Forecasting COVID-19 Cases Using n-SARS-CoV-2 Variants

ABSTRACT

This work proposes a novel Deep Learning-based model to forecast the total number of confirmed COVID-19 cases in four of the worst-hit states of India. Along with statewide restrictions and public holidays, a novel parameter is introduced for training the proposed model, which considers the Alpha, Beta, Delta, and Omicron variants and the degree of their prevalence in each of the four states. Recurrent Neural Network-based Long-Short Term Memory is applied to the custom dataset, with the lowest Mean Absolute Percentage Error being 0.77% for the state of Maharashtra. SHapley Additive exPlanations values are used to examine the significance of the various parameters. The proposed model can be applied to other countries and can include newer variants of the novel coronavirus discovered in the future. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.