Covid-19 SIHR modeling and dynamic analysis

Zhenhe Pan, Taige Wang, Yuanlin Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021
EditorsW. K. Chan, Bill Claycomb, Hiroki Takakura, Ji-Jiang Yang, Yuuichi Teranishi, Dave Towey, Sergio Segura, Hossain Shahriar, Sorel Reisman, Sheikh Iqbal Ahamed
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1711-1716
Number of pages6
ISBN (Electronic)9781665424639
DOIs
StatePublished - Jul 2021
Event45th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2021 - Virtual, Online, Spain
Duration: Jul 12 2021Jul 16 2021

Publication series

NameProceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021

Conference

Conference45th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2021
Country/TerritorySpain
CityVirtual, Online
Period07/12/2107/16/21

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