Time series analysis for predicting Covid-19 infection using Facebook prophet model

Abstract

The International fright due to the occurrence of COVID has created an emergency act in the field of healthcare, bio medical and drug discovery process. However, finding the feasible solution to introduce a drug is a time-consuming process due to pre-clinical and post-clinical testing process. Prediction and estimation of COVID-19 can help the medical practitioners and government authorities to take preventable measure against the outcomes of COVID-19.From December 2019 to April 2020, 2844712 cases of COVID-19 have been informed, which includes 201315 deaths according to European Centre for Disease Prevention and Control. This drastic condition should be treated not only physicians and other health care providers. There are two types of time series forecasting techniques. The first technique time-domain approach models the forthcoming values as a function of previous and current values. The groundwork of this approach is the time series regression of current values of a time series on its own past values. The assessments of the model are applied for forecasting process. The second technique known as Frequency domain models are based on the interpretations of time using sines and cosines functions. These interpretations are known as Fourier representations. Overall, the technique utilizes regressions on sines and cosines function, to model the behavior of the data. The proposed work used Facebook Prophet model for Time Series Analysis to forecast the trend for the year 2021. The models will act as an inference tool to take decisions during pandemic conditions. © 2021 Karadeniz Technical University. All rights reserved.