COVID-19 and India: What Next?
Ramesh Behl (International Management Institute Bhubaneswar), Manit, Mishra (International Management Institute Bhubaneswar)
TL;DR
This paper models COVID-19 spread in India and five states using the SIRD model, providing insights on peak infection dates and numbers to aid policy decisions.
Contribution
It applies a SIRD model with differential equations to COVID-19 data in India, offering predictive insights on infection peaks and durations.
Findings
Identified peak infection dates for India and states.
Estimated peak infection numbers for each region.
Predicted end dates of the COVID-19 wave in the regions.
Abstract
The study carries out predictive modeling based on publicly available COVID-19 data for the duration 01 April to 20 June 2020 pertaining to India and five of its most infected states: Maharashtra, Tamil Nadu, Delhi, Gujarat, and Rajasthan using susceptible, infected, recovered, and dead (SIRD) model. The basic reproduction number R0 is derived by exponential growth method using RStudio package R0. The differential equations reflecting SIRD model have been solved using Python 3.7.4 on Jupyter Notebook platform. For visualization, Python Matplotlib 3.2.1 package is used. The study offers insights on peak-date, peak number of COVID-19 infections, and end-date pertaining to India and five of its states. The results could be leveraged by political leadership, health authorities, and industry doyens for policy planning and execution.
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