Vaccination
reduces
the
overall
burden
of
COVID-19,
while
its
allocation
procedure
may
introduce
additional
health
inequality,
since
populations
characterized
with
certain
social
vulnerabilities
have
received
less
vaccination
and
been
affected
more
by
COVID-19.
We
used
structural
equation
modeling
to
quantitatively
evaluate
extent
which
disparity
would
amplify
where
it
functioned
as
a
mediator
in
effect
pathways
from
COVID-19
mortality.We
USA
nationwide
county
(n
=
3112,
99%
total)
level
data
during
2021
an
ecological
study
design.
Theme-specific
rankings
vulnerability
index
published
CDC
(latest
2018,
including
socioeconomic
status,
household
composition
&
disability,
minority
status
language,
housing
type
transportation)
were
exposure
variables.
coverage
rate
(VCR)
was
variable,
case
fatality
(CFR)
John
Hopkinson
University,
outcome
variable.Greater
language
inversely
associated
VCR,
together
explaining
11.3%
variance
VCR.
Greater
disability
positively
CFR,
VCR
10.4%
CFR.
Our
mediation
analysis,
based
on
mid-year
(30th
June
2021),
found
that
37.6%
(mediation/total
effect,
0.0014/0.0037),
10%
(0.0003/0.0030)
100%
(0.0005/0.0005)
effects
involving
respectively,
mediated
As
whole,
significantly
counted
for
30.6%
CFR
disparity.
Such
seen
throughout
2021,
proportions
ranging
12
32%.Allocation
led
inequality
respect
mortality.
Viable
public
interventions
should
be
taken
guarantee
equitable
deployment
healthcare
recourses
across
different
population
groups.
JMIR Formative Research,
Год журнала:
2025,
Номер
9, С. e62802 - e62802
Опубликована: Фев. 11, 2025
Geospatial
data
science
can
be
a
powerful
tool
to
aid
the
design,
reach,
efficiency,
and
impact
of
community-based
intervention
trials.
The
project
titled
Take
Care
Texas
aims
develop
test
an
adaptive,
multilevel,
increase
COVID-19
testing
vaccination
uptake
among
vulnerable
populations
in
3
regions:
Harris
County,
Cameron
Northeast
Texas.
We
aimed
novel
procedure
for
adaptive
selections
census
block
groups
(CBGs)
include
randomized
trial
project.
CBG
selection
was
conducted
across
regions
over
17-month
period
(May
2021
October
2022).
developed
persistent
recent
burden
metrics,
using
real-time
SARS-CoV-2
monitoring
capture
dynamic
infection
patterns.
To
identify
populations,
we
also
CBG-level
community
disparity
index,
12
contextual
social
determinants
health
(SDOH)
measures
from
US
data.
In
each
round,
determined
priority
CBGs
based
on
their
ensuring
geographic
separation
minimize
"spillover."
Community
input
feedback
local
partners
workers
further
refined
selection.
selected
were
then
into
2
arms-multilevel
just-in-time
intervention-and
1
control
arm,
covariate
randomization,
at
1:1:1
ratio.
interactive
dashboards,
which
included
maps
displaying
locations
community-level
information,
inform
process
guide
delivery.
Selection
randomization
occurred
10
rounds.
A
total
120
followed
stepped
planning
interventions,
with
60
30
counties.
presented
substantial
temporal
changes
variations
CBGs.
exhibited
some
common
geographical
patterns
but
displayed
distinct
variations,
particularly
different
time
points
throughout
this
study.
This
underscores
importance
incorporating
both
SDOH
process.
integrated
geospatial
enhance
design
delivery
trial.
Adaptive
effectively
prioritized
most
in-need
communities
allowed
rigorous
evaluation
interventions
multilevel
methodology
has
broad
applicability
adapted
other
public
prevention
programs,
providing
improving
population
addressing
disparities.
Vaccination
reduces
the
overall
burden
of
COVID-19,
while
its
allocation
procedure
may
introduce
additional
health
inequality,
since
populations
characterized
with
certain
social
vulnerabilities
have
received
less
vaccination
and
been
affected
more
by
COVID-19.
We
used
structural
equation
modeling
to
quantitatively
evaluate
extent
which
disparity
would
amplify
where
it
functioned
as
a
mediator
in
effect
pathways
from
COVID-19
mortality.We
USA
nationwide
county
(n
=
3112,
99%
total)
level
data
during
2021
an
ecological
study
design.
Theme-specific
rankings
vulnerability
index
published
CDC
(latest
2018,
including
socioeconomic
status,
household
composition
&
disability,
minority
status
language,
housing
type
transportation)
were
exposure
variables.
coverage
rate
(VCR)
was
variable,
case
fatality
(CFR)
John
Hopkinson
University,
outcome
variable.Greater
language
inversely
associated
VCR,
together
explaining
11.3%
variance
VCR.
Greater
disability
positively
CFR,
VCR
10.4%
CFR.
Our
mediation
analysis,
based
on
mid-year
(30th
June
2021),
found
that
37.6%
(mediation/total
effect,
0.0014/0.0037),
10%
(0.0003/0.0030)
100%
(0.0005/0.0005)
effects
involving
respectively,
mediated
As
whole,
significantly
counted
for
30.6%
CFR
disparity.
Such
seen
throughout
2021,
proportions
ranging
12
32%.Allocation
led
inequality
respect
mortality.
Viable
public
interventions
should
be
taken
guarantee
equitable
deployment
healthcare
recourses
across
different
population
groups.
