Prediction model of the pandemic spreading based on weibull distribution

• Autorzy: Guľáš Ľuboš , Talian Matej , Szabo Stanislav , Semrádová Beáta

Identyfikatory

DOI

10.2478/mspe-2022-0022

• Języki publikacji: EN

Abstrakty

EN

Pandemics have the potential to cause immense disruption of our everyday activities and has impact on the communities and societies mainly through the restrictions applied to the business activities, services, manufacturing, but also education, transportation etc. Therefore, it is important to create suitable prediction models to establish convenient methods for the planning of the operations and processes to cope with the difficulty. In this paper, the prediction model for the spread of the viral disease in term of the estimated maximal weekly confirmed cases and weekly deaths using the Weibull distribution as a theoretical model for statistical data processing is presented. The theoretical prediction model was applied and confirmed on the data available for the whole world and compared to the situation in Europe and Slovakia for the pandemic waves and can be used for the more precise prediction of the pandemic situation and to enhance planning of the activities and processes regarding to the restrictions applied during the worsening pandemic situation.

Słowa kluczowe

EN

pandemics; prediction model; Weibull distribution

• Wydawca: STE GROUP
• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2022
• Tom: nr 2 (30)
• Strony: 179--186
• Opis fizyczny: Bibliogr. 45 poz., rys., tab.

Twórcy

autor

Guľáš Ľuboš

• Training Centre Lest 962 63 Pliesovce, Slovakia

autor

Talian Matej

• Training Centre Lest 962 63 Pliesovce, Slovakia

autor

Szabo Stanislav

• Technical University of Kosice Faculty of Aeronautics Rampova 7, 040 01 Kosice, Slovakia

autor

Semrádová Beáta

• Technical University of Kosice Faculty of Aeronautics Rampova 7, 040 01 Kosice, Slovakia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu „Społeczna odpowiedzialność nauki” - moduł: Popularyzacja nauki i promocja sportu (2022-2023).