The
COVID-19
pandemic
has
been
a
period
where
time-series
of
disease
statistics,
such
as
the
number
cases
or
vaccinations,
have
intensively
used
by
public
health
professionals
to
estimate
how
their
region
compares
others
and
what
future
could
look
like
at
home.
Conventional
visualizations
are
often
limited
in
terms
advanced
comparative
features
supporting
forecasting
systematically.
This
paper
presents
visual
analytics
approach
support
data-driven
prediction
based
on
search-analyze-predict
process
comprising
multi-metric,
multi-criteria
search
method
technique.
These
supported
visualization
framework
for
comprehensive
comparison
multiple
time-series.
We
inform
design
our
getting
iterative
feedback
from
experts
globally,
evaluate
it
both
quantitatively
qualitatively.
Epidemics,
Journal Year:
2022,
Volume and Issue:
40, P. 100612 - 100612
Published: July 20, 2022
The
use
of
data
has
been
essential
throughout
the
unfolding
COVID-19
pandemic.
We
have
needed
it
to
populate
our
models,
inform
understanding,
and
shape
responses
disease.
However,
not
always
easy
find
access,
varied
in
quality
coverage,
difficult
reuse
or
repurpose.
This
paper
reviews
these
other
challenges
recommends
steps
develop
a
ecosystem
better
able
deal
with
future
pandemics
by
supporting
preparedness,
prevention,
detection
response.
Applied Engineering Letters Journal of Engineering and Applied Sciences,
Journal Year:
2024,
Volume and Issue:
9(1), P. 37 - 45
Published: Jan. 1, 2024
Machine
Learning
(ML)
is
gaining
attention
in
civil
engineering
especially
within
operational
phase
of
building
life
cycle.
This
crucial
for
managing
every
energy
aspect
while
ensuring
occupant
comfort.
Previous
ML
experiments
have
explored
behavior,
occupancy
estimation,
load
prediction,
defect
detection,
and
Heating,
Ventilation,
Air
Conditioning
(HVAC)
system
diagnostics.
However,
challenges
such
as
transferability
limited
literature
on
components
the
hinder
broader
industry
adoption.
critical
review
aims
to
assess
potential
operations,
focusing
consumption,
big
data
control,
reinforcement
learning,
thermal
comfort
modeling.
By
identifying
knowledge
gaps,
study
recommends
further
research
leverage
sustainable
consumption
It
highlights
ML’s
promising
role
striking
a
balance
between
efficiency
wellbeing.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences,
Journal Year:
2022,
Volume and Issue:
380(2233)
Published: Aug. 15, 2022
We
report
on
an
ongoing
collaboration
between
epidemiological
modellers
and
visualization
researchers
by
documenting
reflecting
upon
knowledge
constructs-a
series
of
ideas,
approaches
methods
taken
from
existing
research
practice-deployed
developed
to
support
modelling
the
COVID-19
pandemic.
Structured
independent
commentary
these
efforts
is
synthesized
through
iterative
reflection
develop:
evidence
effectiveness
value
in
this
context;
open
problems
which
communities
may
focus;
guidance
for
future
activity
type
recommendations
safeguard
achievements
promote,
advance,
secure
prepare
collaborations
kind.
In
describing
comparing
a
related
projects
that
were
undertaken
unprecedented
conditions,
our
hope
unique
report,
its
rich
interactive
supplementary
materials,
will
guide
scientific
community
embracing
observation,
analysis
data
as
well
disseminating
findings.
Equally
we
encourage
engage
with
impactful
science
addressing
emerging
challenges.
If
are
successful,
showcase
stimulate
mutually
beneficial
engagement
complementary
expertise
address
significance
epidemiology
beyond.
See
https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/.
This
article
part
theme
issue
'Technical
challenges
real-life
epidemics
examples
overcoming
these'.
Epidemics,
Journal Year:
2021,
Volume and Issue:
37, P. 100499 - 100499
Published: Aug. 30, 2021
The
COVID-19
pandemic
has
seen
infectious
disease
modelling
at
the
forefront
of
government
decision-making.
Models
have
been
widely
used
throughout
to
estimate
pathogen
spread
and
explore
potential
impact
different
intervention
strategies.
Infectious
modellers
policymakers
worked
effectively
together,
but
there
are
many
avenues
for
progress
on
this
interface.
In
paper,
we
identify
discuss
seven
broad
challenges
interaction
models
policy
control.
We
then
conclude
with
suggestions
recommendations
future.
Immersive
interaction
technology,
such
as
virtual
reality
(VR)
and
augmented
(AR),
plays
a
crucial
role
in
creating
realistic
engaging
experience
for
users
within
the
metaverse.
This
technology
can
be
widely
used
fields
paramedicine,
industrial
design,
VR
games,
3D
movies.
Additionally,
advancements
5G
networks
cloud
computing
have
made
it
possible
to
create
high-fidelity
low-latency
environments,
making
multiple
interact
real-time
same
space.
chapter
introduces
concept
application
of
digital
twins,
which
is
representation
physical
assets,
systems,
processes.
They
are
simulate
analyze
behavior
performance
real-world
entities
they
represent
improve
operations,
predict
maintenance
needs,
optimize
performance.
Overall,
metaverse
vision
fully
immersive
interactive
world,
how
this
brought
life.
With
network
infrastructure,
becoming
increasingly
feasible
expected
play
growing
we
live,
work,
with
each
other
world.
Throughout
the
COVID-19
pandemic,
visualizations
became
commonplace
in
public
communications
to
help
people
make
sense
of
world
and
reasons
behind
government-imposed
restrictions.
Though
adult
population
were
main
target
these
messages,
children
affected
by
restrictions
through
not
being
able
see
friends
virtual
schooling.
However,
daily
models
visualizations,
pandemic
response
provided
a
way
for
understand
what
data
scientists
really
do
new
routes
engagement
with
STEM
subjects.
In
this
paper,
we
describe
development
an
interactive
accessible
visualization
tool
be
used
workshops
explain
computational
modeling
diseases,
particular
COVID-19.
We
detail
our
design
decisions
based
on
approaches
evidenced
effective
engaging
such
as
unplugged
activities
interactivity.
share
reflections
learnings
from
delivering
140
assess
their
effectiveness.
Visual
analytics
tools
can
help
illustrate
the
spread
of
infectious
diseases
and
enable
informed
decisions
on
epidemiological
public
health
issues.
To
create
visualisation
that
are
intuitive,
easy
to
use,
effective
in
communicating
information,
continued
research
development
focusing
user-centric
methodological
design
models
is
extremely
important.
As
a
contribution
this
topic,
paper
presents
process
visual
application
ESID
(Epidemiological
Scenarios
for
Infectious
Diseases
).
tool
aimed
at
projecting
future
developments
disease
using
reported
simulated
data
based
sound
mathematical-epidemiological
models.
The
involved
collaborative
participatory
approach
with
project
partners
from
diverse
scientific
fields.
findings
these
studies,
along
guidelines
derived
them,
played
pivotal
role
shaping
tool.
Healthcare,
Journal Year:
2023,
Volume and Issue:
11(6), P. 847 - 847
Published: March 13, 2023
Since
the
outbreak
of
novel
coronavirus
disease
2019
(COVID-19),
epidemic
has
gradually
slowed
down
in
various
countries
and
people's
lives
have
returned
to
normal.
To
monitor
spread
epidemic,
studies
discussing
design
related
healthcare
information
systems
been
increasing
recently.
However,
these
might
not
consider
aspect
user-centric
when
developing
systems.
This
study
examined
innovative
technology
applications
rapidly
built
prototype
for
smart
through
a
systematic
literature
review
patient
innovation.
The
guidelines
Smart
Healthcare
System
(SHS)
were
then
compiled
an
expert
process.
will
provide
reference
future
research
similar
system
development.
2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct),
Journal Year:
2023,
Volume and Issue:
unknown, P. 97 - 102
Published: Oct. 16, 2023
Situated
Visualization
is
an
emerging
field
that
unites
several
areas
-
visualization,
augmented
reality,
human-computer
interaction,
and
internet-of-things,
to
support
human
data
activities
within
the
ubiquitous
world.
Likewise,
dashboards
are
broadly
used
simplify
complex
through
multiple
views.
However,
only
adapted
for
desktop
settings,
requires
visual
strategies
situatedness.
We
propose
concept
of
AR-based
situated
present
design
considerations
challenges
developed
over
interviews
with
experts.
These
aim
directions
opportunities
facilitating
effective
designing
authoring
dashboards.
Epidemics,
Journal Year:
2022,
Volume and Issue:
39, P. 100574 - 100574
Published: May 16, 2022
Uncertainty
quantification
is
a
formal
paradigm
of
statistical
estimation
that
aims
to
account
for
all
uncertainties
inherent
in
the
modelling
process
real-world
complex
systems.
The
methods
are
directly
applicable
stochastic
models
epidemiology,
however
they
have
thus
far
not
been
widely
used
this
context.
In
paper,
we
provide
tutorial
on
uncertainty
epidemic
models,
aiming
facilitate
use
practitioners
with
other
simulators
applied
We
workflow
including
important
decisions
and
considerations
need
be
taken,
illustrate
over
simple
model
UK
SARS-CoV-2
transmission
patient
outcome.
also
present
new
approaches
visualisation
outputs
from
sensitivity
analyses
more
generally
high
input
and/or
output
dimensions.
