{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/45637"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/45637","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A computational approach to understanding spatial and temporal granularities in agent-based modeling","abstract":"Epidemic agent-based models simulate individuals in artificial societies capable of moving, interacting, and transmitting disease amongst themselves. Due to limitations in data and computation, epidemic models simulating tens of millions of individuals often coarsen the finest representations of space and time–termed spatial and temporal granularities in this thesis. This dissertation examines and overcomes a set of computational challenges to investigate a fundamental problem in spatially explicit epidemic agent-based modeling. This research demonstrates that coarsening spatial and temporal granularities influence both computational tractability and epidemic ABM processes. By focusing on the nexus of space, time, and process my dissertation improves understanding of the interrelationships and trade-offs between space and time as they relate to spatial processes using an epidemic modeling case study.","abstract_html":"Epidemic agent-based models simulate individuals in artificial societies capable of moving, interacting, and transmitting disease amongst themselves. Due to limitations in data and computation, epidemic models simulating tens of millions of individuals often coarsen the finest representations of space and time–termed spatial and temporal granularities in this thesis. This dissertation examines and overcomes a set of computational challenges to investigate a fundamental problem in spatially explicit epidemic agent-based modeling. This research demonstrates that coarsening spatial and temporal granularities influence both computational tractability and epidemic ABM processes. By focusing on the nexus of space, time, and process my dissertation improves understanding of the interrelationships and trade-offs between space and time as they relate to spatial processes using an epidemic modeling case study.","abstract_has_math":false,"creators":["Shook, Eric"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Geography","degree_department":null,"school":null,"contributors":["Wang, Shaowen","Hannon, Bruce M.","Kale, Laxmikant V.","McLafferty, Sara L."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-08-22T16:56:15Z","date_published":"2013-08-22T16:56:15Z","updated_at":"2026-07-22T22:25:36Z","subjects":["agent-based model (abm)","spatial and temporal granularities","parallel abm"],"languages":["en"],"rights":["Copyright 2013 by Eric A. Shook. Chapter 2 is published in the International Journal of Geographic Information Science. 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