Journal of Epidemiology and Global Health

Volume 11, Issue 1, March 2021, Pages 55 - 59

Epidemic Landscape and Forecasting of SARS-CoV-2 in India

Authors
Aravind Lathika Rajendrakumar1, *, , ORCID, Anand Thakarakkattil Narayanan Nair1, , Charvi Nangia1, ORCID, Prabal Kumar Chourasia2, Mehul Kumar Chourasia1, ORCID, Mohammed Ghouse Syed1, Anu Sasidharan Nair3, Arun B. Nair3, Muhammed Shaffi Fazaludeen Koya4, ORCID
1School of Medicine, University of Dundee, UK
2Hospitalist, Mary Washington Hospital, Fredericksburg, VA, USA
3Health System Research India Initiative, Kerala, India
4School of Public Health, Boston University, MA, USA

Contributed equally.

*Corresponding author. Email: aravindlr13@gmail.com
Corresponding Author
Aravind Lathika Rajendrakumar
Received 24 May 2020, Accepted 15 August 2020, Available Online 28 August 2020.
DOI
10.2991/jegh.k.200823.001How to use a DOI?
Keywords
COVID-19; India; R0; Rt
Abstract

Background: India was one of the countries to institute strict measures for Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) control in the early phase. Since, then, the epidemic growth trajectory was slow before registering an explosion of cases due to local cluster transmissions.

Methods: We estimated the growth rate and doubling time of SARS-CoV-2 for India and high burden states using crowdsourced time series data. Further, we also estimated the Basic Reproductive Number (R0) and Time-dependent Reproductive number (Rt) using serial intervals from the data. We compared the R0 estimated from five different methods and R0 from SB was further used in the analysis. We modified standard Susceptible-Infectious-Recovered (SIR) models to SIR/Death (SIRD) model to accommodate deaths using R0 with the sequential Bayesian method for simulation in SIRD models.

Results: On average, 2.8 individuals were infected by an index case. The mean serial interval was 3.9 days. The R0 estimated from different methods ranged from 1.43 to 1.85. The mean time to recovery was 14 ± 5.3 days. The daily epidemic growth rate of India was 0.16 [95% CI; 0.14, 0.17] with a doubling time of 4.30 days [95% CI; 3.96, 4.70]. From the SIRD model, it can be deduced that the peak of SARS-CoV-2 in India will be around mid-July to early August 2020 with around 12.5% of the population likely to be infected at the peak time.

Conclusion: The pattern of spread of SARS-CoV-2 in India is suggestive of community transmission. There is a need to increase funds for infectious disease research and epidemiologic studies. All the current gains may be reversed if air travel and social mixing resume rapidly. For the time being, these must be resumed only in a phased manner and should be back to normal levels only after we are prepared to deal with the disease with efficient tools like vaccines or medicine.

KEY POINTS

Question: What are the estimates of infectious disease parameters of early phase of novel SARS-CoV-2 epidemic in India?

Findings: Incidence pattern SARS-CoV-2 shows possible evidence of community transmission. However, the estimated Basic Reproductive Number (R0) is relatively lower than those observed in high burden regions (range 1.43–1.85). Our simulation using susceptible-infectious-recovered/death model shows that peak of SARS-CoV-2 in India is farther than currently projected and is likely to affect around 12.5% of population.

Meaning: The lower estimated R0 is indicative of the effectiveness of early social distancing measures and lockdown. Premature relaxation of the current control measures may result in large numbers of cases in India.

Copyright
© 2020 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Epidemiology and Global Health
Volume-Issue
11 - 1
Pages
55 - 59
Publication Date
2020/08/28
ISSN (Online)
2210-6014
ISSN (Print)
2210-6006
DOI
10.2991/jegh.k.200823.001How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Aravind Lathika Rajendrakumar
AU  - Anand Thakarakkattil Narayanan Nair
AU  - Charvi Nangia
AU  - Prabal Kumar Chourasia
AU  - Mehul Kumar Chourasia
AU  - Mohammed Ghouse Syed
AU  - Anu Sasidharan Nair
AU  - Arun B. Nair
AU  - Muhammed Shaffi Fazaludeen Koya
PY  - 2020
DA  - 2020/08/28
TI  - Epidemic Landscape and Forecasting of SARS-CoV-2 in India
JO  - Journal of Epidemiology and Global Health
SP  - 55
EP  - 59
VL  - 11
IS  - 1
SN  - 2210-6014
UR  - https://doi.org/10.2991/jegh.k.200823.001
DO  - 10.2991/jegh.k.200823.001
ID  - Rajendrakumar2020
ER  -