Non Pharmaceutical Interventions for Optimal Control of COVID-19

Abstract

Background and objective: The outbreak of the current pandemic begun from the first individual of a 55-year old from Hubei province in China, the disease instigated by the new coronavirus spreading across the world. Scientists presently speculate this coronavirus, SARS-CoV-2, originated in a bat and by one way or another jumped to another creature, potentially the pangolin, which at that point gave it to people. The ailment is currently spreading between individuals with no animal delegate. Researchers are struggling to follow the infection back to where it started to become familiar with its spread. In the event that, for example, specialists can locate the soonest cases, they might have the option to distinguish the creature have where the infection hides. In March and April 2020, researchers detailed that this virus created normally. Coronavirus has been become of the serious global phenomena in the recent years and has negative effects in the entire world health and economy. The virus is believed to have been associated with a host animal which human contracted. Subsequently, human-to-human infection began. Through migration as humans have become complex with easy mobility the disease has traveled to the entire continent. Now, numerous scientist are going on in the hope of obtaining medication and vaccination to prevent the spread of the disease and mortality of the disease. It is important that we obtain quantitative and qualitative information about the etiology of this disease which is crucial. Mathematical modeling is capable of providing qualitative information on many parameters that guides the decision making of health practitioners. In this work we focus the optimal control of COVID-19 with the help of Non Pharmaceutical Interventions (NPIs). To find the role of factors/parameters in the transmission of the syndrome we find R₀; the ratio of reproduction for the proposed model.

Methods: To find the role of parameters in the transmission of the syndrome we find R₀; the ratio of reproduction for the proposed model. On the basis of sensitivity indices of the parameters we apply Non Pharmaceutical Interventions(NPIs) to control the sensitive parameters and hence formulate the optimal control mode. With the help of Hamiltonian and Lagrangian we minimize the density of contaminated stuff and infected human population.

Results: We focus the optimal control of COVID-19 with the help of Non Pharmaceutical Interventions(NPIs). On the basis of sensitivity indices of the parameters we apply Non Pharmaceutical Interventions(NPIs) to control the sensitive parameters and hence formulate the optimal control model. The major NPIs are, STAY HOME, SANITIZER (wash hands), EARLY CASE DETECTION (PCR Test) and FACE MASK. These NPIs helps in mitigation and reducing the size of outbreak of the disease.

Conclusion: We check the existence of the optimal solution for the system. At the end, Using matlab we produce numerical simulations for validation of results of control variables. The results demonstrate that if there is no control (variables/interventios), 900 out 1000 susceptible individuals may be infected (exposed) in very short period. As such a circumstances no agency fighting against COVID-19 could be successful due to its limited resources.

Keywords: Basic reproduction number; Mathematical model; Next generation matrix; Novel coronavirus; Optimal control; Pontryagin’s Maximum Principle; Sensitivity analysis.

Fig. 1

The fig represents the effect of interventions/control variables on susceptible population.

Fig. 2

The behavior of exposed class with and without control. The gap between the graphs denotes the effect of interventions.

Fig. 3

The effect of interventions on the density of symptomatic infectious class.

Fig. 4

The fig represents the density of the quarantine class with and without control variables.

Fig. 5

The fig represents the burden of patients in hospitals with and without control variables.

Fig. 6

The fig represents the recovered human population with and without interventions.

Fig. 7

The fig represents the effect of interventions on asymptomatic human class. The difference of the graphs denotes the effectiveness of control variables.

Fig. 8

The fig represents the effect of interventions upon the density of contaminated stuff.

Fig. 9

The fig represents the intervention ‘STAY HOME’.

Fig. 10

The fig represents the intervention ‘FACE MASK’.

Fig. 11

The fig represents the intervention ‘QUICK CASE DETECTION’ with help of laboratory tests.

Fig. 12

The fig represents the intervention ‘REGULAR USE OF SANITIZER’.