5 The Dual Impact of Lockdown on Curbing COVID-19 Spread …
115
figures as ILO (International Labour Organisation) reports, only about 18 per cent
belong to the salaried class
1 ; so for 467 million belonging to the self-employed class
and the non-salaried class (including contractual and non-contractual and especially,
the migrant labourers), the prolonged lockdown is becoming far more threatening
than the danger of being affected with COVID-19 and many might die from hunger,
fatigue, suicides etc.,—a question of life versus livelihood as the possibility of layoff
looms large.
Susceptible-Infected-Recovered (SIR) model is an important tool to understand
the coronavirus transmission-based statistical simulations. In this work of ours, we
have taken the window of daily infected counts from 2 March 2020 to 31 June
2020 and fitted the Susceptible-Infectious-Quarantine-Recovered (SIQR) model into
the data. We have introduced a constant factor in this model which will measure
the growth of COVID-19 infected cases due to any accidental mass gathering. In
addition, we have created a situation-based modeling to create the results. Mainly,
two scenarios have been taken into account. In the first scenario, we have assessed
the growth of coronavirus without any lockdown and social distancing and in the
second case, we have assessed the same with lockdown and social distancing for
comparison purposes.
The paper is structured as follows. Section 5.2 contains the Literature Review. In
Sect. 5.3, we have briefly described our proposed SIQR model (after the incorporation
of a constant) along with the numerical analysis and simulation results regarding the
spread of coronavirus in India under two circumstances viz. with lockdown and social
distancing and without social distancing and lockdown. Section 5.3, contains the
AQI forecasting using Time Series Decomposition and using deep learning models.
Section 5.4 presents a correlative study of lockdown and AQI across three scenarios
viz. With no such COVID-19 scenario, what would be under lockdown and finally
after lockdown scenario?
5.2 SIQR Dynamic Model
The study of COVID-19 spread can be executed by the fundamental rules of SIR
modeling. The model was introduced by Kermack and McKendrik [2]. In this
modeling approach, they divide the entire population into partial groups and study
the contagion and spread of the disease across the groups using the parameter of the
rate of change of the size of these groups. For our case, the basic model has been
improvised by assumptions to accommodate the spread of the virus and different
GDP growth rate simulations by bringing in more parameterised restrictions for
better results in the Indian context [3, 4].
115
figures as ILO (International Labour Organisation) reports, only about 18 per cent
belong to the salaried class
1 ; so for 467 million belonging to the self-employed class
and the non-salaried class (including contractual and non-contractual and especially,
the migrant labourers), the prolonged lockdown is becoming far more threatening
than the danger of being affected with COVID-19 and many might die from hunger,
fatigue, suicides etc.,—a question of life versus livelihood as the possibility of layoff
looms large.
Susceptible-Infected-Recovered (SIR) model is an important tool to understand
the coronavirus transmission-based statistical simulations. In this work of ours, we
have taken the window of daily infected counts from 2 March 2020 to 31 June
2020 and fitted the Susceptible-Infectious-Quarantine-Recovered (SIQR) model into
the data. We have introduced a constant factor in this model which will measure
the growth of COVID-19 infected cases due to any accidental mass gathering. In
addition, we have created a situation-based modeling to create the results. Mainly,
two scenarios have been taken into account. In the first scenario, we have assessed
the growth of coronavirus without any lockdown and social distancing and in the
second case, we have assessed the same with lockdown and social distancing for
comparison purposes.
The paper is structured as follows. Section 5.2 contains the Literature Review. In
Sect. 5.3, we have briefly described our proposed SIQR model (after the incorporation
of a constant) along with the numerical analysis and simulation results regarding the
spread of coronavirus in India under two circumstances viz. with lockdown and social
distancing and without social distancing and lockdown. Section 5.3, contains the
AQI forecasting using Time Series Decomposition and using deep learning models.
Section 5.4 presents a correlative study of lockdown and AQI across three scenarios
viz. With no such COVID-19 scenario, what would be under lockdown and finally
after lockdown scenario?
5.2 SIQR Dynamic Model
The study of COVID-19 spread can be executed by the fundamental rules of SIR
modeling. The model was introduced by Kermack and McKendrik [2]. In this
modeling approach, they divide the entire population into partial groups and study
the contagion and spread of the disease across the groups using the parameter of the
rate of change of the size of these groups. For our case, the basic model has been
improvised by assumptions to accommodate the spread of the virus and different
GDP growth rate simulations by bringing in more parameterised restrictions for
better results in the Indian context [3, 4].