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

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.