A Binary Prototype for Time-Series Surveillance and Intervention
medRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 5, 2025
Abstract
Despite
much
research
on
early
detection
of
anomalies
from
surveillance
data,
a
systematic
framework
for
appropriately
acting
these
signals
is
lacking.
We
addressed
this
gap
by
formulating
hidden
Markov-style
model
time-series
surveillance,
where
the
system
state,
observed
and
decision
rule
are
all
binary.
incur
delayed
cost,
c
,
whenever
abnormal
no
action
taken,
or
an
immediate
k
with
action,
<
.
If
costs
too
high,
then
detrimental,
intervention
should
never
occur.
sufficiently
low,
always
Only
when
intermediate
low
beneficial.
Our
equations
provide
assessing
which
approach
may
apply
under
range
scenarios
and,
if
warranted,
facilitate
methodical
classification
strategies.
thus
offers
conceptual
basis
designing
real-world
public
health
systems.
Language: Английский
Diagnostics for Public Health — Infectious Disease Surveillance and Control
NEJM Evidence,
Journal Year:
2024,
Volume and Issue:
3(5)
Published: April 23, 2024
Accurate
diagnostics
are
critical
in
public
health
to
ensure
successful
disease
tracking,
prevention,
and
control.
Many
of
the
same
characteristics
desirable
for
diagnostic
procedures
both
medicine
health:
example,
low
cost,
high
speed,
invasiveness,
ease
use
interpretation,
day-to-day
consistency,
accuracy.
This
review
lays
out
five
principles
that
salient
when
goal
diagnosis
is
improve
overall
a
population
rather
than
particular
patient,
it
applies
them
two
important
cases:
pandemic
infectious
antimicrobial
resistance.
Language: Английский
The value of environmental surveillance for pandemic response
Pedro Nascimento de Lima,
No information about this author
Stephen L. Karr,
No information about this author
Jing Zhi Lim
No information about this author
et al.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Nov. 22, 2024
Environmental
sampling
surveillance
(ESS)
technologies,
such
as
wastewater
genomic
and
air
sensors,
have
been
increasingly
adopted
during
the
COVID-19
pandemic
to
provide
valuable
information
for
public
health
response.
However,
ESS
coverage
is
not
universal,
decision-makers
need
support
choose
whether
how
expand
sustain
efforts.
This
paper
introduces
a
model
approach
quantify
value
of
systems
that
leading
epidemiological
indicators
Using
base-case
scenario,
we
in
first
year
new
demonstrate
depends
on
biological
societal
parameters.
Under
baseline
assumptions,
an
system
provides
5-day
early
warning
relative
syndromic
could
reduce
deaths
from
149
(95%
prediction
interval:
136–169)
134
(124–144)
per
100,000
population
COVID-19-like
pandemic,
resulting
net
monetary
benefit
$1,450
($609-$2,740)
person.
The
system's
higher
more
transmissible
deadly
pathogens
but
hinges
effectiveness
interventions.
Our
findings
also
suggest
would
net-positive
benefits
even
if
they
were
permanently
maintained
like
SARS-Cov-2
emerged
once
every
century
or
less
frequently.
results
can
be
used
prioritize
ESS,
decide
currently
uncovered
populations,
determine
scale
systems'
over
time.
Language: Английский