Epidemic spread dynamics in multilayer networks: Probing the impact of information outbreaks and reception games
Chaos An Interdisciplinary Journal of Nonlinear Science,
Год журнала:
2025,
Номер
35(3)
Опубликована: Март 1, 2025
The
co-evolution
of
epidemic
and
information
spread
within
multilayer
networks
is
a
current
hot
topic
in
network
science.
During
outbreaks,
the
accompanying
exhibits
both
outbreak
reception
game
behaviors;
yet,
these
complex
phenomena
have
been
scarcely
addressed
existing
research.
In
this
paper,
we
model
outbreaks
using
activated
individuals
who
transmit
messages
to
their
neighbors,
while
also
considering
behaviors
receivers.
By
focusing
on
two
factors,
establish
featuring
games.
Employing
microscopic
Markov
chain
method,
analyze
propagation
dynamics
derive
thresholds,
corroborating
results
with
Monte
Carlo
simulations.
Our
findings
indicate
that
suppress
whereas
increased
costs
promote
spread.
Smooth
dissemination
further
inhibits
transmission
epidemic.
Additionally,
observe
heterogeneity
structure
between
virtual
physical
layers
reduces
ultimate
scale
infection,
layer
exerting
more
substantial
influence.
These
insights
are
crucial
for
elucidating
co-evolutionary
mechanisms
developing
effective
prevention
control
strategies.
Язык: Английский
Information-Disease Coupled Propagation Dynamics Based on the UANU-SIS Model
Modeling and Simulation,
Год журнала:
2025,
Номер
14(01), С. 721 - 733
Опубликована: Янв. 1, 2025
Язык: Английский
Negative public opinion and minority-driven social change in hypergraphs
Chaos An Interdisciplinary Journal of Nonlinear Science,
Год журнала:
2025,
Номер
35(3)
Опубликована: Март 1, 2025
The
phenomenon
where
a
committed
minority
overturns
established
social
norms,
frequently
witnessed
in
revolutions
and
elections,
has
drawn
extensive
attention
as
it
powerfully
showcases
the
profound
influence
of
strong
personal
convictions.
In
order
to
unravel
underlying
mechanisms
crucial
role
public
opinion
within
dynamic
process
can
leverage
negative
challenge
status
even
overturn
norms
when
critical
threshold
is
reached,
we
investigated
effects
by
integrating
into
well-established
traditional
naming
game
model.
It
was
found
that
there
exists
an
optimal
range
influence,
which
facilitates
minority’s
ability
gain
power
achieve
consensus.
Notably,
our
results
show
smaller
mass
individuals
could
trigger
consensus
behavior
under
this
mechanism.
introduction
propagation
yielded
intriguing
results,
offering
new
perspective
on
expanding
formation
dynamics,
particularly
diverse
environments.
Язык: Английский
Modeling and analysis of infectious diseases based on behavioral game theory on two-layered networks under media coverage
PLoS ONE,
Год журнала:
2025,
Номер
20(5), С. e0320904 - e0320904
Опубликована: Май 20, 2025
The
spread
of
infectious
diseases
poses
significant
threats
to
public
health,
the
economy,
and
society
as
a
whole.
Despite
governmental
control
measures
over
individual
behavior,
might
still
be
influenced
by
factors
such
costs,
expected
benefits,
behavior
others,
leading
incomplete
adherence
disease
measures.
Therefore,
this
paper
proposes
behavioral
game
theory
based
model
on
two-layer
networks.
First,
considering
dynamic
interaction
between
awareness
spreading,
coupled
network
spreading
is
established.
Second,
used
describe
impact
relevant
behavior.
first
layer
represents
protective
layer,
while
second
layer.
Government
intervention
in
also
considered
model,
according
situation
threshold
introduced
Finally,
MMCA
analyze
threshold,
proportion
final
population
state
under
different
parameters
are
analyzed.
results
show
that
reducing
personal
increasing
attention
information,
enhancing
adjustments
measures,
outbreak
can
effectively
increased.
Язык: Английский
Evolutionary modeling and analysis of opinion exchange and epidemic spread among individuals
Frontiers in Physics,
Год журнала:
2024,
Номер
12
Опубликована: Ноя. 27, 2024
The
opinions
of
individuals
within
a
group
about
an
ongoing
epidemic
play
crucial
role
in
the
dynamics
spread.
People’s
acceptance
others'
also
changes
with
changing
situation
and
communication
between
individuals,
how
individuals'
views
on
epidemics
affect
spread
has
become
unresolved
issue.
In
this
study,
we
construct
two-layer
coupled
network
that
integrates
Hegselmann-Krause
(HK)
continuous
opinion
model
model.
This
framework
takes
into
account
evolutionary
game
among
group.
We
investigate
dynamic
interaction
exchange
derive
threshold
using
Quasi-Mean-Field
(QMF)
approach.
results
indicate
under
different
infection
rates,
spontaneously
form
varying
levels
epidemic,
which
turn
evolve
final
states
for
higher
rate,
faster
positive
unified
forms.
Promoting
can,
to
some
extent,
inhibit
epidemic.
However,
due
diversity
complexity
information
real
world,
phenomenon
“delayed
prevention”
often
occurs.
Язык: Английский