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Data Science for COVID-19 Vaccination Management

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Innovations in Bio-Inspired Computing and Applications (IBICA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 419))

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Abstract

Medicine and health are essential sectors in industrial societies. Extracting knowledge from the vast amount of data related to disease records and medical records of individuals using the data mining process can identify the laws governing the creation, growth, and spread of disease and provide valuable information to identify the causes of disease. To diagnose, predict and treat diseases according to the prevailing environmental factors to provide health professionals and practitioners. The result of this issue is to increase life expectancy and create peace for the people of the society. With the spread of the COVID-19 virus in recent months worldwide, various organizations are working to find ways to combat the virus. By using data mining technology, intelligent systems can be developed that can automatically understand and interpret the medical characteristics of individuals and extract useful information that can play an effective role in the process of vaccine supply chain management. In this article, we have proposed a solution for the efficient COVID-19 vaccination management.

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Author information

Authors and Affiliations

  1. Faculty of Technology, Department of Informatics, Linnaeus University, Kalmar, Sweden

    Elham Rezaei & Kajal Ghoreyshi

  2. Department of Computer and Systems Sciences (DSV), Stockholm University (SU), Stockholm, Sweden

    Kazi Masum Sadique

Authors
  1. Elham Rezaei
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  2. Kajal Ghoreyshi
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  3. Kazi Masum Sadique
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Corresponding author

Correspondence to Kazi Masum Sadique .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  3. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  5. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Anu Bajaj

  6. Faculty of Information Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Melaka, Malaysia

    Azah Kamilah Muda

  7. Vilnius University, Kaunas, Lithuania

    Dalia Kriksciuniene

  8. Lisbon University Institute, Lisbon, Portugal

    João Carlos Ferreira

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Rezaei, E., Ghoreyshi, K., Sadique, K.M. (2022). Data Science for COVID-19 Vaccination Management. In: Abraham, A., et al. Innovations in Bio-Inspired Computing and Applications. IBICA 2021. Lecture Notes in Networks and Systems, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-96299-9_80

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