PM affiliated faculty will directly support these analytical needs to achieve the overall aims. Aim 3. Estimate the effects of the proposed interventions on pediatric and maternal outcomes and accelerating EMTCT if expanded nationally. The proposed projects involve implementing novel strategies to accelerate EMTCT in Malawi. We will develop mathematical models to quantify and compare the effect of these interventions in averting both maternal and pediatric HIV infections, improving viral load suppression, and increasing retention in care for mother-infant pairs at the national level. Aim 4. Create a capacity building environment for embedded junior investigators new to data management and statistical analysis through didactic training and experiential learning. The Core will host and support the program mentoring activities by providing one-on-one consultancies and didactic training in data management, research methods, and analysis for mentored clinical investigators and researchers.