A study of the COVID-19 epidemic in India using the SEIRD model

Abstract

Background: The coronavirus pandemic (COVID-19) is causing a havoc globally, exacerbated by the newly discovered SARS-CoV-2 virus. Due to its high population density, India is one of the most badly effected countries from the first wave of COVID-19. Therefore, it is extremely necessary to accurately predict the state-wise and overall dynamics of COVID-19 to get the effective and efficient organization of resources across India.

Methods: In this study, the dynamics of COVID-19 in India and several of its selected states with different demographic structures were analyzed using the SEIRD epidemiological model. The basic reproductive ratio R ₀ was systemically estimated to predict the dynamics of the temporal progression of COVID-19 in India and eight of its states, Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh.

Results: For India, the SEIRD model calculations show that the peak of infection is expected to appear around the middle of October, 2020. Furthermore, we compared the model scenario to a Gaussian fit of the daily infected cases and obtained similar results. The early imposition of a nation-wide lockdown has reduced the number of infected cases but delayed the appearance of the infection peak significantly.

Conclusion: After comparing our calculations using India’s data to the real life dynamics observed in Italy and Russia, we can conclude that the SEIRD model can predict the dynamics of COVID-19 with sufficient accuracy.

Author summary

The first step in combating a contagious disease, such as COVID-19, is to obtain accurate predictions of its dynamics. This is especially crucial for large countries like India, with highly diversified states. This paper would demonstrate how one can predict the spread of COVID-19 using the SEIRD model. Our calculations indicate that the first wave of COVID-19 in India would stop by the end of October of 2020, with varying dates for the different states.

Graphical abstract

Keywords

COVID-19 / SARS-CoV-2 / epidemic / statistical analysis / SEIRD model

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ACKNOWLEDGEMENTS

We acknowledge the infrastructural supports provided by IIIT Allahabad, where this study was conducted during the lockdown period.

COMPLIANCE WITH ETHICS GUIDELINES

The authors Rudra Banerjee, Srijit Bhattacharjee and Pritish Kumar Varadwaj declare that they have no conflict of interests.

All procedures performed in studies were in accordance with the ethical standards of the institution or practice at which the studies were conducted.

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