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Guang-Hui She

Dados Biográficos

ID7866804
NOMEGuang-Hui She
PRENOMESGuang-Hui
SOBRENOMEShe
ASSINATURASHE G
AFILIAÇÕESPeking University
VERIFICADONão
TOTAL DE OBRAS1
TOTAL DE CITAÇÕES0
OBRAS COMO AUTOR1
OBRAS COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2022
ANO MAIS RECENTE DE PUBLICAÇÃO2022
ÍNDICE H0
  • Quantifying Social Interventions for Combating Covid-19 via a Symmetry-Based Model

    Open Access•Lei Zhang, Guang-Hui She et al.•ARTICLE•International Journal of…•2022

    The COVID-19 pandemic has revealed new features in terms of substantial changes in rates of infection, cure, and death as a result of social interventions, which significantly challenges traditional SEIR-type models. In this paper we developed a symmetry-based model for quantifying social interventions for combating COVID-19. We found that three key order parameters, separating degree (S) for susceptible populations, healing degree (H) for mild c…

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  • Quantifying Social Interventions for Combating Covid-19 via a Symmetry-Based Model

    Open Access•Lei Zhang, Guang-Hui She et al.•ARTICLE•International Journal of…•2022

    The COVID-19 pandemic has revealed new features in terms of substantial changes in rates of infection, cure, and death as a result of social interventions, which significantly challenges traditional SEIR-type models. In this paper we developed a symmetry-based model for quantifying social interventions for combating COVID-19. We found that three key order parameters, separating degree (S) for susceptible populations, healing degree (H) for mild c…

Beijing (1 obra) · China (1 obra) · Computer Science (1 obra) · Coronavirus disease 2019 (COVID-19 (1 obra) · COVID-19 and Mental Health (1 obra) · COVID-19 epidemiological studies (1 obra) · Degree (music (1 obra) · Econometrics (1 obra) · Economics (1 obra) · Environmental health (1 obra)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae