GeoSpread: An Epidemic Spread Modeling Tool for COVID-19 Using Mobility Data
2nd ACM Conference on Information Technology for Social Good, GoodIT 2022
; : 125-131, 2022.
Article
in English
| Scopus | ID: covidwho-2053346
ABSTRACT
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. © 2022 Owner/Author.
COVID-19; Data Analysis; Disease Spread Modeling; Individual-Centric Models; Simulation Models; Autonomous agents; Computational methods; Disease control; Population statistics; Viruses; Agent-based model; Disease spread; Epidemic spread; Flexible tool; Individual-centric model; Mobility datum; Modelling tools; Simulation model; Spread of virus
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2nd ACM Conference on Information Technology for Social Good, GoodIT 2022
Year:
2022
Document Type:
Article
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