The overall objectives of the Data Management and Biostatistics Core are to 1) integrate and manage data from disparate sites and of many types (clinical outcomes, laboratory data) allowing investigators to access and utilize securely stored data from sites located across the globe and 2) provide biostatistical expertise for project co-investigators and Pis in the execution of more complex analyses as well as advice in the conduct of less complex analyses, he goals of the Core will be met by the Core PI (Friedman), Core Biostatistician (Potts), and Core Data Manager (Twark). Dr Friedman will be charged with overseeing the data management and biostatistical needs of individual projects and investigators. One of the main goals of this Core is to provide data management expertise and service to all projects and investigators. Specifically, the data manager and Core PI, will design the web-based platform with data entry screens, accompanying case report forms, and ensure the security of this site and data. The Core will be responsible for educating data entry personnel at all sites and overseeing and troubleshooting data entry issues. The data manager will be responsible for cleaning and merging data from disparate sources including covariates from human field studies and basic scientific data generated in the laboratory. The data manager and Core Pl will take responsibility for providing merged files to investigators with approved access through this web-based platform. The second goal of the Core is to support data analytic activities for all three projects, with particular emphasis on the more complex data analytic needs of Projects 1 and 2. These activities will be led by the core Pl (Friedman) and executed by both the PI and biostatistician. In some cases, for example CART, repeated measures, and ROC analyses, the Core will execute the analyses in collaboration with the project Pl and co-investigators. For other analyses, the Core will provide consultation to Project Pis and coinvestigators in the execution of analyses relevant to their projects. This includes guidance in the correct approach as well as providing opportunities for more innovative approaches to the analyses.
This Data Management and Biostatistics Core will provide key support for individual research projects aiding them in management and analysis of data. This includes provision of a web-based server to allow data entry from multiple sites as well as access to finalized data bases for analyses. The Core will also execute more complex analyses to enrich the way these complex data are ultimately interpreted and shared.
|Park, Sangshin; Srikiatkhachorn, Anon; Kalayanarooj, Siripen et al. (2018) Use of structural equation models to predict dengue illness phenotype. PLoS Negl Trop Dis 12:e0006799|
|Salje, Henrik; Cummings, Derek A T; Rodriguez-Barraquer, Isabel et al. (2018) Reconstruction of antibody dynamics and infection histories to evaluate dengue risk. Nature 557:719-723|
|Kang, Jeon-Young; Aldstadt, Jared (2017) The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model. Int J Environ Res Public Health 14:|
|Srikiatkhachorn, Anon; Mathew, Anuja; Rothman, Alan L (2017) Immune-mediated cytokine storm and its role in severe dengue. Semin Immunopathol 39:563-574|
|Rattanamahaphoom, Jittraporn; Leaungwutiwong, Pornsawan; Limkittikul, Kriengsak et al. (2017) Activation of dengue virus-specific T cells modulates vascular endothelial growth factor receptor 2 expression. Asian Pac J Allergy Immunol 35:171-178|
|Kalayanarooj, Siripen; Rothman, Alan L; Srikiatkhachorn, Anon (2017) Case Management of Dengue: Lessons Learned. J Infect Dis 215:S79-S88|
|Moulton, Steven L; Mulligan, Jane; Srikiatkhachorn, Anon et al. (2016) State-of-the-art monitoring in treatment of dengue shock syndrome: a case series. J Med Case Rep 10:233|
|Srikiatkhachorn, Anon; Yoon, In-Kyu (2016) Immune correlates for dengue vaccine development. Expert Rev Vaccines 15:455-65|
|Rothman, Alan L; Ennis, Francis A (2016) Dengue Vaccine: The Need, the Challenges, and Progress. J Infect Dis 214:825-7|
|Townsley, E; O'Connor, G; Cosgrove, C et al. (2016) Interaction of a dengue virus NS1-derived peptide with the inhibitory receptor KIR3DL1 on natural killer cells. Clin Exp Immunol 183:419-30|
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