A Conjectural Experiment to Observe the Effect of Conditional locked-down in an Epidemic

TL;DR

This study uses a stochastic SEIR model to analyze the timing and duration of lockdowns in epidemic control, revealing optimal periods and impacts on epidemic duration and fatality rates.

Contribution

It introduces a conjectural setup to evaluate lockdown effects using a stochastic SEIR model across multiple scenarios, highlighting optimal lockdown timing.

Findings

Early lockdown reduces infection spread but prolongs epidemic duration.

Late lockdown minimizes total epidemic duration.

Lockdown timing significantly affects case fatality rate, ranging from 7.55 to 8.02.

Abstract

In a pandemic like Covid-19, there are many countries of lower-earning cannot provide a complete locked-down within the duration of the detected case. The locked-down may result in famine throughout the region of underdeveloped countries after the outbreak. So, a conjectural setup of an epidemic has been studied by applying specific period of locked-down (30 days) in 5 different scenarios. The stochastic approach to the SEIR (Susceptible, Exposed, Infected and Recovered) model has been used to evaluate the dynamics and the effects of locked-down. It is observed that there exist a suitable period to apply locked-down where more susceptible escape from the infection. The effect of the early (as soon as the infected case detected) and late (with respect to the estimated peak of detected cases for no locked-down) implementation of the locked-down has also been studied and found that the late implementation of locked-down will take the least time to end the epidemic. The CFR (Case Fatality Rate) has also been found to be varied from 7.55 to 8.02 for all the considered scenarios.