Healthcare,
Год журнала:
2023,
Номер
11(2), С. 260 - 260
Опубликована: Янв. 13, 2023
In
2020,
coronavirus
(COVID-19)
was
declared
a
global
pandemic
and
it
remains
prevalent
today.
A
necessity
to
model
the
transmission
of
virus
has
emerged
as
result
COVID-19’s
exceedingly
contagious
characteristics
its
rapid
propagation
throughout
world.
Assessing
incidence
infection
could
enable
policymakers
identify
measures
halt
gauge
required
capacity
healthcare
centers.
Therefore,
modeling
susceptibility,
exposure,
infection,
recovery
in
relation
COVID-19
is
crucial
for
adoption
interventions
by
regulatory
authorities.
Fundamental
factors,
such
rate,
mortality
must
be
considered
order
accurately
represent
behavior
using
mathematical
models.
The
difficulty
creating
identifying
real
variables.
Parameters
might
vary
significantly
across
models,
which
can
variations
simulation
results
because
projections
primarily
rely
on
particular
dataset.
purpose
this
work
establish
susceptible–exposed–infected–recovered
(SEIR)
describing
outbreak
Kingdom
Saudi
Arabia
(KSA).
goal
study
derive
essential
epidemiological
factors
from
actual
data.
System
dynamics
design
experiment
approaches
were
used
determine
most
appropriate
combination
parameters
influence
COVID-19.
This
investigates
how
variables
seasonal
amplitude,
social
awareness
impact,
waning
time
adapted
correctly
estimate
scenarios
number
infected
persons
daily
basis
KSA.
also
utilized
ascertain
stress
(or
hospital
capacity)
affects
percentage
hospitalizations
deaths.
Additionally,
policies
or
strategies
monitoring
restricting
Arabia.
ERJ Open Research,
Год журнала:
2024,
Номер
10(3), С. 00939 - 2023
Опубликована: Апрель 19, 2024
Background
Data
on
viral
kinetics
and
variants
affecting
the
duration
of
shedding
were
limited.
Our
objective
was
to
determine
in
distinct
severe
acute
respiratory
syndrome
coronavirus
2
variants,
including
Omicron
BA.4/5
BF.7,
identify
relevant
influencing
factors.
Methods
We
carried
out
a
longitudinal
cohort
study
at
Beijing
Xiaotangshan
Fangcang
shelter
hospital
from
May
June
2022
(Omicron
BA.4/5)
November
December
BF.7).
Nucleocapsid
protein
(N)
open
reading
frame
(ORF)
genes
considered
as
target
reverse
transcription
PCR.
The
daily
results
cycle
threshold
(CT),
lowest
ORF1ab-CT
values
for
days
1–3
post-hospitalisation
N-CT
(CT3minN)
demographic
clinical
characteristics
collected.
Results
1433
patients
with
disease
2019
(COVID-19)
recruited
hospital,
which
278
diagnosed
1155
BF.7.
Patients
BF.7
infection
showed
longer
shedding.
associated
age,
alcohol
use,
severity
COVID-19
CT3minN.
Moreover,
nomogram
had
excellent
accuracy
predicting
Conclusions
indicated
that
period
contagiousness
than
those
BA.4/5.
affected
by
variety
factors
may
become
an
applicable
instrument
predict
Furthermore,
we
developed
new
model
can
accurately
COVID-19,
created
user-friendly
website
apply
this
prediction
(
https://puh3.shinyapps.io/CVSP_Model/
).
The Lancet Microbe,
Год журнала:
2024,
Номер
5(10), С. 100894 - 100894
Опубликована: Авг. 23, 2024
The
unprecedented
COVID-19
pandemic
has
highlighted
the
strategic
value
of
wastewater-based
surveillance
(WBS)
SARS-CoV-2.
This
multisite
28-month-long
study
focused
on
WBS
for
older
residents
in
12
long-term
care
facilities
(LTCFs)
Edmonton
(AB,
Canada)
by
assessing
relationships
between
COVID-19,
WBS,
and
serostatus
during
pandemic.
Healthcare,
Год журнала:
2023,
Номер
11(2), С. 260 - 260
Опубликована: Янв. 13, 2023
In
2020,
coronavirus
(COVID-19)
was
declared
a
global
pandemic
and
it
remains
prevalent
today.
A
necessity
to
model
the
transmission
of
virus
has
emerged
as
result
COVID-19’s
exceedingly
contagious
characteristics
its
rapid
propagation
throughout
world.
Assessing
incidence
infection
could
enable
policymakers
identify
measures
halt
gauge
required
capacity
healthcare
centers.
Therefore,
modeling
susceptibility,
exposure,
infection,
recovery
in
relation
COVID-19
is
crucial
for
adoption
interventions
by
regulatory
authorities.
Fundamental
factors,
such
rate,
mortality
must
be
considered
order
accurately
represent
behavior
using
mathematical
models.
The
difficulty
creating
identifying
real
variables.
Parameters
might
vary
significantly
across
models,
which
can
variations
simulation
results
because
projections
primarily
rely
on
particular
dataset.
purpose
this
work
establish
susceptible–exposed–infected–recovered
(SEIR)
describing
outbreak
Kingdom
Saudi
Arabia
(KSA).
goal
study
derive
essential
epidemiological
factors
from
actual
data.
System
dynamics
design
experiment
approaches
were
used
determine
most
appropriate
combination
parameters
influence
COVID-19.
This
investigates
how
variables
seasonal
amplitude,
social
awareness
impact,
waning
time
adapted
correctly
estimate
scenarios
number
infected
persons
daily
basis
KSA.
also
utilized
ascertain
stress
(or
hospital
capacity)
affects
percentage
hospitalizations
deaths.
Additionally,
policies
or
strategies
monitoring
restricting
Arabia.
