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dc.contributor.authorHuang, Ganyu, et al.
dc.date.accessioned2020-04-29T00:41:44Z
dc.date.available2020-04-29T00:41:44Z
dc.date.issued2020-04-07
dc.identifier.urihttps://doi.org/10.1007/s12204-020-2167-2en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12663/1232
dc.description.abstractOn 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.en_US
dc.languageEnglishen_US
dc.subjectCOVID-19en_US
dc.subjectCoronavirusen_US
dc.subjectInfectious Diseasesen_US
dc.subjectChinaen_US
dc.subjectPrognosisen_US
dc.titlePrediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamicsen_US
eihealth.countryOthersen_US
eihealth.categoryHealth systems and servicesen_US
eihealth.categoryPublic Health Interventionsen_US
eihealth.typePublished Articleen_US
eihealth.maincategorySlow Spread / Reducir la Dispersiónen_US
dc.relation.ispartofjournalJournal of Shanghai Jiaotong University (Science)en_US


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