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Evaluating the Sustainable COVID-19 Vaccination Framework of India Using Recurrent Neural Networks

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Abstract

COVID-19 has laid an impact on every sector of the world. Howsoever severe, vaccines have acted as the sole source of a protective guard to prevent the further spread of the COVID-19 pandemic. In this research, the authors broadly focus on the trends in the vaccination drive of India. The paper revolves around a prediction and evaluation approach, which depending on the past and the current trends of daily vaccinations, obtain comparable results using a self-built recurrent neural network of LSTM layers for this study on time series evaluation. Through the neural network, the study predicts the exact vaccination figures likely to be achieved 1 year after vaccine introduction in the Indian subcontinent. The gathered data from January 16, 2021, until September 30, 2021, follow effective visualization of how the model outputs resemble the vaccination numbers for October 2021 and the predictions until January 16, 2022. Finally, the paper follows an extensive data analysis keeping in mind, the analogy of the number of COVID-19 cases and deaths before and after the vaccination system was centralized, to prove how sustainable the framework has been so far.

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Acknowledgement

This research work is supported by National Science and Technology Council (NSTC), Taiwan Grant No. NSTC112-2221-E-468-008-MY3.

Author information

Author notes

  1. Brij B. Gupta

    Present address: CCRI & Department of Computer Science and Information Engineering, Asia University, Taichung, 413, Taiwan

Authors and Affiliations

  1. Department of Computer Science and Engineering, Chandigarh College of Engineering and Technology, Sector-26, Chandigarh, 160019, India

    Anshul Gupta, Sunil K. Singh & Muskaan Chopra

  2. Department of Computer Science and Engineering, Indraprastha Institute of Information Technology, New Delhi, Delhi, 110020, India

    Shabeg Singh Gill

  3. Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, 02447, Seoul, South Korea

    Brij B. Gupta

  4. Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India

    Brij B. Gupta

  5. Lebanese American University, 1102, Beirut, Lebanon

    Brij B. Gupta

  6. Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, India

    Brij B. Gupta

  7. Department of Computer Science, Faculty of Engineering, Albert Ludwigs University of Freiburg, Freiburg im Breisgau, Deutschland

    Anshul Gupta

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All authors contributed equally for this research work.

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Correspondence to Anshul Gupta, Sunil K. Singh or Brij B. Gupta.

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The authors declare that there has not been any conflict amongst the authors in the work stated.External data that has been gathered during the course of this research is clearly stated in the article wherever required. The final datasets generated after cleaning are available from the corresponding author upon reasonable request.

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Gupta, A., Singh, S.K., Gupta, B.B. et al. Evaluating the Sustainable COVID-19 Vaccination Framework of India Using Recurrent Neural Networks. Wireless Pers Commun 133, 73–91 (2023). https://doi.org/10.1007/s11277-023-10751-3

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