RTI International proposes an Information Technology Resource (ITR) for the Modeling of Infectious Disease Agent Study (MIDAS) that builds on the extensive development effort that was led by RTI in the pilot MIDAS Network. The activities for the ITR will be driven by the needs of the modelers in the Research Groups and Centers of Excellence. We propose to use the CMMI approach to managing software development and a process that includes users to harden and test software developed by the modelers, develop computational tools for MIDAS researchers and other audiences, extend the Model Repository capabilities initiated in the pilot phase, integrate existing ontologies and develop new MIDAS-specific vocabulary as required, and provide computational surge capacity required to respond to policymaker urgent requests and high- performance computing assistance to the research groups. For data development, we propose to manage both structured and unstructured data and make available to non-MIDAS users all unrestricted data, a number of innovations and enhancements to the synthesized human and animal databases that were both initiated during the pilot phase, and develop data standards for interoperability between models. A number of dissemination and outreach approaches are proposed, including the implementation of a method to evaluate the information needs of target audiences to increase awareness of MIDAS among additional research and educational communities. We propose to not only address the activities that have been outlined for theITR, but also propose innovative enhancements, including new visualization tools, web process servers to provide customized databases, and geospatial host-vector probability surfaces. The goal of the ITR will be to use our knowledge in computer science, geospatial and non-geospatial data, computational modeling, and health communication, and project-support capabilities to respond to and anticipate needs of MIDAS researchers and, in general, drive and support the growth and maturation of infectious disease modeling. MIDAS will help prepare the nation to respond to outbreaks of infectious disease by providing policymakers and public health officials with reliable and timely information that can be used either in planning for an event or in responding to repercussions from an event.

Public Health Relevance

MIDAS will help prepare the nation to respond to outbreaks of infectious disease by providing policymakers and public health officials with reliable and timely information that can be used in planning. The goal of the ITR will be to use knowledge in computer science, geospatial and non-geospatial data, computer modeling, and health communication, and project-support capabilities to respond to and anticipate needs of MIDAS researchers and, in general, drive and support the growth and maturation of infectious disease modeling.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
5U24GM087704-04
Application #
8270002
Study Section
Special Emphasis Panel (ZGM1-CBCB-5 (MI))
Program Officer
Sheeley, Douglas
Project Start
2009-06-01
Project End
2014-05-31
Budget Start
2012-06-01
Budget End
2013-05-31
Support Year
4
Fiscal Year
2012
Total Cost
$1,986,141
Indirect Cost
$795,882
Name
Research Triangle Institute
Department
Type
DUNS #
004868105
City
Research Triangle
State
NC
Country
United States
Zip Code
27709
Bruhn, Mark C; Munoz, Breda; Cajka, James et al. (2012) Synthesized Population Databases: A Geospatial Database of US Poultry Farms. Methods Rep RTI Press MR-0023-1201:1-24
Bryant, Stephanie P; Solano, Eric; Cantor, Susanna et al. (2011) Sharing Research Models: Using Software Engineering Practices for Facilitation. Methods Rep RTI Press 2011:1-16
Cooley, Philip; Lee, Bruce Y; Brown, Shawn et al. (2010) Protecting health care workers: a pandemic simulation based on Allegheny County. Influenza Other Respir Viruses 4:61-72
Zimmerman, Richard K; Lauderdale, Diane S; Tan, Sylvia M et al. (2010) Prevalence of high-risk indications for influenza vaccine varies by age, race, and income. Vaccine 28:6470-7
Lee, Bruce Y; Brown, Shawn T; Cooley, Philip et al. (2010) Simulating school closure strategies to mitigate an influenza epidemic. J Public Health Manag Pract 16:252-61
Cajka, James C; Cooley, Philip C; Wheaton, William D (2010) Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling. Methods Rep RTI Press 19:1-14