Time Series Analysis of COVID-19 Data to Study the Effect of Lockdown and Unlock in India

被引：4

作者：

Singh S. ^{[1
]}

Chowdhury C. ^{[1
]}

Panja A.K. ^{[1
]}

Neogy S. ^{[1
]}

机构：

[1] Department of Computer Science and Engineering, Jadavpur University, Kolkata

来源：

Chowdhury, Chandreyee (chandreyee.chowdhury@jadavpuruniversity.in) | 1600年 / Springer卷 / 102期

关键词：

ARIMA; COVID-19; Forecast; Time series; Trend;

D O I：

10.1007/s40031-021-00585-7

中图分类号：

学科分类号：

摘要：

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. © 2021, The Institution of Engineers (India).

引用

页码：1275 / 1281

页数：6

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