About: Prediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamics

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Prediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamics
Creator	Huang, Ganyu
Source	Medline; PMC; WHO
abstract	On 12 December 2019, a novel coronavirus disease, named COVID-19, began to spread around the world from Wuhan, China. It is useful and urgent to consider the future trend of this outbreak. We establish the 4+1 penta-group model to predict the development of the COVID-19 outbreak. In this model, we use the collected data to calibrate the parameters, and let the recovery rate and mortality change according to the actual situation. Furthermore, we propose the BAT model, which is composed of three parts: simulation of the return rush (Back), analytic hierarchy process (AHP) method, and technique for order preference by similarity to an ideal solution (TOPSIS) method, to figure out the best return date for university students. We also discuss the impacts of some factors that may occur in the future, such as secondary infection, emergence of effective drugs, and population flow from Korea to China.
has issue date	2020-04-07(xsd:dateTime)
bibo:doi	10.1007/s12204-020-2167-2
bibo:pmid	32288415
has license	no-cc
sha1sum (hex)	40ae26f6095a1e1bf5e3e4d5652403c2234d2051
schema:url	https://doi.org/10.1007/s12204-020-2167-2
resource representing a document's title	Prediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamics
has PubMed Central identifier	PMC7137853
has PubMed identifier	32288415
schema:publication	J Shanghai Jiaotong Univ Sci
resource representing a document's body	covid:40ae26f6095a1e1bf5e3e4d5652403c2234d2051#body_text
is schema:about of	named entity 'OUTBREAK' named entity 'PROPAGATION' named entity 'CORONAVIRUS DISEASE' named entity 'OPTIMAL' named entity 'DATE' named entity 'CODE' named entity 'ORDER' named entity 'DECEMBER' named entity 'CHANGE' named entity 'LET' named entity 'CONSIDER' named entity 'HIERARCHY' named entity 'KEY' named entity '2B1' named entity 'PREDICT' covid:arg/40ae26f6095a1e1bf5e3e4d5652403c2234d2051 named entity 'NOVEL CORONAVIRUS' named entity 'WORDS' named entity 'ACCORDING' named entity 'KOREA' named entity 'ESTABLISH' named entity 'USEFUL' named entity 'SIMILARITY' named entity 'COMPOSED OF' named entity 'PENTA' named entity 'EFFECTIVE' named entity 'MODEL' named entity 'SOLUTION' named entity 'ACTUAL' named entity 'OCCUR' named entity 'PREFERENCE' named entity 'RUSH' named entity 'PARTS' named entity 'BEST' named entity 'DYNAMICS' named entity 'COVID-19' named entity 'RETURN' named entity 'COLLECTED' named entity 'SITUATION' named entity 'CHINA' named entity 'BASED' named entity 'PREDICTION' named entity 'STUDENTS' named entity 'RECOVERY' named entity '2019' named entity 'DRUGS' named entity 'PROCESS' named entity 'IMPACTS' named entity 'FIGURE' named entity 'NAMED' named entity 'DATE' named entity 'UNIVERSITY' named entity 'RATE' named entity 'BAT' named entity 'DOCUMENT ' named entity 'POPULATION' named entity 'TREND' named entity 'URGENT' named entity 'EMERGENCE' named entity 'NONLINEAR' named entity 'EPIDEMIC' named entity 'PARAMETERS' named entity 'RETURN' named entity 'DYNAMICS MODEL' named entity 'COVID-19' named entity 'GROUP' named entity 'LEAST SQUARES' named entity 'STUDENTS' named entity 'NUMBER' named entity 'DISCUSS' named entity 'SIMULATION' named entity 'MORTALITY' named entity 'CHINA' named entity 'FLOW' named entity 'SECONDARY INFECTION' named entity 'UNIVERSITY' named entity 'WUHAN' named entity 'METHOD' named entity 'FUTURE' named entity 'WORLD' named entity 'SPREAD'

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