About: Determination of COVID-19 parameters for an agent-based model: Easing or tightening control strategies

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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	Determination of COVID-19 parameters for an agent-based model: Easing or tightening control strategies
Creator	Macintyre, Raina Miller, Eric Najmi, Ali Rashidi, Taha Safarighouzhdi, Farshid
Source	MedRxiv
abstract	Different agent-based models have been developed to estimate the spread progression of coronavirus disease 2019 (COVID-19) and to evaluate different control strategies to control outbreak of the infectious disease. While there are several estimation methods for the disease-specific parameters of COVID-19, they have been used for aggregate level models such as SIR and not for agent-based models. We propose a mathematical structure to determine parameter values of agent-based models considering the mutual effects of parameters. Then, we assess the extent to which different control strategies can intervene the transmission of COVID-19. Accordingly, we consider scenarios of easing social distancing restrictions, opening businesses, speed of enforcing control strategies and quarantining family members of isolated cases on the disease progression. We find the social distancing compliance level in the Sydney greater metropolitan area to be around 85%. Then we elaborate on consequences of easing the compliance level in the disease suppression. We also show that tight social distancing levels should be considered when the restrictions on businesses and activity participations are easing.
has issue date	2020-06-23(xsd:dateTime)
bibo:doi	10.1101/2020.06.20.20135186
has license	medrxiv
sha1sum (hex)	6e4f8cf1bc1b6cd9153f2d03ce6584c6c597746f
schema:url	https://doi.org/10.1101/2020.06.20.20135186
resource representing a document's title	Determination of COVID-19 parameters for an agent-based model: Easing or tightening control strategies
resource representing a document's body	covid:6e4f8cf1bc1b6cd9153f2d03ce6584c6c597746f#body_text
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