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

> **NIH NIH P01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $55,855

## Abstract

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 an...

## Key facts

- **NIH application ID:** 10841700
- **Project number:** 5P01HD112215-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Maganizo Chagomerana
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $55,855
- **Award type:** 5
- **Project period:** 2023-05-15 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10841700

## Citation

> US National Institutes of Health, RePORTER application 10841700, Data Science and Analytical Core [Parent Title: PREVENTING INFANT INFECTIONS WITH IMPLEMENTATION SCIENCE IN MALAWI] (5P01HD112215-02). Retrieved via AI Analytics 2026-07-02 from https://api.ai-analytics.org/grant/nih/10841700. Licensed CC0.

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