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Research Article Open access CC BY 4.0

Predictive Analysis of Real-Time Strategy using Face book’s Prophet Model on Covid-19 Dataset of India

Pankaj Kumar, Renuka Sharma, S. K. Singh

Journal of Pharmaceutical Research International · pp. 305–312 · Published 23 Nov 2021

10.9734/jpri/2021/v33i51A33496

Abstract

The global epidemic of the novel coronavirus (COVID-19) called SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) has infected millions and killed millions. The prevalence of the virus is of paramount importance in identifying future infections and preparing healthcare facilities to avoid death. Accurately predicting the spread of COVID-19 is a challenging analytical and practical task for the research community. We can learn to use predictive analytics to predict the positive outcomes of these risks. These predictive analytics can look at the risks of past successes and failures. In this paper, the Facebook prophet model discusses the number of large-scale cases and deaths in India based on daily time-series data from 30 January 2020 to 30 April 2021, for forecasting and visualization. The covid-19 pandemic could end prematurely if social distancing and safety measures are required to stabilize and control is required to achieve treatment in India. This paper suggests that the Prophet Model is more effective in predicting COVID-19 cases. The forecast results will help the government plan strategies to prevent the spread of the coronavirus.

Prophet India Covid-19 coronavirus face book prediction machine learning

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