Infectious Disease Modelling,
Год журнала:
2021,
Номер
7(1), С. 30 - 44
Опубликована: Ноя. 27, 2021
This
paper
uses
Covasim,
an
agent-based
model
(ABM)
of
COVID-19,
to
evaluate
and
scenarios
epidemic
spread
in
New
York
State
(USA),
the
UK,
Novosibirsk
region
(Russia).
Epidemiological
parameters
such
as
contagiousness
(virus
transmission
rate),
initial
number
infected
people,
probability
being
tested
depend
on
region's
demographic
geographical
features,
containment
measures
introduced;
they
are
calibrated
data
about
COVID-19
interest.
At
first
stage
our
study,
epidemiological
(numbers
people
tested,
diagnoses,
critical
cases,
hospitalizations,
deaths)
for
each
mentioned
regions
were
analyzed.
The
characterized
terms
seasonality,
stationarity,
dependency
spaces,
extrapolated
using
machine
learning
techniques
specify
unknown
model.
second
stage,
Optuna
optimizer
based
tree
Parzen
estimation
method
objective
function
minimization
was
applied
determine
model's
parameters.
validated
with
historical
2020.
modeled
results
State,
UK
have
demonstrated
that
if
level
testing
is
preserved,
positive
cases
will
remain
same
during
March
2021,
while
it
reduce.
Due
features
(two
datasets
stationary
series
1),
forecast
precision
relatively
high
but
lower
new
COVID-19.
JAMA Network Open,
Год журнала:
2021,
Номер
4(6), С. e2116425 - e2116425
Опубликована: Июнь 25, 2021
Importance
The
COVID-19
pandemic
has
severely
disrupted
US
educational
institutions.
Given
potential
adverse
financial
and
psychosocial
effects
of
campus
closures,
many
institutions
developed
strategies
to
reopen
campuses
in
the
fall
2020
semester
despite
ongoing
threat
COVID-19.
However,
opted
have
limited
reopening
minimize
risk
spread
SARS-CoV-2.
Objective
To
analyze
how
Boston
University
(BU)
fully
reopened
its
controlled
transmission
worsening
Boston,
Massachusetts.
Design,
Setting,
Participants
This
multifaceted
intervention
case
series
was
conducted
at
a
large
urban
university
Massachusetts,
during
semester.
BU
response
included
high-throughput
SARS-CoV-2
polymerase
chain
reaction
testing
facility
with
capacity
deliver
results
less
than
24
hours;
routine
asymptomatic
screening
for
COVID-19;
daily
health
attestations;
adherence
monitoring
feedback;
robust
contact
tracing,
quarantine,
isolation
on-campus
facilities;
face
mask
use;
enhanced
hand
hygiene;
social
distancing
recommendations;
dedensification
classrooms
public
places;
enhancement
all
building
air
systems.
Data
were
analyzed
from
December
20,
2020,
January
31,
2021.
Main
Outcomes
Measures
diagnosis
confirmed
by
reverse
transcription–polymerase
anterior
nares
specimens
sources
transmission,
as
determined
through
tracing.
Results
Between
August
more
500
000
tests
identified
719
individuals
COVID-19,
including
496
students
(69.0%),
11
faculty
(1.5%),
212
staff
(29.5%).
Overall,
718
individuals,
or
1.8%
community,
had
test
positive
Of
837
close
contacts
traced,
86
(10.3%)
tracers
source
370
(51.5%),
206
(55.7%)
identifying
non-BU
source.
Among
5
84
known
infection,
most
reported
outside
(all
members
[100%]
67
[79.8%]).
A
108
183
undergraduate
(59.0%)
39
98
graduate
(39.8%);
notably,
no
traced
classroom
setting.
Conclusions
Relevance
In
this
used
coordinated
strategy
testing,
isolation,
management
oversight,
control
an
Scientific Reports,
Год журнала:
2021,
Номер
11(1)
Опубликована: Апрель 6, 2021
Coronavirus
disease
2019
(COVID-19)
has
caused
strain
on
health
systems
worldwide
due
to
its
high
mortality
rate
and
the
large
portion
of
cases
requiring
critical
care
mechanical
ventilation.
During
these
uncertain
times,
public
decision
makers,
from
city
departments
federal
agencies,
sought
use
epidemiological
models
for
support
in
allocating
resources,
developing
non-pharmaceutical
interventions,
characterizing
dynamics
COVID-19
their
jurisdictions.
In
response,
we
developed
a
flexible
scenario
modeling
pipeline
that
could
quickly
tailor
makers
seeking
compare
projections
epidemic
trajectories
healthcare
impacts
multiple
intervention
scenarios
different
locations.
Here,
present
components
configurable
features
COVID
Scenario
Pipeline,
with
vignette
detailing
current
use.
We
also
model
limitations
active
areas
development
meet
ever-changing
maker
needs.
Scientific Reports,
Год журнала:
2021,
Номер
11(1)
Опубликована: Апрель 22, 2021
As
the
UK
reopened
after
first
wave
of
COVID-19
epidemic,
crucial
questions
emerged
around
role
for
ongoing
interventions,
including
test-trace-isolate
(TTI)
strategies
and
mandatory
masks.
Here
we
assess
importance
masks
in
secondary
schools
by
evaluating
their
impact
over
September
1-October
23,
2020.
We
show
that,
assuming
TTI
levels
from
August
2020
no
fundamental
changes
virus's
transmissibility,
adoption
would
have
reduced
predicted
size
a
second
wave,
but
preventing
it
required
68%
or
46%
those
with
symptoms
to
seek
testing
(assuming
masks'
effective
coverage
15%
30%
respectively).
With
community
settings
not
schools,
rates
increase
76%
57%.
Infectious Disease Modelling,
Год журнала:
2021,
Номер
7(1), С. 30 - 44
Опубликована: Ноя. 27, 2021
This
paper
uses
Covasim,
an
agent-based
model
(ABM)
of
COVID-19,
to
evaluate
and
scenarios
epidemic
spread
in
New
York
State
(USA),
the
UK,
Novosibirsk
region
(Russia).
Epidemiological
parameters
such
as
contagiousness
(virus
transmission
rate),
initial
number
infected
people,
probability
being
tested
depend
on
region's
demographic
geographical
features,
containment
measures
introduced;
they
are
calibrated
data
about
COVID-19
interest.
At
first
stage
our
study,
epidemiological
(numbers
people
tested,
diagnoses,
critical
cases,
hospitalizations,
deaths)
for
each
mentioned
regions
were
analyzed.
The
characterized
terms
seasonality,
stationarity,
dependency
spaces,
extrapolated
using
machine
learning
techniques
specify
unknown
model.
second
stage,
Optuna
optimizer
based
tree
Parzen
estimation
method
objective
function
minimization
was
applied
determine
model's
parameters.
validated
with
historical
2020.
modeled
results
State,
UK
have
demonstrated
that
if
level
testing
is
preserved,
positive
cases
will
remain
same
during
March
2021,
while
it
reduce.
Due
features
(two
datasets
stationary
series
1),
forecast
precision
relatively
high
but
lower
new
COVID-19.
