flepiMoP: The evolution of a flexible infectious disease modeling pipeline during the COVID-19 pandemic
Epidemics,
Год журнала:
2024,
Номер
47, С. 100753 - 100753
Опубликована: Март 2, 2024
The
COVID-19
pandemic
led
to
an
unprecedented
demand
for
projections
of
disease
burden
and
healthcare
utilization
under
scenarios
ranging
from
unmitigated
spread
strict
social
distancing
policies.
In
response,
members
the
Johns
Hopkins
Infectious
Disease
Dynamics
Group
developed
flepiMoP
(formerly
called
COVID
Scenario
Modeling
Pipeline),
a
comprehensive
open-source
software
pipeline
designed
creating
simulating
compartmental
models
infectious
transmission
inferring
parameters
through
these
models.
framework
has
been
used
extensively
produce
short-term
forecasts
longer-term
scenario
at
state
county
level
in
US,
other
countries
various
geographic
scales,
more
recently
seasonal
influenza.
this
paper,
we
highlight
how
evolved
throughout
address
changing
epidemiological
dynamics,
new
interventions,
shifts
policy-relevant
model
outputs.
As
reached
mature
state,
provide
detailed
overview
flepiMoP's
key
features
remaining
limitations,
thereby
distributing
its
documentation
as
flexible
powerful
tool
researchers
public
health
professionals
rapidly
build
deploy
large-scale
complex
any
pathogen
demographic
setup.
Язык: Английский
Role of heterogeneity: National scale data-driven agent-based modeling for the US COVID-19 Scenario Modeling Hub
Epidemics,
Год журнала:
2024,
Номер
48, С. 100779 - 100779
Опубликована: Июнь 28, 2024
UVA-EpiHiper
is
a
national
scale
agent-based
model
to
support
the
US
COVID-19
Scenario
Modeling
Hub
(SMH).
uses
detailed
representation
of
underlying
social
contact
network
along
with
data
measured
during
course
pandemic
initialize
and
calibrate
model.
In
this
paper,
we
study
role
heterogeneity
on
complexity
resulting
epidemic
dynamics
using
UVA-EpiHiper.
We
discuss
various
sources
that
encounter
in
use
modeling
analysis
under
scenarios.
also
how
affects
computational
corresponding
simulations.
Using
round
13
SMH
as
an
example,
was
initialized
calibrated.
then
output
produced
by
can
be
analyzed
obtain
interesting
insights.
find
despite
model,
software,
computation
incurred
scenario
modeling,
it
capable
capturing
heterogeneities
real-world
systems,
especially
those
networks
behaviors,
enables
analyzing
epidemiological
outcomes
between
different
demographic,
geographic,
cohorts.
applying
disease
are
within
states,
demographic
groups,
which
attributed
population
demographics,
structures,
initial
immunity.
Язык: Английский
Profiling and Bottlenecks Analysis of an Agent-based Dengue Fever Simulation Model
Опубликована: Апрель 19, 2024
Agent-Based
Model
simulations
plays
a
critical
role
in
computational
epidemiology,
usually
employing
GPU
aceleration
to
account
for
large
scale
scenarios.
In
this
work,
we
profile
and
analyze
an
agent
based
model
dengue
fever
disease
spreading
simulation
as
part
of
bachelor
thesis
find
bottlenecks
performance
issues.
We
have
discovered
bottleneck
two
the
kernels,
inefficient
host-to-device
memory
transfers.
The
use
unified
architecture
also
running
more
kernels
parallel
using
ISO
C++17
Parallelism
are
proposed
future
solutions
these
challenges.
Язык: Английский
Preface: COVID-19 Scenario Modeling Hubs
Epidemics,
Год журнала:
2024,
Номер
48, С. 100788 - 100788
Опубликована: Авг. 24, 2024
Язык: Английский
Efficient Agent-Based Simulations Using the Sender Asynchronous Programming Model
Опубликована: Окт. 23, 2024
This
paper
develops
and
evaluates
an
Agent-Based
Model
(ABM)
simulator
for
disease
transmission
using
the
C++
Sender
Programming
Model.
The
asynchronous
approach
with
is,
on
average,
2.61
times
faster
than
synchronous
methods,
enhancing
performance
while
preserving
cross-platform
compatibility.
research
offers
a
valuable
alternative
simulating
complex
epidemiological
scenarios,
advancing
computational
epidemiology
by
optimizing
both
portability.
Future
work
will
focus
improving
memory
management
validating
model
across
different
hardware
configurations
population
densities.
Язык: Английский