The Software and Computation Component for the University of Pittsburgh MIDAS National Center of Excellence will be a cross-cutting component providing development and support relevant to all research projects of the center. Housed at the Pittsburgh Supercomputing Center and led by Dr. Shawn Brown, the component will advance the use of modling and simulation in public health decision making by enhancing the time to solution for aget-based simulations, providing meaningful platforms for visualization of public health data, and promotion of productization of open-source scientific tools developed by the center. The Component will have impact in all aspects of the proposed center, and beyond into the MIDAS Network, providing leadership in software development, high-performance computing, and scientific visualization. The component has the following specific aims: 1. Provide the programmatic framework AgentHPC that will be a flexible, robust definition of agent-based models through a standard API that takes advantage of high-performance computing and modern, accelerator technology to provide performance sufficient for real-time decision support. AgentHPC will be flexible for implementing a wide array of models and reduce the time to solution for modeling work. 2.Provide interactive geospatial visualization and analysis service-oriented platform for public health and simulation data. Leveraging our previous work on the GAIA platform, a public health data repository will be established for sharing data and creating interactive visualizations. 3.Establish a collaborative web-based open-source development platforms and a user requirements gathering forum for software tools developed by the Center of Excellence. Open-source platforms, such as Google Code, and a user requirements forum provide the community a means for interacting with our developers.

Public Health Relevance

Recognizing that computational modeling is a vital component of public health decision making, the Computaitonal Core will enhance it use through reduction in time to solution for simulations, visualizing data, and creating accessible, ready-to-use tools relevant to a public health audience through moving tools to open source distribution platforms and facilitating user requirements..

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZGM1-BBCB-5 (MI))
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University of Pittsburgh
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Brooks, Logan C; Farrow, David C; Hyun, Sangwon et al. (2018) Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions. PLoS Comput Biol 14:e1006134
Biggerstaff, Matthew; Johansson, Michael; Alper, David et al. (2018) Results from the second year of a collaborative effort to forecast influenza seasons in the United States. Epidemics 24:26-33
EspaƱa, Guido; Grefenstette, John; Perkins, Alex et al. (2018) Exploring scenarios of chikungunya mitigation with a data-driven agent-based model of the 2014-2016 outbreak in Colombia. Sci Rep 8:12201
Paternina-Caicedo, Angel; Driessen, Julia; Roberts, Mark et al. (2018) Heterogeneity Between States in the Health and Economic Impact of Measles Immunization in the United States. Open Forum Infect Dis 5:ofy137
Althouse, Benjamin M; Guerbois, Mathilde; Cummings, Derek A T et al. (2018) Role of monkeys in the sylvatic cycle of chikungunya virus in Senegal. Nat Commun 9:1046
Buchanich, Jeanine M; Doerfler, Shannon M; Lann, Michael F et al. (2018) Improvement in racial disparities in years of life lost in the USA since 1990. PLoS One 13:e0194308
Lauer, Stephen A; Sakrejda, Krzysztof; Ray, Evan L et al. (2018) Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010-2014. Proc Natl Acad Sci U S A 115:E2175-E2182
Brownwright, Tenley K; Dodson, Zan M; van Panhuis, Willem G (2017) Spatial clustering of measles vaccination coverage among children in sub-Saharan Africa. BMC Public Health 17:957
Kirsch, Thomas D; Moseson, Heidi; Massaquoi, Moses et al. (2017) Impact of interventions and the incidence of ebola virus disease in Liberia-implications for future epidemics. Health Policy Plan 32:205-214
Grubaugh, Nathan D; Ladner, Jason T; Kraemer, Moritz U G et al. (2017) Genomic epidemiology reveals multiple introductions of Zika virus into the United States. Nature 546:401-405

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