Abstract
Novel corona virus (Covid-19) is biggest challenge for whole world. World Health Organization (WHO) mentioned this is epidemic.Data has been collected from 209 different individual situation reports of World health organization for Covid-19 in India. First compared the forecasting models on the basis minimum AIC, MAPE, MAE and then best model have been used for forecasting on the India epidemiological data to anticipate the epidemiological pattern of the prevalence.
Highlights
Corona viruses are a large family of viruses that cause illness ranging from the common cold to more severe diseases
First compared the forecasting models on the basis minimum Akaike information criterion (AIC), Mean absolute percentage error (MAPE), Mean absolute error (MAE) and best model have been used for forecasting on the India epidemiological data to anticipate the epidemiological pattern of the prevalence
The data for this paper considers descriptive analysis to allow easy and convenience forecasting and the Autoregressive Integrated Moving Average (ARIMA) (p, 1, q) procedure is considered effective because of the trend of the Covid-19 data
Summary
Corona viruses are a large family of viruses that cause illness ranging from the common cold to more severe diseases. Corona viruses were first discovered in the 1930s when an acute respiratory infection of domesticated chickens was shown to be caused by infectious bronchitis virus (IBV). Arthur Schalk and M.C. Hawn described in 1931 a new respiratory infection of chickens in North Dakota. The infection of new-born chicks was characterized by gasping and listlessness. Human corona viruses were discovered in the 1960s. Other human corona viruses have since been identified, including SARS-CoV in 2003, HCoV NL63 in 2004, HCoV HKU1 in 2005, MERS-CoV in 2012, and SARS-CoV-2 in 2019. There have been a large number of animal corona viruses identified since the 1960 [1]
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