Background
Methods
Probability distribution function of influenza transmission
Influential factors needs to be considered
Passenger sources partition
Immunity difference
Immunity phases | Infants and juveniles(<19) | Adults(20–60) | Elderly people(>60) |
---|---|---|---|
Infection rate(β
i
) | β1 = 37.56% | β2 = 8.37% | β3 = 16.25% |
Social relation structure
Model modifications
Agent-based SEIR model
Hierarchical structure of personal contact network model
Results
Experimental groups and initialization
Assumptions of influential factors
Passenger sources partition assumptions
Scene | Passenger source partition | Passenger number |
---|---|---|
Departure | Affected areas | 16 |
Arrival | Affected areas | 16 |
Immunity difference assumptions
Social relation structures assumptions
Classification of passengers | Passenger number | Spatial distancesl/m | Intimate relationships coefficientω |
---|---|---|---|
Relatives | uniform (2,3) | 0 ~ 0.55 | 2.6 |
Friends | uniform (2,5) | 0.55 ~ 0.8 | 1.8 |
Colleagues | uniform (2,8) | 0.8 ~ 1.2 | 1.5 |
Individuals | 1 | 1.2 ~ 3.6 | 0 |
Hierarchical structure of personal contact network model in terminal
Terminal plane structure and passengers’ flow setting
The parameters of passengers’ flow
Procedures | Time (unit: min) |
---|---|
Domestic check-in | Uniform(2,5) |
International check-in | Uniform(3,8) |
Security check | Uniform(3,10) |
Immigration inspection | Uniform(1,2) |
Customs inspection | Uniform(1,5) |
Inspection and quarantine | Uniform(1,2) |
Waiting for boarding | Uniform(15,90) |
Baggage claim | Uniform(5,8) |
Discussion
Hierarchical network properties
Influences on influenza transmission
Without considering the three factors | Considering passenger source partition | Considering immunity difference | Considering social relation structure | Considering all the three factors | |
---|---|---|---|---|---|
Departure | 1052 | 1411 | 1016 | 1207 | 1561 |
Arrival | 358 | 430 | 344 | 564 | 683 |
Main infected area
Intervention strategies
Conclusions
Symbol | Name | Value | Source |
---|---|---|---|
f(t) | Transmission probability density function | - | Calculated by Eq. (3) |
t
| Valid contact time | - /min | Social relation pattern |
β
i
| Infection rate of different immunity phase | β1 = 37.56%, β2 = 8.37%, β3 = 16.25% | Dr. Huang SQ’s doctoral dissertation |
F(t) | Probability distribution function | - | Calculated by Eq. (4) |
α
| Layer of hierarchical network | 0, 1, 2, 3 | Structure of personal contact network |
n
| Node number | - | Structure of personal contact network |
{n
i
} | Set of all unit model | - | Structure of personal contact network |
C
| Clustering coefficient | 0 ~ 1 | Figure 5 (b) |
M
| Number of basic unit model | - | Calculated by Eq. (5) |
N
| Number of nodes in a personal contact network | - | Structure of personal contact network |
n
0
| Number of nodes in all the unit models | - | Structure of personal contact network |
W
| Newly constructed network | - | Calculated by Eq. (6) |
U
| All nodes in network | - | Calculated by Eq. (6) |
V
| All edges in network | - | Calculated by Eq. (6) |
u
i
| Node set in a unit model i | - | Structure of personal contact network |
v
i
| Edge set in a unit model i | - | Structure of personal contact network |
v
new
| Newly added edges | - | Structure of personal contact network |
n
x
| Number of unit models that compose the higher layer network | - | Structure of personal contact network |
F(y) | Probability distribution function of adding new edge | - | Calculated by Eq. (7) |
d
i
| Actual degree of individual i in layer α | - | Characteristic of network and structure of personal contact network |
d
i max
| Maximum degree of links that individual i owns in layer α − 1 | - | Characteristic of network and structure of personal contact network |
l
| Spatial distances | 0 ~ 0.55, 0.55 ~ 0.8, 0.8 ~ 1.2, 1.2 ~ 3.6 | Social relation pattern |
ω
| Intimate relationships | 2.6, 1.8, 1.5, 0 | Social relation pattern |
p(k) | Degree distribution | 10−6 ~ 10−1 | Figure 5 (a) |