Abstract

Decision making and intervention against infectious diseases require analysis of large volumes of data, including demographic data, contact networks, age- specific contact rates, mobility networks, and healthcare and control intervention data and models. In this paper, we present our Networks-Of-Traces for Epidemic Spread Simulations (N0TES2) model and system which aim at assisting experts and helping them explore existing simulation trace data sets. N0TES2 supports analysis and indexing of simulation data sets as well as parameter and feature analysis, including identification of unknown dependencies across the input parameters and output variables spanning the different layers of the observation and simulation data.

Original languageEnglish (US)
Title of host publicationAAAI Workshop - Technical Report
PublisherAI Access Foundation
Pages79-83
Number of pages5
VolumeWS-15-06
ISBN (Print)9781577357179
StatePublished - 2015
Event29th AAAI Conference on Artificial Intelligence, AAAI 2015 - Austin, United States
Duration: Jan 25 2015Jan 30 2015

Other

Other29th AAAI Conference on Artificial Intelligence, AAAI 2015
CountryUnited States
CityAustin
Period1/25/151/30/15

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Liu, S., Garg, Y., Candan, K., Sapino, M. L., & Chowell-Puente, G. (2015). NOTES2: Networks-of-traces for epidemic spread simulations. In AAAI Workshop - Technical Report (Vol. WS-15-06, pp. 79-83). AI Access Foundation.