A Simulation Study of Coronavirus as an Epidemic Disease Using Agent-Based Modeling

Abstract

At the end of 2019, the world faced the novel coronavirus, and with it fear of economic collapse and mass fatalities. Simulation systems can be used to monitor the behavior of the virus. Simulation provides an abstract representation of reality by conveying details and characteristics of reality in a simple application. One of the most important ways to simulate is agent-based modeling. The health information professional plays an important role in developing these models. In this research, we simulate the spread of COVID-19 in a region restricted to a population with specific demographic characteristics and social relationships. This study aims to clarify the effects of preventative techniques that suppress the spread of epidemics, such as quarantines, social distancing, and reduced mass transit.

Keywords: COVID-19; SIR model; agent-based modeling; coronavirus; epidemic diseases.

Figure 1

Coronavirus cases distribution around the world May 22, 2020

Figure 2

The initial environment.

Figure 3

The chart of our proposed model.

Figure 4

The flow chart of our proposed model

Figure 5

The behavior of SIR model used in Khalil et al.

Figure 6

The original behavior of SIR model¹¹

Figure 7

The behavior of our proposed model

Figure 8

(a) SIR plot, (b) example run of the first scenario without any controlling procedures and without considering any relationships between people or traveling between the two regions

Figure 9

(a) SIR plot, (b) example run of the second scenario of the model with average isolation tendency = 10%

Figure 10

(a) SIR plot, (b) example run of the third scenario of the model with an average hospital going tendency = 10%

Figure 11

(a) SIR plot, (b) example run of the fourth scenario of the model with adding a cured chance = 20%

Figure 12

(a) SIR plot, (b) example run of the fifth scenario of the model with employing the paramedics = 2 persons (a) LINKs option without controlling procedures: to the left the SIR plot, to the right a sample run. (b) LINKs option with controlling procedures: to the left the SIR model, to the right a sample run.

Figure 13

SIR plots and example runs of the sixth scenario (a) LINKs option without controlling procedures: to the left the SIR plot, to the right a sample run. (b) LINKs option with controlling procedures: to the left the SIR model, to the right a sample run.

Figure 14

aTRAVEL option with LINKS option and controlling procedures: to left the SIR plot, to the right a sample run Figure 14b TRAVEL option without LINKS option and controlling procedures: to left the SIR plot, to the right a sample run Figure 14c TRAVEL option without LINKS option and without controlling procedures: to left the SIR plot, to the right a sample run