Epidemiological modeling based on coronavirus data

Monika Szymura; Martyna Horst; Anna Altmann

Epidemiological modeling based on coronavirus data

Monika Szymura
, Martyna Horst
, Anna Altmann

Katedra Matematyki (RMS/RMS1)

Silesian University of Technology

Wyniki badań: Wkład do czasopisma › Artykuł z konferencji › recenzja

Abstrakt

The article presents selected compartmental epidemiological models. The SI model is discussed, which is considered to be the most basic epidemiological compartmental model. The SVIR model was also analyzed, which additionally takes into account e.g. use of vaccinations. In addition to theoretical elaboration, the article also includes simulations based on real coronavirus pandemic data in selected countries. The obtained results show that on the basis of real data from a certain period of time, it is possible to predict the trend of the further course of infection in a given population.

Język oryginału	angielski
Strony (od–do)	102-111
Liczba stron	10
Czasopismo	CEUR Workshop Proceedings
Tom	3575
Status publikacji	Opublikowano - 2023
Wydarzenie	28th International Conference on Information Society and University Studies, IVUS 2023 - Kaunas, Litwa Czas trwania: 12 maj 2023 → …

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Cytowanie

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title = "Epidemiological modeling based on coronavirus data",

abstract = "The article presents selected compartmental epidemiological models. The SI model is discussed, which is considered to be the most basic epidemiological compartmental model. The SVIR model was also analyzed, which additionally takes into account e.g. use of vaccinations. In addition to theoretical elaboration, the article also includes simulations based on real coronavirus pandemic data in selected countries. The obtained results show that on the basis of real data from a certain period of time, it is possible to predict the trend of the further course of infection in a given population.",

keywords = "SARS-Cov-2, differential equation, epidemic, epidemiological model, mathematical model",

author = "Monika Szymura and Martyna Horst and Anna Altmann",

note = "Publisher Copyright: {\textcopyright} 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org); 28th International Conference on Information Society and University Studies, IVUS 2023 ; Conference date: 12-05-2023",

year = "2023",

language = "English",

volume = "3575",

pages = "102--111",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

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}

TY - JOUR

T1 - Epidemiological modeling based on coronavirus data

AU - Szymura, Monika

AU - Horst, Martyna

AU - Altmann, Anna

N1 - Publisher Copyright: © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)

PY - 2023

Y1 - 2023

N2 - The article presents selected compartmental epidemiological models. The SI model is discussed, which is considered to be the most basic epidemiological compartmental model. The SVIR model was also analyzed, which additionally takes into account e.g. use of vaccinations. In addition to theoretical elaboration, the article also includes simulations based on real coronavirus pandemic data in selected countries. The obtained results show that on the basis of real data from a certain period of time, it is possible to predict the trend of the further course of infection in a given population.

AB - The article presents selected compartmental epidemiological models. The SI model is discussed, which is considered to be the most basic epidemiological compartmental model. The SVIR model was also analyzed, which additionally takes into account e.g. use of vaccinations. In addition to theoretical elaboration, the article also includes simulations based on real coronavirus pandemic data in selected countries. The obtained results show that on the basis of real data from a certain period of time, it is possible to predict the trend of the further course of infection in a given population.

KW - SARS-Cov-2

KW - differential equation

KW - epidemic

KW - epidemiological model

KW - mathematical model

UR - https://www.scopus.com/pages/publications/85179620859

M3 - Conference article

AN - SCOPUS:85179620859

SN - 1613-0073

VL - 3575

SP - 102

EP - 111

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 28th International Conference on Information Society and University Studies, IVUS 2023

Y2 - 12 May 2023

ER -

Epidemiological modeling based on coronavirus data

Abstrakt

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

Inne pliki i linki

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Cytowanie