Elsevier

Chaos, Solitons & Fractals

Volume 138, September 2020, 109939
Chaos, Solitons & Fractals

Predicting optimal lockdown period with parametric approach using three-phase maturation SIRD model for COVID-19 pandemic

https://doi.org/10.1016/j.chaos.2020.109939Get rights and content

Highlights

  • The very first model to predict the minimum optimal time of the lockdown.

  • Deliberates salient features like silent carriers, sociability of newly infected person and unregistered deaths of coronavirus infectious people along with SIR model.

  • Based on the awareness and sustainability of disease, the number of suspected person varies with respect to time of spreading of virus. Hence, three phases are formed to define the suspected rate as it will not grow exponentially all the time.

  • At first Phase, when the awareness of newly discovered virus is at initial phases, the suspecting rate will grow exponentially. Suspected rate depends on sociability of infected person.

  • Second Phase is during lockdown when the social distancing is followed. In this phase, death cases are more as number of current infected person are at peak. Simultaneously, the number of recovered person per day will increase.

  • Third Phase is when there is reduction in number of active cases. Number of suspected cases will reduce depending upon the testing speed of medical team.

  • In order to calculate the optimal lockdown time Topt, the approach of proposed model is to find a situation when the number suspected people starts to reduce w.r.t. time, number of infected people increases for a while but start reducing with respect to time, and also the number of recovered people rises w.r.t. time.

  • The model is tested on China data and is efficient enough to propose a model very close to their actual figures of infected people, recovered people, died and active cases. The model predicts the optimal lockdown period as 73 days for China which is very close to their actual lockdown period (77 days).

  • Also, the model is implemented to predict the optimal lockdown period of India and Italy.

  • The programming part is done in C++ language with Linux OS.

Abstract

This paper proposes a three-phase Susceptible-Infected-Recovered-Dead (3P-SIRD) model to calculate an optimal lockdown period for some specific geographical regions that will be favorable to break not only the transmission chain but also will help country’s economy to recover and support infrastructure in a fight against COVID-19. Proposed model is novel since it additionally includes parameters i.e. silent carriers, sociability of newly infected person and unregistered died coronavirus infected people along with the infection rate, suspected rate and death rate. These parameters contribute a lot to figure out the more clear model, along with essential parameters. The model takes the testing rate of suspected people into consideration and this rate varies with respect to phase of the epidemic growth. Proposed 3P-SIRD model is divided into three-phases based on the awareness and sustainability of disease. Time is divided into different periods as rate of infection and recovery fluctuates region to region. The model is tested on China data and is efficient enough to propose a model very close to their actual figures of infected people, recovered people, died and active cases. The model predicts the optimal lockdown period as 73 days for China which is very close to their actual lockdown period (77 days). Further, the model is implemented to predict the optimal lockdown period of India and Italy.

Keywords

COVID-19
SIRD Model
Pandemic
Lockdown
Silent Carriers

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