Building Time Series Prognostic Models to Analyze the Spread of COVID-19 Pandemic

  • Ch. V. Raghavendran, G. Naga Satish, Rama Reddy T., B. Annapurna

Abstract

The COVID-19 was officially confirmed as a pandemic by World Health Organization (WHO). It is an infectious disease that has been spreading swiftly across the globe, creating unprecedented lockdowns. This virus spreads among humans through small droplets from the nose or mouth of an infected person. In this 21st century with most advanced technology available, we are not able to control it. In this paper, we will study how the Time Series based Machine Learning (ML) techniques are useful for analyzing and predicting the Confirmed cases, Recovered cases and Deaths caused by COVID-19. We analyze the spread of COVID-19 and try to forecast the possible cases in the coming days using the datasets from John Hopkins University. We implement different Regression techniques, Time series forecasting technique like Auto ARIMA, Facebook Prophet Model to analyze on the rise and extent of the virus.

Published
2020-03-30
How to Cite
Ch. V. Raghavendran, G. Naga Satish, Rama Reddy T., B. Annapurna. (2020). Building Time Series Prognostic Models to Analyze the Spread of COVID-19 Pandemic. International Journal of Advanced Science and Technology, 29(3), 13258 -. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/31524
Section
Articles