We have analyzed the COVID19 epidemic data for India and some of its states between March 10 till October 3, 2020. The behavior amongst various parameters and their patterns are studied. We modeled the distributions of various epidemic parameters through multiple techniques such as generalized linear models and SIR. We found that different states are at different stages of the pandemic life-cycle. Our analysis seems to suggest India is not yet gone past its first wave. Given this reality, mitigation measures such as social distancing, wearing masks, cleaning hands can not be overemphasized. We also found that India and states’ pandemic behavior varies by a wide margin due to various practices and policies.

1.
Ramesh
 
Behl
 and
Manit
 
Mishra
 "
COVID-19 Lifecycle: Predictive Modelling of States in India
",
Global Business Review
2.
Luo
,
J.
 (
2020
).
When will COVID-19 end? Data-driven prediction.
 https://ddi.sutd.edu.sg/.
Google Scholar
 
3.
Yang
 
Z.
, et al. “
Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions
.”
Global Business Review
4.
Petropoulos
 
F.
,
Makridakis
 
S.
 “
Forecasting the novel coronavirus COVID-19
,”
PLoS ONE
,
15
(
3
):
e0231236
,
2020
.
https://doi.org/10.1371/journal.pone.0231236
Google Scholar
Crossref
Search ADS
PubMed
 
5.
Smith
 
D.
 and
Moore
 
L.
 “
The SIR Model for Spread of Disease - The Differential Equation Model
.”
Convergence
(December
2004
)
Google Scholar
 
6.
Caccavo
,
D.
 (
2020
).
Chinese and Italian COVID-19 outbreaks can be correctly described by a modified SIRD model
.
medRxiv.
doi:
https://doi.org/10.1101/2020.03.19.20039388
.
Google Scholar
 
This content is only available via PDF.
© 2021 Author(s).
2021
Author(s)
You do not currently have access to this content.