The Administrative Core consists of two major functional units - the Executive Unit and the Data Management, Statistics, and Information Technology (DMS/IT) Unit.
The Aims of the Executive Unit are to 1) provide overall scientific and programmatic leadership and direction, 2) oversee and coordinate the activities of Projects 1 and 2, 3) ensure reliable exchange of information and collaboration among all the units and investigators, 4) coordinate and oversee management of the Program Project's fiscal resources, and 5) promote and ensure the Program Project's adherence to relevant federal, University, and IRB requirements.
The Aims of the Data Management, Statistics, and Information Technology (DMS/IT) Unit are to 6) provide a state-of-the-art data management system and methods capable of supporting the interactive projects of multiple participating investigators, 7) provide a set of online resources and communications technologies that facilitate scholarly exchange, distance-independent collaboration, information dissemination and project-specific training, and 8) provide statistical expertise in design, modeling, data analysis, statistical writing, and the development of novel methodologies as related to the execution of Projects 1 and 2. Related to the specific aims of Project 1 and 2, the Clinical and Specimen Core will recruit a substantial number of study participants, each of whom will contribute clinical specimens for laboratory evaluation. Project 1 will generate epidemiological and behavioral data on the participants, while Project 2 will generate laboratory data using the clinical specimens. The Administrative Core will play a central role in coordinating the administrative, fiscal and personnel support required to achieve the scientific mission of these components and fostering the synergistic interaction among them. The Administrative Core will also be critical in managing the extensive amount of data from these projects and conducting the sophisticated analyses necessary to provide robust and valid conclusions.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Program Projects (P01)
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Application #
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Special Emphasis Panel (ZAI1-MH-A)
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University of California San Diego
La Jolla
United States
Zip Code
Hoenigl, Martin; Green, Nella; Camacho, Martha et al. (2016) Signs or Symptoms of Acute HIV Infection in a Cohort Undergoing Community-Based Screening. Emerg Infect Dis 22:532-4
Gianella, Sara; Letendre, Scott (2016) Cytomegalovirus and HIV: A Dangerous Pas de Deux. J Infect Dis 214 Suppl 2:S67-74
Hoenigl, Martin; Little, Susan J (2016) How can we detect HIV during the acute or primary stage of infection? Expert Rev Mol Diagn 16:1049-1051
Hoenigl, Martin; Graff-Zivin, Joshua; Little, Susan J (2016) Costs per Diagnosis of Acute HIV Infection in Community-based Screening Strategies: A Comparative Analysis of Four Screening Algorithms. Clin Infect Dis 62:501-11
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Kassanjee, Reshma; Pilcher, Christopher D; Busch, Michael P et al. (2016) Viral load criteria and threshold optimization to improve HIV incidence assay characteristics. AIDS 30:2361-71
Yang, S; Lok, J J (2016) A goodness-of-fit test for structural nested mean models. Biometrika 103:734-741

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