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Prediction and evaluation of the SARS-CoV-2 epidemic using an improved SEIR model
2022 Global Conference on Robotics, Artificial Intelligence and Information Technology, GCRAIT 2022 ; : 160-168, 2022.
Article in English | Scopus | ID: covidwho-2097597
ABSTRACT
The present work propose an improved SEIR model that considers isolation and repeated nucleic acid detection factors. It was applied to the Kashgar Region, Xinjiang, China, to predict the changing trend of the number of confirmed cases and the number of susceptible individuals in Kashgar, and to evaluate and analyze local policy interventions. Model perform four predictive analyses of the epidemic situation in Kashgar. Comprehensive nucleic acid testing, isolation of asymptomatic patients, increasing isolation time and different proportions of the population isolated, control of population flow. Improved kinetic parameters were obtained using the Monte Carlo method. The theoretical estimation of the epidemic using the improved SEIR infectious disease dynamics model was in good agreement with the actuality of the epidemic in Kashgar. The analysis showed that in the areas with large area and dense population, repeat nucleic acid detection, quarantine of asymptomatic individuals and control the contact rate between people can quickly and effectively inhibit development of the local epidemic. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Prognostic study Language: English Journal: 2022 Global Conference on Robotics, Artificial Intelligence and Information Technology, GCRAIT 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Prognostic study Language: English Journal: 2022 Global Conference on Robotics, Artificial Intelligence and Information Technology, GCRAIT 2022 Year: 2022 Document Type: Article