Time Series Analysis of COVID-19 Data to Study the Effect of Lockdown and Unlock in India
preprint
OA: gold
CC-BY-4.0
Abstract
Abstract 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 no 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 no of cases and we have drawn some important inferences through experimentation.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-21T05:10:58.409756+00:00
License: CC-BY-4.0