CORE C ABSTRACT - Data Management and Analysis Research Core The purpose of this core is to manage and support the resources to address fundamental questions about the role of respiratory syncytial virus (RSV) on childhood respiratory morbidity and asthma. This data management and analysis core will serve to manage the data from the two human study populations for Project 1 and 2: Infant Susceptibility to Pulmonary Infections and Asthma Following RSV Exposure (INSPIRE) and Childhood Allergy and the Neonatal Environment (CANOE), the experimental data, and the proposed animal studies in Project 2. It will also serve to oversee the analyses for this proposal. The combination of data management and analysis centered within one core allows for the oversight of the complex human, biosample and experimental data to be used in this proposal, and the integrated collaboration of the biostatistical team in the proposed analyses, and thus builds synergy for the projects 1 and 2 that this core serves. The research team has a successful track record of working with the types of complex data generated in these projects and conducting the proposed biostatistical analyses. This core assembles a complementary research team of biostatisticians, geneticists, systems biologists, bioinformatics and database management staff along with the data management and state of the art analytical skills necessary to successfully conduct the proposed studies. The two major functions of this core, data management and data analysis are outlined in two separate aims or functions of this core: 1) Management and integration of clinical, physiological, immunologic, microbiome, airway epithelial cell, genetic and epigenetic data from collaborating sites with a central infrastructure that facilitates the proposed research. This includes ensuring subject-level data quality control of primary clinical data collection, the pre-analytical variables and biospecimen processing and performance of assays with validated standard protocols that minimize errors in reproducibility, and efficient organization of samples and data among all research centers. 2) Integration of analytic support for the conduct of the proposed rigorous biostatistical analyses that address research questions across projects 1 and 2. This includes ensuring integration of the biostatistical team with the scientific cores, creating derived and imputed variables, developing shared analytic datasets for specific projects to be disseminated to the biostatistical leads on each aim, and conducting and implementing the proposed rigorous statistical methodology. This is a natural extension of the work of our experienced biostatistical team who have been integrated into each of the projects, and who will oversee the proposed analyses.