Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support.
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| Title: | Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support. |
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| Authors: | Bhattacharya P; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Chen J; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Hoops S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Machi D; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Lewis B; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Venkatramanan S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Wilson ML; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Klahn B; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Adiga A; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Hurt B; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Outten J; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Adiga A; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Warren A; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Baek YY; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Porebski P; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Marathe A; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.; Dept. of Public Health Sciences, University of Virginia, Charlottesville, VA, USA., Xie D; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Swarup S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA., Vullikanti A; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.; Dept. of Computer Science, University of Virginia, Charlottesville, VA, USA., Mortveit H; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.; Dept. of Eng. Systems and Environment, University of Virginia, Charlottesville, VA, USA., Eubank S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.; Dept. of Public Health Sciences, University of Virginia, Charlottesville, VA, USA., Barrett CL; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.; Dept. of Computer Science, University of Virginia, Charlottesville, VA, USA., Marathe M; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.; Dept. of Computer Science, University of Virginia, Charlottesville, VA, USA. |
| Source: | The international journal of high performance computing applications [Int J High Perform Comput Appl] 2023 Jan; Vol. 37 (1), pp. 4-27. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Sage Science Press Country of Publication: United States NLM ID: 100911700 Publication Model: Print Cited Medium: Print ISSN: 1094-3420 (Print) Linking ISSN: 10943420 NLM ISO Abbreviation: Int J High Perform Comput Appl Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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