Numerical Forecasting of Covid-19 Epidemic in Odisha Using S.I.R Model: A Case Study
DOI:
https://doi.org/10.13052/jgeu0975-1416.1023Keywords:
SIR model, basic reproduction number, COVID-19, lockdown, herd immunity.Abstract
In this paper, we study the effectiveness of SIR model (Susceptible- Infected-
Removed) in predicting the future development of infectious disease caused
by SARS-CoV-2 virus for the Indian state of Odisha. This model helps in
checking the effectiveness of controlling measures like lockdown policies
and helps in framing new strategies to control the spread of the disease.
We formulate a set of differential equations to find the rate of change of
susceptible, infected and removed population with respect to time and solve
it using Euler’s method. Using the cumulative data of confirmed cases, we
try to find the answers to the question of COVID-19 surge. Also, through this
we predict the trend in the spread of covid-19 in the state for the next few
months. The analysis includes data from March 1 (which is marked as the
start of second wave of COVID) to June 28, 2021. We propose predictions
on various parameters and factors related to the spread of COVID-19 and
on the number of susceptible, infected and removed population until June 2021. By comparing the daily recorded data with the data from our modeling
approaches, we conclude that the spread of COVID-19 can be under control
in all communities, if proper lockdown restrictions and strong policies are
implemented to control the infection rates.
Downloads
References
Bagal, D., Rath, A., Barua, A., and Patnaik, D. (2021). Estimating the
parameters of susceptible-infected-recovered model of COVID-19 cases
in India during lockdown periods. Retrieved 27 August 2021, from
https://pubmed.ncbi.nlm.nih.gov/32834642/.
Biswas, S., Ghosh, J., Sarkar, S., and Ghosh, U. (2020). COVID-19 pandemic
in India: a mathematical model study. Nonlinear Dynamics, 102(1),
–553. https://doi.org/10.1007/s11071-020-05958-z
CDRI Report (2020). Response to COVID-19: Odisha, India. www.cdri.wor
ld/casestudy/response-tocovid19-by-odisha.pdf.
S. Kapoor and B. Jana
COVID-19: Odisha State Dashboard. State Dashboard. (2021). Retrieved 4
September 2021, from https://statedashboard.odisha.gov.in/.
Cooper, I., Mondal, A., and Antonopoulos, C. (2021). A SIR model assump-
tion for the spread of COVID-19 in different communities. Retrieved 27
August 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7
/.
Carcione, J., Santos, J., Bagaini, C., and Ba, J. (2021). A Simulation of a
COVID-19 Epidemic Based on a Deterministic SEIR Model. Retrieved
August 2021, from https://www.frontiersin.org/articles/10.3389/fpu
bh.2020.00230/full.
Garikipati N (2020).Odisha’s quiet success in warfare on Covid-19 pan-
demic. Coverage Circle. https://www.policycircle.org/life/odishas-
quiet-success-in-war-on-covid
Hojman, S., and Asenjo, F. (2020). Phenomenological dynamics of COVID-
pandemic: Meta-analysis for adjustment parameters. Chaos: An
Interdisciplinary Journal Of Nonlinear Science, 30(10), 103120. https:
//doi.org/10.1063/5.0019742
Infection rate – Wikipedia. (2021). Retrieved 9 September 2021, from https:
//en.wikipedia.org/wiki/Infection rate
Kumar M, Ghosh S (2020).Using lessons from disaster management, Odisha
takes on Covid-19. MONGABAY. https://india.mongabay.com/2020/04
/using-lessons-from-disaster-management-odisha-takes-on-covid-19/
Kumar S, Maheshwari V, Prabhu J, Prasanna M et al (2020). Social eco-
nomic impact of COVID-19 outbreak in India. Int J Pervasive Compute
Common 16(4):309–319. https://doi.org/10.1108/IJPCC-06-2020-0053
Kwok OK, Lai F et al. (2020). Herd immunity–estimating the level required to
halt the COVID-19 epidemics in affected countries. J Infect 80(6):32–33.
https://doi.org/10.1016/j.jinf.2020.03.027
Mathematical modelling of infectious disease - Wikipedia. En.wikipedia.org.
(2021). Retrieved 27 August 2021, from https://en.wikipedia.org/wiki/
Mathematical modelling of infectious disease.
Mohanty D (2020).How the Covid-19 pandemic unfolded in Odisha. Hindus-
tan Times. www.hindustantimes.com/india-news/how-the-covid-19-p
andemic-unfolded-in-odisha/story-HVv0Y5KB1mGXiP1TiKrHI.html
Mukesh Jahar, P.K. Ahluwalia and Ashok Kumar. (2020). COVID-19 Epi-
demic Forecast in Different States of India using SIR Model. Retrieved
August 2021, from https://www.medrxiv.org/content/10.1101/2020
.05.14.20101725v1.full.pdf.
Numerical Forecasting of Covid-19 Epidemic in Odisha 115
Pani MB (2020).No End to COVID-19 containment woes for residents of
Katapali in Odisha. The New Indian Express. www.newindianexpress.c
om/states/odisha/2020/jul/30/no-end-to-covid-19-containment-woes-f
or-residents-of-katapali-in-odisha-2176649.html.
Pal M (2020).Empower gram panchayats to be able to deal with crises like
COVID-19 effectively in rural areas. National Herald.. www.nationalhe
raldindia.com/india/empower-gram-panchayats-to-beable-to-deal-with
-crises-like-covid-19-effectively-in-rural-areas
Riyapan, P., Shuaib, S., and Intarasit, A. (2021). A Mathematical Model of
COVID-19 Pandemic: A Case Study of Bangkok, Thailand. Retrieved 25
August 2021, from https://www.hindawi.com/journals/cmmm/2021/6
/.
Roberto Telles, C., Lopes, H., and Franco, D. (2021). SARS-COV-2: SIR
Model Limitations and Predictive Constraints. Symmetry, 13(4), 676.
https://doi.org/10.3390/sym13040676
Telles, C., Roy, A., Ajmal, M., Mustafa, S., Ahmad, M., and de la Serna, J.
et al. (2021). The Impact of COVID-19 Management Policies Tailored
to Airborne SARS-CoV-2 Transmission: Policy Analysis. JMIR Public
Health And Surveillance, 7(4), e20699. https://doi.org/10.2196/20699
Tiwari, V., Deyal, N., and Bisht, N. (2021). Mathematical Modeling Based
Study and Prediction of COVID-19 Epidemic Dissemination Under the
Impact of Lockdown in India. Retrieved 25 August 2021, from https:
//www.frontiersin.org/articles/10.3389/fphy.2020.586899/full.
Zaman, G., Jung, I., Torres, D., and Zeb, A. (2021). Mathematical Modeling
and Control of Infectious Diseases. Retrieved 23 August 2021, from ht
tps://www.hindawi.com/journals/cmmm/2017/7149154/.
