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Compartmental Epidemic Model for COVID analysis

reference : https://arxiv.org/pdf/2002.06563.pdf

seirqdp model

To characterize the epidemic of COVID-19, a generalized classical SEIR model is used by introducing 7 different states

Constant

is the total population.

The coefficients are

  • <\alpha> → protection rate
  • <\beta> → infection rate
  • <\gamma^{-1}> → avg latent time
  • <\delta^{-1}> → avg quarantine time
  • <\lambda(t)=\lambda_0(1-e^{-\lambda_1t})> → cure rate
  • <\kappa(t)=\kappa_0e^{-\kappa_1t}> → mortality rate

It is assumed the cure rate <\lambda> and the mortality rate <\kappa> are both time dependent.

The SEIRQP model is described by following differential equations

Parameter Estimation

The fitting is done using the time histories of the number of quarantined Q(t), recovered R(t) and deaths D(t) only. Time histories obtained from https://www.worldometers.info/coronavirus/country/india/

estimated model

Forecast from estimated model

forecast