Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study

Abstract

Highlights Developed deep learning methods to forecast the COVID19 spread. Five deep learning models have been compared for COVID-19 forecasting. Time-series COVID19 data from Italy, Spain, France, China, the USA, and Australia are used. Results demonstrate the potential of deep learning models to forecast COVID19 data. Results show the superior performance of the Variational AutoEncoder model.

Applications of artificial intelligence in battling against covid-19: A literature review

“…Comparing different deep learning algorithms: A comparative study over a number of DNN algorithms in predicting the epidemic is presented in [423] . In this work, simple Recurrent Neural Network (RNN), Long short-term memory (LSTM), Bidirectional LSTM (BiLSTM), Gated recurrent units (GRUs) and Variational AutoEncoder (VAE) algorithms have been studied based on daily confirmed and recovered cases collected from six countries namely Italy, Spain, France, China, USA, and Australia.…”

Novel spatiotemporal feature extraction parallel deep neural network for forecasting confirmed cases of coronavirus disease 2019

“…Accurately predicting the development of new cases can more effectively manage the resulting excess demand in the entire supply chain. Zeroual et al [ 10 ] found that effective management of infected patients has become a challenging problem facing hospitals. Accurate short-term prediction of the number of new infections and recovered cases is essential to optimize available resources and prevent or slow the development of such diseases.…”

Effect of an antiviral drug control in host COVID-19 kinetics

“…Theorem 1. All the solutions of the system (1) subject to initial condition (2) are positive and bounded in R 3 + , for all t > 0.…”

“…Also, the Government of states has implemented lockdown, travel restrictions, quarantine measures and testing to control the disease. Several epidemiological mathematical models [3][4][5][6][7][8][9] have been developed to make the right decisions in these measures. These have highlighted that social distancing intervention to mitigate the epidemic is a key aspect.…”