令和5年度 電気・電子・情報関係学会 四国支部連合大会 講演論文集＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿
2023 Shikoku-Section Joint Convention Record of the Institutes of Electrical and Related Engineers

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Research on The Eﬀects of Refraining from Going Out in The Spread ofCOVID-19 by Using a Multi-Agent Simulation
Masaki SAITO

Yoko UWATE
Yoshifumi NISHIO( Tokushima University)

1. Introduction

In addition, the transmission of infectious diseases isshown in the flowchart in Fig. 2. In this study, it is considered that the immunity is impaired due to physical inactivity when not going out. Humans are about 60% more likely
to contract an infectious disease when they are sedentaryfor 12 weeks than when they walk regularly. Therefore, inthe simulation of not going out, the infection rate is 10%
higher when people do not go out for two weeks.

In the past, governments have taken measures such as
lockdowns and requests for people to refrain from going out
when the number of people infected with COVID-19 increased. As a result of these measures, the number of new
infected people was reduced, but the virus was not completely eliminated, and the number of new infected people
increased again, the economy stagnated, and these measures became one of the reasons for the confusion and physical inactivity. This study focuses on the relationship between physical inactivity and infections and compares thenumber of infected people in the simulation of refraining
from going out as in the past and that of not refraining
from going out by using a multi-agent simulation.

2. Multi-Agent Simulation
The multi-agent simulation (MAS) is based on the ideathat programs do exhibit behaviors entirely described by
the program instructions. It is possible to simulate an artificial world inhabited by interacting processes, by relating
an individual to a program. It is also possible to simulate by transposing the population of a real bio system toits artificial counterpart in which particular hypotheses canbe explored by repeating experiments. Each organism of
the population is represented as an agent whose behavior isprogrammed with all the required details.

Figure 2: Flowchart of the transmission of infectious diseases.

4. Results
The results of the 50 simulations showed that the number of all positive cases was 137.8 in the case of refraining
from going out and 142.2 in the case of not refraining fromgoing out, and the number of new infected people at thepeak was 48.92 in the case of refraining from going out and51.68 in the case of not refraining from going out. Thereis little diﬀerence in these items between the two simulations. However, the peak period was 23.88 days later in thecase refraining from going out and 20.02 days later in thecase not refraining from going out, and the number of new
infected people after two months was 27.04 in the case refraining from going out and 8.46 in the case not refraining
from going out. Therefore, the peak period is earlier whenpeople do not refrain from going out, but after two months,
the virus is reduced considerably.

3. Proposed Model
Figure 1 shows two virtual areas: the area on the left is
the home or the area near it, and the area on the right is
the workplace, school, or any other place where people goout and about. On weekdays, 80% of people are active for 8hours in the right area (work or school) and spend the restof the time in the left area (home). On holidays, people
move to the right area for 24 hours to exercise, shop, ortravel. However, on holidays, 60% of people go out if they
do not refrain from going out, while only 30% of people
go out if they do. The number of people is 5,000 and thesimulation period is 2 months.
The scatter plot shows the agents, and the movement of
the agents and the infection situation can be recognized asa video. The blue points are the susceptible agents.Eachsimulation is repeated 50 times and the average value iscalculated.

4. Conclusion
In this study, the number of people infected with COVID19 was compared between going out and refraining fromgoing out. Then, two types of simulation models were created by MAS. One is a simulation in which people do notrefrain from going out and people go out freely. The otheris a simulation in which people refrain from going out andthe infection rate increases due to physical inactivity. As aresult, the peak period is earlier when people do not refrainfrom going out, but the virus is considerably reduced after
two months.

Figure 1: Two virtual areas. The left area has 5,000 agents.

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