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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahmad, W., Abbas, M., Rafiq, M., Baleanu, D.: Mathematical analysis for the effect of voluntary vaccination on the propagation of corona virus pandemic. Results Phys. 31, 104917 (2021)
Al-Amer, R., et al.: Covid-19 vaccination intention in the first year of the pandemic: a systematic review. J. Clin. Nurs. 31(1–2), 62–86 (2022)
Asim, M.N., Wasim, M., Khan, M.U.G., Mahmood, W., Abbasi, H.M.: A survey of ontology learning techniques and applications. Database 2018 (2018)
Bayes, C., Valdivieso, L., et al.: Modelling death rates due to covid-19: A bayesian approach. arXiv preprint arXiv:2004.02386 (2020)
Below, D., Mairanowski, F.: The impact of vaccination on the spread patterns of the covid epidemic. medRxiv (2021)
Bloom, D.E., Canning, D., Weston, M.: The value of vaccination. In: Fighting the Diseases of Poverty, pp. 214–238. Routledge (2017)
Buonomo, B.: Effects of information-dependent vaccination behavior on coronavirus outbreak: insights from a siri model. Ricerche mat. 69(2), 483–499 (2020)
Campos-Mercade, P., Meier, A.N., Schneider, F.H., Meier, S., Pope, D., Wengström, E.: Monetary incentives increase covid-19 vaccinations. Science 374(6569), 879–882 (2021)
Chimmula, V.K.R., Zhang, L.: Time series forecasting of covid-19 transmission in Canada using LSTM networks. Chaos, Solitons Fractals 135, 109864 (2020)
Cihan, P.: Forecasting fully vaccinated people against covid-19 and examining future vaccination rate for herd immunity in the US, Asia, Europe, Africa, South America, and the world. Appl. Soft Comput. 111, 107708 (2021)
Hilorme, T., Tkach, K., Dorenskyi, O., Katerna, O., Durmanov, A.: Decision making model of introducing energy-saving technologies based on the analytic hierarchy process. Journal of Management Information and Decision Sciences 22(4), 489–494 (2019)
Khadir, A.C., Aliane, H., Guessoum, A.: Ontology learning: Grand tour and challenges. Comput. Sci. Rev. 39, 100339 (2021)
Kyrychko, Y.N., Blyuss, K.B., Brovchenko, I.: Mathematical modelling of the dynamics and containment of covid-19 in Ukraine. Sci. Rep. 10(1), 1–11 (2020)
Marchau, V.A., Walker, W.E., Bloemen, P.J., Popper, S.W.: Decision making under deep uncertainty: from theory to practice. Springer Nature (2019)
Marden, J.R., Shamma, J.S.: Game theory and control. Ann. Rev. Control Robot. Autonomous Syst. 1, 105–134 (2018)
Nesteruk, I.: Visible and real sizes of the covid-19 pandemic in ukraine (2021)
Paul, A., Sikdar, D., Mahanta, J., Ghosh, S., Jabed, M.A., Paul, S., Yeasmin, F., Sikdar, S., Chowdhury, B., Nath, T.K.: Peoples’ understanding, acceptance, and perceived challenges of vaccination against covid-19: a cross-sectional study in Bangladesh. PLoS ONE 16(8), e0256493 (2021)
Pavlyuk, O., Fedevich, O., Strontsitska, A.: Forecasting the number of patients with covid-19 in LVIV region. Bull. Vinnytsia Polytech. Inst. 3, 57–64 (2020)
Peng, L., Guo, Y., Hu, D.: Information framing effect on public’s intention to receive the covid-19 vaccination in china. Vaccines 9(9), 995 (2021)
Perumal, V., Narayanan, V., Rajasekar, S.J.S.: Detection of covid-19 using CXR and CT images using transfer learning and Haralick features. Appl. Intell. 51(1), 341–358 (2021)
Sarica, S., Luo, J.: Design knowledge representation with technology semantic network. Proc. Design Soc. 1, 1043–1052 (2021)
Semerikov, S., et al.: Our sustainable coronavirus future (2020)
Senkivskyy, V., Kudriashova, A.: Multifactorial selection of alternative options for an edition design based on a fuzzy preference relation. Printing and Publishing 73(1), 80–86 (2017)
Senkivskyy, V., Pikh, I., Kudriashova, A., Lytovchenko, N.: Theoretical fundamentals of quality assurance of publishing and printing processes (part 2: Synthesis of priority models of factors action). Printing and Publishing 71(1), 20–29 (2016)
Senkivskyy, V., Pikh, I., Babichev, S., Kudriashova, A., Senkivska, N.: Modeling of alternatives and defining the best options for websites design. In: IntelITSIS, pp. 259–270 (2021)
Shekera, O.: Analytical review of the global coronavirus infection pandemic in Ukraine. Health Soc. 10(1), 14–25 (2021)
Taha, H.A.: Operations Research: An Introduction, vol. 790. Pearson/Prentice Hall Upper Saddle River, NJ (2011)
Troiano, G., Nardi, A.: Vaccine hesitancy in the era of covid-19. Public Health 194, 245–251 (2021)
Walkowiak, M.P., Walkowiak, D.: Predictors of covid-19 vaccination campaign success: lessons learnt from the pandemic so far. a case study from poland. Vaccines 9(10), 1153 (2021)
Yang, L., Cormican, K., Yu, M.: Ontology-based systems engineering: a state-of-the-art review. Comput. Ind. 111, 148–171 (2019)
Zhu, Q., Rass, S.: Game theory meets network security: a tutorial. In: Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, pp. 2163–2165 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-031-16203-9_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-16202-2
Online ISBN: 978-3-031-16203-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)