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Prognostic Assessment of COVID-19 Vaccination Levels

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Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making (ISDMCI 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 149))

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Abstract

In order to move to a stable life rhythm and a satisfactory condition of people, which would ensure the organization of the usual mode of daily activities, it is necessary to achieve a sufficiently complete vaccination of the population in a region. At the same time, significant obstacles to achieving the desired result in Ukraine are the hesitation of a large part of the population regarding the vaccination, fear of a purely medical procedure, and distrust of its effectiveness. Due to the lack of a wide range of scientifically grounded research of this problem, insufficient attention is paid to a deeper analysis of the factors influencing the intensity and effectiveness of vaccination. In view of what has been said in the proposed article, many factors related to the vaccination process have been identified based on the developed ontology. A formalized representation of the connections between factors has been made using the semantic network as an information database, which has become a prerequisite for ranking by weight factors. Using the methodology of hierarchies modelling, the levels of factors preferences are established and a multilevel model of their priority influence on the researched process is synthesized. Alternative options for the vaccination process have been designed and a prognostic assessment of the levels of COVID-19 vaccination intensity has been carried out, which allows the selection of the optimal option for the specific parameters of the initial factors.

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Authors and Affiliations

  1. Ukrainian Academy of Printing, Lviv, Ukraine

    Iryna Pikh, Vsevolod Senkivskyy, Alona Kudriashova & Nataliia Senkivska

  2. Lviv Polytechnic National University, Lviv, Ukraine

    Iryna Pikh & Nataliia Senkivska

Authors
  1. Iryna Pikh
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  2. Vsevolod Senkivskyy
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  3. Alona Kudriashova
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  4. Nataliia Senkivska
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Corresponding author

Correspondence to Alona Kudriashova .

Editor information

Editors and Affiliations

  1. Jan Evangelista Purkyně University in Ústi nad Labem, Ústi nad Labem, Czech Republic

    Sergii Babichev

  2. Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko

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Pikh, I., Senkivskyy, V., Kudriashova, A., Senkivska, N. (2023). Prognostic Assessment of COVID-19 Vaccination Levels. In: Babichev, S., Lytvynenko, V. (eds) Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making. ISDMCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 149. Springer, Cham. https://doi.org/10.1007/978-3-031-16203-9_15

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