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Dynamic Behavior Investigation of a Novel Epidemic Model Based on COVID-19 Risk Area Categorization
Fractal and Fractional ; 6(8):410, 2022.
Article in English | MDPI | ID: covidwho-1957259
ABSTRACT
This study establishes a compartment model for the categorized COVID-19 risk area. In this model, the compartments represent administrative regions at different transmission risk levels instead of individuals in traditional epidemic models. The county-level regions are partitioned into High-risk (H), Medium-risk (M), and Low-risk (L) areas dynamically according to the current number of confirmed cases. These risk areas are communicable by the movement of individuals. An LMH model is established with ordinary differential equations (ODEs). The basic reproduction number R0 is derived for the transmission of risk areas to determine whether the pandemic is controlled. The stability of this LHM model is investigated by a Lyapunov function and Poincare–Bendixson theorem. We prove that the disease-free equilibrium (R0 < 1) is globally asymptotically stable and the disease will die out. The endemic equilibrium (R0 > 1) is locally and globally asymptotically stable, and the disease will become endemic. The numerical simulation and data analysis support the previous theoretical proofs. For the first time, the compartment model is applied to investigate the dynamics of the transmission of the COVID-19 risk area. This work should be of great value in the development of precision region-specific containment strategies.

Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Prognostic study Language: English Journal: Fractal and Fractional Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Prognostic study Language: English Journal: Fractal and Fractional Year: 2022 Document Type: Article