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Title: GeoSpread: an Epidemic Spread Modeling Tool for COVID-19 Using Mobility Data
We present an individual-centric agent-based model and a flexible tool, GeoSpread, for studying and predicting the spread of viruses and diseases in urban settings. Using COVID-19 data collected by the Korean Center for Disease Control & Prevention (KCDC), we analyze patient and route data of infected people from January 20, 2020, to May 31, 2020, and discover how infection clusters develop as a function of time. This analysis offers a statistical characterization of population mobility and is used to parameterize GeoSpread to capture the spread of the disease. We validate simulation predictions from GeoSpread with ground truth and we evaluate different what-if counter-measure scenarios to illustrate the usefulness and flexibility of the tool for epidemic modeling.  more » « less
Award ID(s):
1838022 2130681
NSF-PAR ID:
10387948
Author(s) / Creator(s):
; ; ;
Editor(s):
Mourlas, cotas; Pacheco, Diego; Pandi, Catia
Date Published:
Journal Name:
GoodIT 2022: {ACM} International Conference on Information Technology for Social Good, Limassol, Cyprus, September 7 - 9, 2022
Page Range / eLocation ID:
125 to 131
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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