Table of contents
●Basic Concept and Function / Model Overview of MultiLayer-MultiAgent Model
●Progress
●Report of the current calculation parameters and calculation results
●Appendix
○Generation logic of each layer of MLN
Basic Concept of MultiLayer-MultiAgent Model
●Model for observing the macroscopic effects of microscopic human activities
✔️Macro models such as the SEIR model cannot detect infection routes or risk points through people's micro activities
✔️By using multiple layers, it is possible to simulate complex events while reducing the number of parameters compared to a single layer network, because basic statistics are set and calculated for each layer instead of each node
✔️Layers can be freely added or removed
✔️Infection rate and economic effect can be defined per contact for each layer, and contact thinning is also possible
●Interactions between different activities can be observed by modeling them as different layers and overlapping them
✔️Contexts are assumed such as family, work, neighborhood community, school, travel, and event participation
✔️The number of reproductions is fluid and changes each time the model is changed, but the layer (= people's activities / context) is universal and can be used 10 or 50 years later
●Policy-based external operations for each Layer can be performed
✔️Workplace Layer: Thinning out according to guidelines from Keidanren and supervisory authorities, etc.
✔️School Layer: Thinning out by guidelines from Ministry of Education, Culture, Sports, Science and Technology, Ministry of Health, Labor and Welfare, etc.
✔️Travel & Events Layer: Some thinning out by declaring a state of emergency, etc.
Model Overview
●Data
✔️Using artificial synthetic data provided by Dr. Murata (Kansai University) (information such as household, age, gender, occupation, latitude, and longitude can be used)
●Infection transmission model
✔️A multi-agent based SEIRS model after the effect of vaccination was adopted
✔️The degree of I can be broken down into light and severe conditions
✔️Expanding economic loss calculation due to measures for serious illness and death is also under consideration.
●The model allows for adjustment (thinning out) of the coupling relationship of the edges of each layer
✔️See Appendix for rules on joining relationships for each layer
✔️Can be thinned out, not all edges connected
✔️Thinning rate can be adjusted on a layer-by-layer basis
✔️This is done taking into consideration state of emergency, school closures, guidance to companies on telework rate targets, etc.
✔️Economic effect through thinning can also be expandable
●Vaccination
✔️Probabilistically determine to vaccinate or not at each node
✔️It is possible to set a rule to reduce the transition probability to E of a node in the state of S by ▲X% by vaccination
✔️Assuming to have expansion such as vaccination with a certain priority based on information on age and latitude / longitude from Dr. Murata
New Infections when Infection Parameters (Greeks) are Fixed
[[premise of calculation]]
・ 5,000 households (about 10,000 agents), Random seed 1
・ [W-m0 relationship] family: fully combine, workplace: W=3, m0=1, school: W=4, m0=2, neighborhood: W=4, m0=2, travel events: randomly with two people
・ [Infection (Greeks) parameter] As shown at 3 of the list of infection parameters in Appendix
Accumulative Infections when Infection Parameters (Greeks) are Fixed
[[premise of calculation]]
・ 5,000 households (about 10,000 agents), Random seed 1
・ [W-m0 relationship] family: fully combine, workplace: W=3, m0=1, school: W=4, m0=2, neighborhood: W=4, m0=2, travel events: randomly with two people
・ [Infection (Greeks) parameter] As shown at 3 of the list of infection parameters in Appendix
Number of Serious illness when Infection Parameters (Greeks) are Fixed
[[premise of calculation]]
・ 5,000 households (about 10,000 agents), Random seed 1
・ [W-m0 relationship] family: fully combine, workplace: W=3, m0=1, school: W=4, m0=2, neighborhood: W=4, m0=2, travel events: randomly with two people
・ [Infection (Greeks) parameter] As shown at 3 of the list of infection parameters in Appendix
Number of Deaths when Infection Parameters (Greeks) are Fixed
[[premise of calculation]]
・ 5,000 households (about 10,000 agents), Random seed 1
・ [W-m0 relationship] family: fully combine, workplace: W=3, m0=1, school: W=4, m0=2, neighborhood: W=4, m0=2, travel events: randomly with two people
・ [Infection (Greeks) parameter] As shown at 3 of the list of infection parameters in Appendix
