Author: Pan, Z.; Wang, T.; Zhang, Y.
Title: Covid-19 SIHR modeling and dynamic analysis Cord-id: 71sfnavm Document date: 2021_1_1
ID: 71sfnavm
Snippet: We propose a novel disease transmission model: the Susceptible-Infected-Hospitalized-Recovered (SIHR) model, which is a modification of the classical SIR model commonly used in modeling the spread of infectious diseases for understanding epidemic duration, number of infected people throughout the duration, and peak number of infected people etc. More specifically, we introduce a new hospitalization state, denoted by H, between the I and R state in the SIR model, and such new state is constrained
Document: We propose a novel disease transmission model: the Susceptible-Infected-Hospitalized-Recovered (SIHR) model, which is a modification of the classical SIR model commonly used in modeling the spread of infectious diseases for understanding epidemic duration, number of infected people throughout the duration, and peak number of infected people etc. More specifically, we introduce a new hospitalization state, denoted by H, between the I and R state in the SIR model, and such new state is constrained by the number of hospital beds denoted by M. We perform study on the dynamics of the novel SIHR model. Our numerical results based on the COVID-19 dataset from Wuhan, China show that the SIHR model illustrates much better fitting with the dataset than the classic SIR model. The computational results demonstrate how and when one should increase the hospital beds number M based on detailed numerical analysis. © 2021 IEEE.
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