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Predicting Number of COVID-19 Cases in India – Abinash Chakraborty

researchsnappy by researchsnappy
May 18, 2020
in Healthcare Research
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Predicting Number of COVID-19 Cases in India – Abinash Chakraborty
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Abinash Chakraborty

The first confirmed case of COVID-19 in India was reported on 30-Jan-2020 in the state of Kerela. The number of confirmed cases in India was low till 15-Mar-2020, presumably because patients with COVID-19-like symptoms were not being tested.

As can be seen in the graph above, since 15-Mar-2020, there is a seeming exponential rise in the number of COVID-19 cases in India.

To predict the Total Number of Confirmed Cases, I’ve used a linear regression model to fit the data.

It is assumed that Total Number of Confirmed COVID-19 Cases in India (y) is a function of Number of Days (x) since SARS-COV2 first entered India, modelled as —

where a and lambda are constants to be determined.

The natural way to fit this would be to use Linear Regression for Logarithms of y and x. However, in doing so, only the dataset post 30-Mar-2020 has been used. This is for two reasons —

  1. India started testing more aggressively post-30th March
  2. Tablighi Jamaat Cluster (discovered around the 30-Mar) led to huge spike in the number of confirmed cases.

Based on this fitting, the following prediction was made for the Total Number of Confirmed COVID-19 Cases in India on 14-Apr-2020 —

As of 15-Apr-2020 5 PM, the Total Confirmed Cases in India as per the Ministry of Health is 11933. That’s an error <0.3% against my prediction.

Among the States/Union Territories of India, the State of Maharashtra is worst affected.

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