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SQEIR: An epidemic virus spread analysis and prediction model.
Wu, Yichun; Sun, Yaqi; Lin, Mugang.
  • Wu Y; College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China.
  • Sun Y; College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China.
  • Lin M; Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China.
Comput Electr Eng ; 102: 108230, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2287100
ABSTRACT
In 2019, a new strain of coronavirus pneumonia spread quickly worldwide. Viral propagation may be simulated using the Susceptible Infectious Removed (SIR) model. However, the SIR model fails to consider that separation of patients in the COVID-19 incubation stage entails difficulty and that these patients have high transmission potential. The model also ignores the positive effect of quarantine measures on the spread of the epidemic. To address the two flaws in the SIR model, this study proposes a new infectious disease model referred to as the Susceptible Quarantined Exposed Infective Removed (SQEIR) model. The proposed model uses the weighted least squares for the optimal estimation of important parameters in the infectious disease model. Based on these parameters, new differential equations were developed to describe the spread of the epidemic. The experimental results show that this model exhibits an accuracy 6.7% higher than that of traditional infectious disease models.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Comput Electr Eng Year: 2022 Document Type: Article Affiliation country: J.compeleceng.2022.108230

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Comput Electr Eng Year: 2022 Document Type: Article Affiliation country: J.compeleceng.2022.108230