Author: Singh, Saswat; Chowdhury, Chandreyee; Panja, Ayan Kumar; Neogy, Sarmistha
Title: Time Series Analysis of COVID-19 Data to Study the Effect of Lockdown and Unlock in India Cord-id: 262lp9m2 Document date: 2021_4_8
ID: 262lp9m2
Snippet: The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast the effect of unlocking in India would allow governments to alter their policies accordingly and plan ahead. The study investigated prediction forecasts using the ARIMA model on the COVID-19 data on the lockdown period and the unlock period. In this work, we have considered not only the number of positive COVID cases bu
Document: The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast the effect of unlocking in India would allow governments to alter their policies accordingly and plan ahead. The study investigated prediction forecasts using the ARIMA model on the COVID-19 data on the lockdown period and the unlock period. In this work, we have considered not only the number of positive COVID cases but also considered the number of tests carried out. The time series data sample was collected till June 2020, and the prediction and analysis are done for August 2020. The model developed and the forecasted results align very closely with the actual number of cases, and some important inferences have been drawn through the experimentation.
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