About: A Network-Based Stochastic Epidemic Simulator: Controlling COVID-19 with Region-Specific Policies

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A Network-Based Stochastic Epidemic Simulator: Controlling COVID-19 with Region-Specific Policies
Creator	Lewis, Michael Baimukashev, Daulet Ibragimov, Bauyrzhan Karabay, Aknur Kuzdeuov, Askat Mirzakhmetov, Almas Nurpeiissov, Mukhamet Varol, Huseyin
Source	MedRxiv
abstract	In this work, we present an open-source stochastic epidemic simulator, calibrated with extant epidemic experience of COVID-19. Our simulator incorporates information ranging from population demographics and mobility data to health care resource capacity, by region, with interactive controls of system variables to allow dynamic and interactive modeling of events. The simulator can be generalized to model the propagation of any disease, in any territory, but for this experiment was customized to model the spread of COVID-19 in the Republic of Kazakhstan, and estimate outcomes of policy options to inform deliberations on governmental interdiction policies.
has issue date	2020-05-06(xsd:dateTime)
bibo:doi	10.1101/2020.05.02.20089136
has license	medrxiv
sha1sum (hex)	b36a5cc7c9d2c4d2cf78b1ed914be945c9bf5885
schema:url	https://doi.org/10.1101/2020.05.02.20089136
resource representing a document's title	A Network-Based Stochastic Epidemic Simulator: Controlling COVID-19 with Region-Specific Policies
resource representing a document's body	covid:b36a5cc7c9d2c4d2cf78b1ed914be945c9bf5885#body_text
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