Challenges and opportunities in uncertainty quantification for healthcare and biological systems
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences,
Год журнала:
2025,
Номер
383(2292)
Опубликована: Март 13, 2025
Uncertainty
quantification
(UQ)
is
an
essential
aspect
of
computational
modelling
and
statistical
prediction.
Multiple
applications,
including
geophysics,
climate
science
aerospace
engineering,
incorporate
UQ
in
the
development
translation
new
technologies.
In
contrast,
application
to
biological
healthcare
models
understudied
suffers
from
several
critical
knowledge
gaps.
era
personalized
medicine,
patient-specific
modelling,
digital
twins
,
a
lack
understanding
appropriate
implementation
methodology
limits
success
simulation
clinical
setting.
The
main
contribution
our
review
article
emphasize
importance
current
deficiencies
frameworks
for
systems.
As
introduction
special
issue
on
this
topic,
we
provide
overview
methodologies,
their
applications
non-biological
systems
gaps
opportunities
development,
as
later
highlighted
by
authors
publishing
issue.
This
part
theme
‘Uncertainty
(Part
1)’.
Язык: Английский
Finding the Integral-Equation-Based Linear Renewal Density Equation and Analytical Solutions
Symmetry,
Год журнала:
2025,
Номер
17(3), С. 453 - 453
Опубликована: Март 18, 2025
In
this
study,
the
linear
renewal
equation
is
obtained
by
using
integral
equation,
function
and
Fourier–Stieltjes
transform.
It
proven
that
can
be
taking
derivative
of
equation.
Analytical
methods
for
solution
are
discussed.
shown
a
powerful
tool
model
direct
relationship
between
stochastic
processes
density
functions.
transform
allows
to
simplified
in
frequency
domain
analytical
solutions
obtained,
Laplace
provides
an
effective
method,
especially
uniform
distribution
exponential
The
equation-based
derived
study
preserves
temporal
structural
symmetries
system,
allowing
derivation
symmetric
forms
space.
light
findings,
predictions
were
made
about
what
kind
studies
would
done
future.
Язык: Английский
Real-time inference of the end of an outbreak: Temporally aggregated disease incidence data and under-reporting
Infectious Disease Modelling,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 1, 2025
Professor
Pierre
Magal
made
important
contributions
to
the
field
of
mathematical
biology
before
his
death
on
February
20,
2024,
including
research
in
which
epidemiological
models
were
used
study
ends
infectious
disease
outbreaks.
In
related
work,
there
has
been
interest
inferring
(in
real-time)
when
outbreaks
have
ended
and
control
interventions
can
be
relaxed.
Here,
we
analyse
data
from
2018
Ebola
outbreak
Équateur
Province,
Democratic
Republic
Congo,
during
an
Response
Team
(ERT)
was
deployed
implement
public
health
measures.
We
use
a
renewal
equation
transmission
model
perform
quasi
real-time
investigation
into
ERT
could
withdrawn
safely
at
tail
end
outbreak.
Specifically,
each
week
following
arrival
ERT,
calculate
probability
future
cases
if
is
withdrawn.
First,
show
that
similar
estimates
obtained
either
daily
or
weekly
case
reports.
This
demonstrates
high
temporal
resolution
reporting
may
not
always
necessary
determine
Second,
demonstrate
how
under-reporting
accounted
for
rigorously
estimating
cases.
find
that,
lower
level
reporting,
longer
it
wait
after
apparent
final
removed
(with
only
small
additional
cases).
Finally,
uncertainty
extent
included
Our
highlights
importance
accounting
deciding
remove
Язык: Английский