Chaos An Interdisciplinary Journal of Nonlinear Science,
Journal Year:
2023,
Volume and Issue:
33(11)
Published: Nov. 1, 2023
Scientific
cooperation
on
an
international
level
has
been
well
studied
in
the
literature.
However,
much
less
is
known
about
this
intercontinental
level.
In
paper,
we
address
issue
by
creating
a
collection
of
approximately
13.8×106
publications
around
papers
one
highly
cited
authors
working
complex
networks
and
their
applications.
The
obtained
rank-frequency
distribution
probability
sequences
describing
continents
number
countries—with
which
are
affiliated—follows
power
law
with
exponent
−1.9108(15).
Such
dependence
literature
as
Zipf’s
law,
it
originally
observed
linguistics;
later,
turned
out
that
very
commonly
various
fields.
distinct
“continent
(number
countries)”
function
analyzed
grows
according
to
0.527(14);
i.e.,
follows
Heap’s
law.
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Nov. 20, 2023
Our
ability
to
forecast
epidemics
far
into
the
future
is
constrained
by
many
complexities
of
disease
systems.
Realistic
longer-term
projections
may,
however,
be
possible
under
well-defined
scenarios
that
specify
state
critical
epidemic
drivers.
Since
December
2020,
U.S.
COVID-19
Scenario
Modeling
Hub
(SMH)
has
convened
multiple
modeling
teams
make
months
ahead
SARS-CoV-2
burden,
totaling
nearly
1.8
million
national
and
state-level
projections.
Here,
we
find
SMH
performance
varied
widely
as
a
function
both
scenario
validity
model
calibration.
We
show
remained
close
reality
for
22
weeks
on
average
before
arrival
unanticipated
variants
invalidated
key
assumptions.
An
ensemble
participating
models
preserved
variation
between
(using
linear
opinion
pool
method)
was
consistently
more
reliable
than
any
single
in
periods
valid
assumptions,
while
projection
interval
coverage
near
target
levels.
were
used
guide
pandemic
response,
illustrating
value
collaborative
hubs
The Lancet Digital Health,
Journal Year:
2022,
Volume and Issue:
4(10), P. e738 - e747
Published: Sept. 20, 2022
Infectious
disease
modelling
can
serve
as
a
powerful
tool
for
situational
awareness
and
decision
support
policy
makers.
However,
COVID-19
efforts
faced
many
challenges,
from
poor
data
quality
to
changing
human
behaviour.
To
extract
practical
insight
the
large
body
of
literature
available,
we
provide
narrative
review
with
systematic
approach
that
quantitatively
assessed
prospective,
data-driven
studies
in
USA.
We
analysed
136
papers,
focused
on
aspects
models
are
essential
have
documented
forecasting
window,
methodology,
prediction
target,
datasets
used,
geographical
resolution
each
study.
also
found
fraction
papers
did
not
evaluate
performance
(25%),
express
uncertainty
(50%),
or
state
limitations
(36%).
remedy
some
these
identified
gaps,
recommend
adoption
EPIFORGE
2020
model
reporting
guidelines
creating
an
information-sharing
system
is
suitable
fast-paced
infectious
outbreak
science.
In
Spring
2021,
the
highly
transmissible
SARS-CoV-2
Delta
variant
began
to
cause
increases
in
cases,
hospitalizations,
and
deaths
parts
of
United
States.
At
time,
with
slowed
vaccination
uptake,
this
novel
was
expected
increase
risk
pandemic
resurgence
US
summer
fall
2021.
As
part
COVID-19
Scenario
Modeling
Hub,
an
ensemble
nine
mechanistic
models
produced
6-month
scenario
projections
for
July-December
2021
These
estimated
substantial
resurgences
across
resulting
from
more
variant,
projected
occur
most
US,
coinciding
school
business
reopening.
The
scenarios
revealed
that
reaching
higher
vaccine
coverage
reduced
size
duration
substantially,
impacts
largely
concentrated
a
subset
states
lower
coverage.
Despite
accurate
projection
surges
occurring
timing,
magnitude
substantially
underestimated
by
compared
reported
during
July-December,
highlighting
continued
challenges
predict
evolving
pandemic.
Vaccination
uptake
remains
critical
limiting
transmission
disease,
particularly
Higher
goals
at
onset
surge
new
were
avert
over
1.5
million
cases
21,000
deaths,
although
may
have
had
even
greater
impacts,
considering
model.
Journal of Clinical Microbiology,
Journal Year:
2022,
Volume and Issue:
60(7)
Published: June 29, 2022
Laboratory
tests
for
the
accurate
and
rapid
identification
of
SARS-CoV-2
variants
can
potentially
guide
treatment
COVID-19
patients
inform
infection
control
public
health
surveillance
efforts.
Here,
we
present
development
validation
a
variant
DETECTR
assay
incorporating
loop-mediated
isothermal
amplification
(LAMP)
followed
by
CRISPR-Cas12
based
single
nucleotide
polymorphism
(SNP)
mutations
in
spike
(S)
gene.
This
targets
L452R,
E484K/Q/A,
N501Y
mutations,
at
least
one
which
is
found
nearly
all
major
variants.
In
comparison
three
different
Cas12
enzymes,
only
newly
identified
enzyme
CasDx1
was
able
to
accurately
identify
targeted
SNP
mutations.
An
analysis
pipeline
CRISPR-based
from
261
clinical
samples
yielded
concordance
97.3%
agreement
98.9%
(258
261)
lineage
classification,
using
whole-genome
sequencing
and/or
real-time
RT-PCR
as
test
comparators.
We
also
showed
that
detection
E484A
mutation
necessary
sufficient
Omicron
other
circulating
patient
samples.
These
findings
demonstrate
utility
faster
simpler
diagnostic
method
compared
with
laboratories.
Proceedings of the National Academy of Sciences,
Journal Year:
2023,
Volume and Issue:
120(18)
Published: April 25, 2023
Policymakers
must
make
management
decisions
despite
incomplete
knowledge
and
conflicting
model
projections.
Little
guidance
exists
for
the
rapid,
representative,
unbiased
collection
of
policy-relevant
scientific
input
from
independent
modeling
teams.
Integrating
approaches
decision
analysis,
expert
judgment,
aggregation,
we
convened
multiple
teams
to
evaluate
COVID-19
reopening
strategies
a
mid-sized
United
States
county
early
in
pandemic.
Projections
seventeen
distinct
models
were
inconsistent
magnitude
but
highly
consistent
ranking
interventions.
The
6-mo-ahead
aggregate
projections
well
line
with
observed
outbreaks
US
counties.
results
showed
that
up
half
population
could
be
infected
full
workplace
reopening,
while
restrictions
reduced
median
cumulative
infections
by
82%.
Rankings
interventions
across
public
health
objectives,
there
was
strong
trade-off
between
outcomes
duration
closures,
no
win-win
intermediate
identified.
Between-model
variation
high;
thus
provide
valuable
risk
quantification
making.
This
approach
can
applied
evaluation
any
setting
where
are
used
inform
case
study
demonstrated
utility
our
one
several
multimodel
efforts
laid
groundwork
Scenario
Modeling
Hub,
which
has
provided
rounds
real-time
scenario
situational
awareness
making
Centers
Disease
Control
Prevention
since
December
2020.
Epidemics,
Journal Year:
2023,
Volume and Issue:
44, P. 100705 - 100705
Published: July 18, 2023
Beginning
in
December
2020,
the
COVID-19
Scenario
Modeling
Hub
has
provided
quantitative
scenario-based
projections
for
cases,
hospitalizations,
and
deaths,
aggregated
across
up
to
nine
modeling
groups.
Projections
spanned
multiple
months
into
future
timely
information
on
potential
impacts
of
epidemiological
uncertainties
interventions.
results
were
shared
with
public,
public
health
partners,
Centers
Disease
Control
Response
Team.
The
insights
situational
awareness
informed
decision-making
mitigate
disease
burden
(e.g.,
vaccination
strategies).
By
aggregating
from
teams,
rapidly
synthesized
times
great
uncertainty
conveyed
possible
trajectories
presence
emerging
variants.
Here
we
detail
several
use
cases
these
practice
communication,
including
assessments
whether
directly
or
indirectly
communication
guidance.
These
include
examples
where
comparisons
projected
outcomes
under
different
scenarios
used
inform
Advisory
Committee
Immunization
Practices
recommendations.
We
also
describe
challenges
lessons
learned
during
this
highly
beneficial
collaboration.
Epidemics,
Journal Year:
2024,
Volume and Issue:
47, P. 100775 - 100775
Published: May 24, 2024
Across
many
fields,
scenario
modeling
has
become
an
important
tool
for
exploring
long-term
projections
and
how
they
might
depend
on
potential
interventions
critical
uncertainties,
with
relevance
to
both
decision
makers
scientists.
In
the
past
decade,
especially
during
COVID-19
pandemic,
field
of
epidemiology
seen
substantial
growth
in
use
projections.
Multiple
scenarios
are
often
projected
at
same
time,
allowing
comparisons
that
can
guide
choice
intervention,
prioritization
research
topics,
or
public
communication.
The
design
is
central
their
ability
inform
questions.
this
paper,
we
draw
fields
analysis
statistical
experiments
propose
a
framework
epidemiology,
also
other
fields.
We
identify
six
different
fundamental
purposes
designs
(decision
making,
sensitivity
analysis,
situational
awareness,
horizon
scanning,
forecasting,
value
information)
discuss
those
structure
scenarios.
aspects
content
process
design,
broadly
all
settings
specifically
multi-model
ensemble
As
illustrative
case
study,
examine
first
17
rounds
from
U.S.
Scenario
Modeling
Hub,
then
reflect
future
advancements
could
improve
epidemiological
settings.
Epidemics,
Journal Year:
2024,
Volume and Issue:
47, P. 100757 - 100757
Published: March 5, 2024
The
Scenario
Modeling
Hub
(SMH)
initiative
provides
projections
of
potential
epidemic
scenarios
in
the
United
States
(US)
by
using
a
multi-model
approach.
Our
contribution
to
SMH
is
generated
multiscale
model
that
combines
global
metapopulation
modeling
approach
(GLEAM)
with
local
and
mobility
US
(LEAM-US),
first
introduced
here.
LEAM-US
consists
3142
subpopulations
each
representing
single
county
across
50
states
District
Columbia,
enabling
us
project
state
national
trajectories
COVID-19
cases,
hospitalizations,
deaths
under
different
scenarios.
age-structured,
multi-strain.
It
integrates
data
on
vaccine
administration,
human
mobility,
non-pharmaceutical
interventions.
contributed
all
17
rounds
SMH,
allows
for
mechanistic
characterization
spatio-temporal
heterogeneities
observed
during
pandemic.
Here
we
describe
mathematical
computational
structure
underpinning
our
model,
present
as
case
study
results
concerning
emergence
SARS-CoV-2
Alpha
variant
(lineage
designation
B.1.1.7).
findings
reveal
considerable
spatial
temporal
heterogeneity
introduction
diffusion
variant,
both
at
level
individual
combined
statistical
areas,
it
competes
against
ancestral
lineage.
We
discuss
key
factors
driving
time
required
rise
dominance
within
population,
quantify
significant
impact
had
effective
reproduction
number
level.
Overall,
show
able
capture
complexity
pandemic
response
US.
PLoS ONE,
Journal Year:
2023,
Volume and Issue:
18(1), P. e0280745 - e0280745
Published: Jan. 23, 2023
After
admission
to
hospital,
COVID-19
progresses
in
a
substantial
proportion
of
patients
critical
disease
that
requires
intensive
care
unit
(ICU)
admission.In
pragmatic,
non-blinded
trial,
387
aged
40-90
years
were
randomised
receive
treatment
with
SoC
plus
doxycycline
(n
=
192)
or
only
195).
The
primary
outcome
was
the
need
for
ICU
as
judged
by
attending
physicians.
Three
types
analyses
carried
out
outcome:
"Intention
treat"
(ITT)
based
on
randomisation;
"Per
protocol"
(PP),
excluding
not
treated
according
and
"As
treated"
(AT),
actual
received.
trial
undertaken
six
hospitals
India
high-quality
facilities.
An
online
application
serving
electronic
case
report
form
developed
enable
screening,
randomisation
collection
outcomes
data.Adherence
per
protocol
95.1%.
Among
all
participants,
77
(19.9%)
needing
admission.
In
three
analyses,
associated
relative
risk
reduction
(RRR)
absolute
(ARR):
ITT
31.6%
RRR,
7.4%
ARR
(P
0.063);
PP
40.7%
9.6%
0.017);
AT
43.2%
10.8%
0.007),
numbers
needed
treat
(NTT)
13.4
(ITT),
10.4
9.3
respectively.
Doxycycline
well
tolerated
single
patient
stopping
due
adverse
events.In
hospitalized
patients,
doxycycline,
safe,
inexpensive,
widely
available
antibiotic
anti-inflammatory
properties,
reduces
when
added
SoC.
Epidemics,
Journal Year:
2023,
Volume and Issue:
46, P. 100738 - 100738
Published: Dec. 29, 2023
Between
December
2020
and
April
2023,
the
COVID-19
Scenario
Modeling
Hub
(SMH)
generated
operational
multi-month
projections
of
burden
in
US
to
guide
pandemic
planning
decision-making
context
high
uncertainty.
This
effort
was
born
out
an
attempt
coordinate,
synthesize
effectively
use
unprecedented
amount
predictive
modeling
that
emerged
throughout
pandemic.
Here
we
describe
history
this
massive
collective
research
effort,
process
convening
maintaining
open
hub
active
over
multiple
years,
provide
a
blueprint
for
future
efforts.
We
detail
generating
17
rounds
scenarios
at
different
stages
pandemic,
disseminating
results
public
health
community
lay
public.
also
highlight
how
SMH
expanded
generate
influenza
during
2022-23
season.
identify
key
impacts
on
draw
lessons
improve
collaborative
efforts,
scenario
projections,
interface
between
models
policy.