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

数据科学和分析核心-摘要 实现消除母婴传播（EMTCT）将取决于以下方面的成功合作： 来自不同领域的科学家和实践者。这些领域中最重要的是分析学科， 特别是流行病学、生物统计学和实施科学。这些学科致力于应用 适当的概念框架和分析方法，以确保准确的计量和有效的 健康研究中的推论。数据科学和分析核心的目标是确保协同作用 通过与研究人员合作和发展能力， 制作和管理高质量的数据，用于评估围产期艾滋病毒传播、抗逆转录病毒疗法的使用和坚持， 和PrEP的吸收和遵守，通过以下具体目标： 目标1。开发数据管理系统，支持三个部门的数据管理活动 项目研究项目。马拉维联合国项目（UNC-PM）有一个既定的数据部门 负责管理NIH资助的大型临床试验网络、观察性队列的数据， 实施研究和登记册。数据部门一贯取得杰出的 评估所有数据指标，同时满足外部监测标准。项目已成功 从卫生部电子数据库和纸质登记簿中提取常规数据，并将其与 在实施一些研究时使用研究数据。数据科学和分析核心将利用这些数据 通过设计数据收集工具，创建和管理数据库， 从卫生部的数据库中提取常规数据，并建立数据质量保证和控制系统。目标二。 支持研究项目从设计到传播的分析方面。的研究项目 在本申请中提出的主题集中在EMTCT，但需要广泛的分析 评估来自不同来源的数据的能力。所有项目都需要跨领域的分析能力 数据科学和分析核心和UNC-PM附属教师将直接支持这些分析需求， 实现总体目标。目标3：估计拟议干预措施对儿科和 如果在全国范围内推广，孕产妇的结果和加速消除母婴传播。拟议项目包括 在马拉维实施新的战略，加速消除母婴传播。我们将建立数学模型， 量化和比较这些干预措施在避免孕产妇和儿童艾滋病毒感染方面的效果， 改善病毒载量抑制，并在国家一级增加母婴护理的保留率。 目标4。为刚接触数据的嵌入式初级调查员创建能力建设环境 通过教学培训和体验式学习，管理和统计分析。芯会 通过提供一对一的咨询和教学培训，主持和支持项目指导活动 在数据管理，研究方法和分析指导临床调查人员和研究人员。

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.