Nature Communications,
Journal Year:
2020,
Volume and Issue:
11(1)
Published: Aug. 26, 2020
Abstract
The
pressing
need
to
restart
socioeconomic
activities
locked-down
control
the
spread
of
SARS-CoV-2
in
Italy
must
be
coupled
with
effective
methodologies
selectively
relax
containment
measures.
Here
we
employ
a
spatially
explicit
model,
properly
attentive
role
inapparent
infections,
capable
of:
estimating
expected
unfolding
outbreak
under
continuous
lockdown
(baseline
trajectory);
assessing
deviations
from
baseline,
should
relaxations
result
increased
disease
transmission;
calculating
isolation
effort
required
prevent
resurgence
outbreak.
A
40%
increase
transmission
would
yield
rebound
infections.
isolating
daily
~5.5%
exposed
and
highly
infectious
individuals
proves
necessary
maintain
epidemic
curve
onto
decreasing
baseline
trajectory.
We
finally
provide
an
ex-post
assessment
based
on
epidemiological
data
that
became
available
after
initial
analysis
estimate
actual
occurred
weakening
lockdown.
PLoS Computational Biology,
Journal Year:
2021,
Volume and Issue:
17(7), P. e1009149 - e1009149
Published: July 26, 2021
The
COVID-19
pandemic
has
created
an
urgent
need
for
models
that
can
project
epidemic
trends,
explore
intervention
scenarios,
and
estimate
resource
needs.
Here
we
describe
the
methodology
of
Covasim
(COVID-19
Agent-based
Simulator),
open-source
model
developed
to
help
address
these
questions.
includes
country-specific
demographic
information
on
age
structure
population
size;
realistic
transmission
networks
in
different
social
layers,
including
households,
schools,
workplaces,
long-term
care
facilities,
communities;
age-specific
disease
outcomes;
intrahost
viral
dynamics,
viral-load-based
transmissibility.
also
supports
extensive
set
interventions,
non-pharmaceutical
such
as
physical
distancing
protective
equipment;
pharmaceutical
vaccination;
testing
symptomatic
asymptomatic
testing,
isolation,
contact
tracing,
quarantine.
These
interventions
incorporate
effects
delays,
loss-to-follow-up,
micro-targeting,
other
factors.
Implemented
pure
Python,
been
designed
with
equal
emphasis
performance,
ease
use,
flexibility:
highly
customized
scenarios
be
run
a
standard
laptop
under
minute.
In
collaboration
local
health
agencies
policymakers,
already
applied
examine
dynamics
inform
policy
decisions
more
than
dozen
countries
Africa,
Asia-Pacific,
Europe,
North
America.
Frontiers in Psychology,
Journal Year:
2020,
Volume and Issue:
11
Published: July 10, 2020
Background:
The
COVID-19
pandemic
had
a
massive
impact
on
health
care
systems,
increasing
the
risks
of
psychological
distress
in
professionals.
This
study
aims
at
assessing
prevalence
burnout
and
psychopathological
conditions
professionals
working
institution
Northern
Italy,
to
identify
socio-demographic,
work-related
predictors
burnout.
Methods:
Health
hospitals
Istituto
Auxologico
Italiano
were
asked
participate
an
online
anonymous
survey
investigating
socio-demographic
data,
emergency-related
work
factors,
state
anxiety,
distress,
post-traumatic
symptoms
Predictors
three
components
assessed
using
elastic
net
regression
models.
Results:
Three
hundred
thirty
participated
survey.
Two
thirty-five
(71.2%)
scores
anxiety
above
clinical
cutoff,
88
(26.8%)
levels
depression,
103
(31.3%)
113
(34.3%)
stress,
121
(36.7%)
stress.
Regarding
burnout,
107
(35.7%)
moderate
105
(31.9%)
severe
emotional
exhaustion;
46
(14.0%)
40
(12.1%)
depersonalization;
132
(40.1%)
reduced
personal
accomplishment.
all
hours,
comorbidities,
fear
infection
perceived
support
by
friends.
both
exhaustion
depersonalization
female
gender,
being
nurse,
hospital,
contact
with
patients.
Reduced
accomplishment
was
also
predicted
age.
Conclusions:
high
during
emergency.
Monitoring
timely
treatment
these
is
needed.
IEEE Access,
Journal Year:
2020,
Volume and Issue:
8, P. 130820 - 130839
Published: Jan. 1, 2020
The
very
first
infected
novel
coronavirus
case
(COVID-19)
was
found
in
Hubei,
China
Dec.
2019.
COVID-19
pandemic
has
spread
over
214
countries
and
areas
the
world,
significantly
affected
every
aspect
of
our
daily
lives.
At
time
writing
this
article,
numbers
cases
deaths
still
increase
have
no
sign
a
well-controlled
situation,
e.g.,
as
13
July
2020,
from
total
number
around
13.1
million
positive
cases,
571,527
were
reported
world.
Motivated
by
recent
advances
applications
artificial
intelligence
(AI)
big
data
various
areas,
paper
aims
at
emphasizing
their
importance
responding
to
outbreak
preventing
severe
effects
pandemic.
We
firstly
present
an
overview
AI
data,
then
identify
aimed
fighting
against
COVID-19,
next
highlight
challenges
issues
associated
with
state-of-the-art
solutions,
finally
come
up
recommendations
for
communications
effectively
control
situation.
It
is
expected
that
provides
researchers
communities
new
insights
into
ways
improve
drives
further
studies
stopping
outbreak.
Signal Transduction and Targeted Therapy,
Journal Year:
2021,
Volume and Issue:
6(1)
Published: March 8, 2021
Abstract
Since
the
first
description
of
a
coronavirus-related
pneumonia
outbreak
in
December
2019,
virus
SARS-CoV-2
that
causes
infection/disease
(COVID-19)
has
evolved
into
pandemic,
and
as
today,
>100
million
people
globally
over
210
countries
have
been
confirmed
to
infected
two
died
COVID-19.
This
brief
review
summarized
what
we
hitherto
learned
following
areas:
epidemiology,
virology,
pathogenesis,
diagnosis,
use
artificial
intelligence
assisting
treatment,
vaccine
development.
As
there
are
number
parallel
developments
each
these
areas
some
development
deployment
were
at
unprecedented
speed,
also
provided
specific
dates
for
certain
milestones
so
readers
can
appreciate
timing
critical
events.
Of
note
is
fact
diagnostics,
antiviral
drugs,
vaccines
developed
approved
by
regulatory
within
1
year
after
was
discovered.
conducted
parallel,
events
evolution
research
data
our
understanding.
The
world
working
together
combat
this
pandemic.
highlights
directions
will
evolve
rapidly
near
future.
SN Computer Science,
Journal Year:
2020,
Volume and Issue:
1(4)
Published: June 11, 2020
COVID-19
is
a
pandemic
that
has
affected
over
170
countries
around
the
world.
The
number
of
infected
and
deceased
patients
been
increasing
at
an
alarming
rate
in
almost
all
nations.
Forecasting
techniques
can
be
inculcated
thereby
assisting
designing
better
strategies
taking
productive
decisions.
These
assess
situations
past
enabling
predictions
about
situation
to
occur
future.
might
help
prepare
against
possible
threats
consequences.
play
very
important
role
yielding
accurate
predictions.
This
study
categorizes
forecasting
into
two
types,
namely,
stochastic
theory
mathematical
models
data
science/machine
learning
techniques.
Data
collected
from
various
platforms
also
vital
forecasting.
In
this
study,
categories
datasets
have
discussed,
i.e.,
big
accessed
World
Health
Organization/National
databases
social
media
communication.
done
based
on
parameters
such
as
impact
environmental
factors,
incubation
period,
quarantine,
age,
gender
many
more.
used
for
are
extensively
studied
work.
However,
come
with
their
own
set
challenges
(technical
generic).
discusses
these
provides
recommendations
people
who
currently
fighting
global
pandemic.
