For protecting the infection process, we have introduced 6 types of filter concept to block the infection process statistically. To shows the Infection mechanism behind the policies, we simulated a city where 10,000 people are acting depending on its roles and the infection event happens in the activities. 30 minutes is treated as 1 tick in the simulation. By using the agent-based simulation model, we can express the intervention policies against the pandemic. We have simulated 12 types of policies. The simulation results show that the "Filter Density Index(FDI)" as a combination of policies has a bifurcation point and that if the FDI can be controlled below a certain level, the infection can be suppressed. However, the value of the bifurcation point itself cannot be determined. Instead, we propose that a dynamic social infection control mechanism should be introduced to a society, based on two types of surveillances as policy implementation level and spreading level of the infection.

1. Hiroishi Deguchi
Tokyo Institute of Technology
@wideexit
deguchi@dis.titech.ac.jp
Statistical & Multi-objective
Social Control of Infection
Process of COVID-19
Summary
for working people
against the pandemic
Ver 0.6 20200320

2. For protecting the infection process, we have introduced 6 types
of filter concept to block the infection process statistically
To shows the Infection mechanism behind the policies, we
simulated a city where 10,000 people are acting depending
on its roles and the infection event happens in the activities.
30 minutes is treated as 1 tick in the simulation. By using the
agent-based simulation model, we can express the
intervention policies against the pandemic. We have
simulated 12 types of policies.
The simulation results show that the "Filter Density
Index(FDI)" as a combination of policies has a bifurcation
point and that if the FDI can be controlled below a certain
level, the infection can be suppressed.
However, the value of the bifurcation point itself cannot be
determined. Instead, we propose that a dynamic social
infection control mechanism should be introduced to a
society, based on two types of surveillances as policy
implementation level and spreading level of the infection.
Summary

3. Decomposition of Infection Process
Contamination
of Place by an
infected person
Excretion of
Virus in a place
Contamination of a Person
by a contaminated place
Contaminated
Person
Infection of
the Person
by the
contaminat
ed body
Contaminated
Place
Infected Persoon
We decompose the infection process
into three parts such as (1)
contamination of place by an infected
agent, (2) contamination of an agent by
a contaminated place and (3) infection
of the agent by the contaminated body
1
2
3

4. Personal
Excretion filter
such as Mask
Sterilization of
place
Spatial Density
Control Policy
PPE(Personal
Protective
Equipment)
Personal
Sterilization Policy
such as washing
hand
Filter Model for Protecting Infection Process
(1)
(2)
(3)
(4)

5. Vaccination
Policy
(5)
Cluster
Closing
Policy
We distinguish 6 types of infection
protection policies as infection protection
filters. In the statistical process of infection,
the filters intervene in the possibility of
contamination and infection events.
(6)
(5)
(6)

6. Our
Proposed
Conceptual
Chart of
Infection
Control
Policies by
the
combination
of 6 filters
Vaccination
Start
Threshold of
Medical Resource
for Severe Patients
Threshold of
StartingClosing Policy
Threshold of Strong
Closing Policy
Time
Severe Patients
in Hospital
Total Number of
Infected Persons
Time
Finish
Infection
Process
Strong
Interventions
Strong
Interventions
Strong
Interventions
Strong Interventions
by Filter Policies under
the execution serveillance

7. 5 Days
2m
1
3s
4m
0
Infection
20.8
0.2
4c
5
3m
5 Days
1
p23s
=1-P23
p3s4c
p3s4m
=1-P3S4C
p4cd
5 Days
3 Days
3 Days
1
1
1
3 Days
5 Days
3 Days
p12m
=1-p12
p12
p4c4m
=1-p4cd
Hospital L1
Hospital L2Virus
Excretion
p23
Hospital L3
Not Detected
asymptomatic infection
3
3 Days
Combination of Models
Human Activity Model
Disease Stage Model
Stage Transition Model
Infection Model
Office Area
School
Hospital
Traffic
Tomb
Home Town
Virtual
Density
Control
Excretion
Control
Isolation &
Treatment
Policy
30 minutes
is a tick
Excretion
Control
Personal
Contamination
Protection
Personal
Contamination
Protection
Disinfection
Control
Disinfection
Control
Vaccination
Policy
Multi-Aspect Agent
Based Model by SOARS
Filter Model:
Intervention AspectDisease State
Transition Aspect
Human Activity
Model Aspect
City Structure
Model Aspect
Cohort & Family Structure
Model Aspect
1
2 3 4
5
Multi-Aspect Agent Based Micro Modeling

8. Multi Scenario Simulation of
COVID-19 infection process
and the interventions for
the process
Brief Sketch of the Results
See the details of graphical result in Appendix B
You can download the simulation program
from <https://bit.ly/2vCbm7l> and run the
scenarios by yourself.
See Appendix A

9. Depending on the intervention policies, the
infection processes are different!
In our
model, the
infection
will finish
after half of
the
population
has infected
S1(1)
S4(1)
S3(1)
S5(1)
Not Infected
Infected
Vaccinated

10. Infection flow shows several peaks might
happen. Even if the infection process once has
stopped, it will restart in the pandemic
situation until enough vaccination has done.
S1(1)
S4(1)
S3(1)
S5(1)
Dead
Patient over state 2
Patient over state 1
Patient of State 1
Patient of Severe or Critical

11. 0
2
4
6
8
10
12
14
16
1
150
299
448
597
746
895
1044
1193
1342
1491
1640
1789
1938
2087
2236
2385
2534
2683
2832
2981
3130
3279
3428
3577
3726
3875
4024
4173Patient Severe + Critical
S4(1)
0
10
20
30
40
50
60
70
80
1
151
301
451
601
751
901
1051
1201
1351
1501
1651
1801
1951
2101
2251
2401
2551
2701
2851
3001
3151
3301
3451
3601
3751
3901
4051
4201
Patient Severe + critical
S1(1)
We have to prepare “ventilator beds” for patients of
Severe or Critical situation. The simulation shows
the required number per 10,000 population.
Even if the
infection process
once has
stopped, the
infection process
will restart in the
pandemic
situation when
the protection
policies become
weak
0
5
10
15
20
25
1
150
299
448
597
746
895
1044
1193
1342
1491
1640
1789
1938
2087
2236
2385
2534
2683
2832
2981
3130
3279
3428
3577
3726
3875
4024
4173
Patient Severe + Critical
S3(1)
0
1
2
3
4
5
6
7
1
145
289
433
577
721
865
1009
1153
1297
1441
1585
1729
1873
2017
2161
2305
2449
2593
2737
2881
Patient Severe + Critical
S5(1)
Patient of Severe or Critical

12. Simulation Result & FDI of 12 Scenarios
D D 7 F 425 5 A 5 A ( 5 A 0N
18 52
I 1 E6 DMF
1E D 6 DMF
3P D 1 E
((%)(+ (+ (& )( (
18 52 &
I 1 E6 DMF
1E D 6 DMF
3P D 1 E
) %+&& (+ ) ( )&
18 52
I 1 E
1E D 6 DMF
3P D 1 E
) % ) (( ( %+
18 52 +
I 1 E
1E D 6 DMF
% + (+ & (
18 52 .
I 1 E
1E D
% + (+ + - %+
18 52
I 1 E6 DMF
1E D 6 DMF
-)%&& (+ -+ . . .
18 52
I 1 E6 DMF
1E D
-)%&& (+ +-( ) - %+
18 52 )
I 1 E
1E D 6 DMF
- %). & (+ )
18 52 -
I 1 E
1E D
- %). ) ) ()&&
18 52 7 9 ED 7 D D . %)&(+ . + (+ . +
18 52 (
7 9 ED OD C
D D
. %)&(+ + +-
18 52 (
1E D
C E && AAD
. %)&(+ )) + )) ))++%+

13. Twelve Scenarios of COVID-19 Infection Process
Simulation show that there exist the bifurcation
point for protection policies
0
1000
2000
3000
4000
5000
6000
0 10 20 30 40 50 60 70 80 90 100
Infected Avarage
FDI
When FDI becomes smaller, then Infection Protection becomes stronger
How can we control
protection policies
under the
bifurcation point?
Bifurcation point of
the structural
parameter(FDI)
Each dot of
the graph
shows the
average of two
simulations of
each scenario
We have
shown the
existence of a
bifurcation
point of FDI.
But it is
impossible to
show the
point
numerically

14. Two
Purpose for
Intervention
Minimize
the death in
the society
Maintain
social functions
in the society
Multi Objective Constraint Satisfaction Problem
Disease
State
Surveillance
Execution of the
policies
Execution
Level
Surveillance
Medical
Resource
Surveillance
Combination
of 6 protection
policies as
alternatives
DM & Consensus
Building for Intervention
State
Estimation
Execution
Management
Mechanism model
by ABM
State
Feedback
Execution
Feedback
Evidence based policy making with mechanism model
1
2
3
4
567
Social Implementation of Feedback System in a Society
Quick Response

15. How to Observe “Policy Execution
Level” of six filter policies as an
Execution Management System
How many people
wear a mask in public
space or in traffic or
in school or in office
How many
places the
attenuation is
done properly.
How PPE is
used properly
at hospital?
How many places
Spatial Density
Policy has
introduced
properly
How many
people
washing hand
in school or
in office or in
family
How many people
are vaccinated when
the vaccination has
started

16. Appendix A
How to run COVID-19
Simulation Model
!16

17. How to download and run the COVID-19
pandemic Simulation Program
This COVID-19 pandemic simulation program was
created on SOARS(Spot Oriented Agent Role
Simulator) that is developed by Deguchi laboratory.
GitHub of SOARS is as follows.
https://github.com/degulab/SOARS
You can download execution program of
the simulation on JAVA(jar file) from the
following URL
https://drive.google.com/file/d/
11KF5FZC6cNRliozggl0YH4TBC-cVkFg-/
view?usp=sharing
or https://bit.ly/2vCbm7l
Please try the simulation by yourself!!
!17

18. (1) Select a
Scenario
(2) Run the
Simulation
!18

19. (3) There are three
windows such as two
graphic windows and
Log window.
!19

20. (4) You can look the
collected logs of the
simulation
!20

21. Appendix F
How to protect infection inside
Hospitals that can not be closed
The
importance
of gray zone
control
Red
Zone
Gray Zone
Yellow Zone
Green Zone
!21

22. Standard PPE
treatment at yellow
zone at a hospital
Green Zone
Yellow Zone
Red
Zone
!22

23. Red
Zone
Gray Zone
Yellow Zone
Green Zone
Safe zone of
uninfected persons
Attach and detach zone
of PPE(Personal
Protective Equipment
Suspected persons
should be treated
at “Gray Zone”,
including
COVID-19
infected but not
detected persons
and not infected
but suspected
persons
COVID-19 infected persons
are an isolation ward
Gray zone control is not referred to
explicitly. But it is well-recognized by working
doctors in a hospital. Gray zone is the most
dangerous zone where cross-infection
between an infected but not detected person
and a not infected person.
!23

24. There are many Gray zones inside a hospital. It is critical
to control the gray zones for avoiding cluster infection
inside hospital.
1) Zoning for suspected persons as "Gray Zone"
2) Management of the moving pattern of stakeholders
such as patients, suspected persons, nurses, doctors and
clinical engineers among red zone, yellow zone, green
zone and gray zones inside a hospital
3) Spacial zoning is the best way for suspected persons,
e.g., waiting rooms or wards in a hospital. Besides, it is
hard to apply spacial zoning for CT or other inspection
equipment. Then time zoning the second-best way.
4) Infected persons can be hospitalized together inwards
in the red zone. But suspected persons should be treated
separately to avoid cross-infection. It is hard to realize!
!24