Estimating Mycobacterium tuberculosis transmission in a South African clinic: Spatiotemporal model based on person movements
PLoS Computational Biology,
Год журнала:
2025,
Номер
21(2), С. e1012823 - e1012823
Опубликована: Фев. 18, 2025
The
risk
of
Mycobacterium
tuberculosis
(Mtb)
transmission
can
be
high
in
crowded
clinics.
We
developed
a
spatiotemporal
model
airborne
Mtb
based
on
the
Wells-Riley
equation.
collected
environmental,
clinical
and
person-tracking
data
South
African
clinic
during
COVID-19,
when
community
or
surgical
masks
were
compulsory
ventilation
was
increased.
matched
person
movements
with
records
to
identify
location
infectious
TB
patients.
modeled
concentration
doses
(quanta)
estimated
individual
infection.
Over
five
days,
video
sensors
tracked
1,438
attendees.
CO
2
levels
low
(median
431
ppm,
IQR
406
ppm–458
ppm);
quanta
higher
morning
than
afternoon,
highest
waiting
room.
infection
per
attendee
0.05%
(80%-credible
interval
(CrI)
0.01%–0.06%).
It
increased
number
close
contacts
patients
time
spent
clinic,
1.3-fold
(95%-CrI
1.2–1.4)
scenarios
without
mask
use
2.1-fold
0.9–5.0)
pre-pandemic
rates,
emphasizing
importance
ventilation.
Spatiotemporal
modeling
high-risk
areas
evaluate
impact
control
measures
Язык: Английский
Prevalence and Determinants of Tuberculosis Mantoux Test on Children Under Five in Banyumas District
E3S Web of Conferences,
Год журнала:
2025,
Номер
609, С. 04008 - 04008
Опубликована: Янв. 1, 2025
The
incidence
of
children
suffering
from
Tuberculosis
(TB)
is
increasing.
A
history
contact
between
adult
TB
patients
and
an
important
factor
in
the
transmission
to
children.
This
research
aims
determine
tuberculosis's
prevalence
determinants
under
five
household
contacts
Banyumas
District,
Central
Java.
design
this
quantitative
with
a
cross-sectional
approach.
sample
study
was
5
years
age
(toddlers)
Regency
(District
South
Purwokerto
Sumbang)
whose
homes
there
were
positive
patient
tuberculosis
willing
undergo
Mantoux
test
as
many
48
toddlers.
Data
collection
carried
out
using
questionnaires.
analysis
univariate,
bivariate,
multivariate
analysis.
among
270/1000.
most
influential
variable
on
health
conditions
(lumps
glands)
p-value
0.009
OR
=
83.204
sleeping
same
room
(
0.035
14.246).
results
concluded
that
risk
toddler
condition
room.
Язык: Английский
Infection prevention and control measures during the COVID-19 pandemic and airborne tuberculosis transmission during primary care visits in South Africa
International Journal of Infectious Diseases,
Год журнала:
2025,
Номер
unknown, С. 107921 - 107921
Опубликована: Май 1, 2025
Язык: Английский
Occupational exposure monitoring of airborne respiratory viruses in outpatient medical clinics
Aerosol Science and Technology,
Год журнала:
2024,
Номер
unknown, С. 1 - 21
Опубликована: Окт. 23, 2024
Exposure
to
airborne
respiratory
viruses
can
be
a
health
hazard
in
occupational
settings.
In
this
study,
air
sampling
was
conducted
from
January
March
2023
two
outpatient
medical
clinics—one
primary
care
clinic
and
one
dedicated
the
diagnosis
treatment
of
illnesses—for
purpose
assessing
virus
presence.
Work
involved
operation
BioSpot-VIVASTM
as
stationary
sampler
deployment
NIOSH
BC-251
bioaerosol
samplers
either
devices
or
personal
worn
by
staff
members.
Results
were
correlated
with
deidentified
clinical
data
patient
testing.
Samples
seven
days
analyzed
for
SARS-CoV-2,
influenza
A
H1N1
H3N2
viruses,
B
Victoria-
Yamagata-lineage
an
overall
17.5%
(17/97)
positivity
rate.
Airborne
predominated
particles
aerodynamic
diameters
1–4
μm
recovered
similar
quantities
both
clinics.
(17.4%,
15/86)
VIVAS
(18.2%,
2/11)
collected
detectable
at
rates,
but
more
numerous
provided
greater
insight
into
presence
across
spaces
job
categories.
60%
samples
reception
areas
contained
virus,
exposure
significantly
(p
=
0.0028)
occurred
desks
compared
"mobile"
categories
providers
nurses.
Overall,
study
provides
valuable
insights
impacts
mitigation
controls
tailored
reducing
highlights
need
continued
diligence
toward
risk
Язык: Английский
Social contact patterns and their impact on the transmission of respiratory pathogens in rural China
Infectious Disease Modelling,
Год журнала:
2024,
Номер
10(2), С. 439 - 452
Опубликована: Дек. 10, 2024
Social
contact
patterns
significantly
influence
the
transmission
dynamics
of
respiratory
pathogens.
Previous
surveys
have
quantified
human
social
patterns,
yielding
heterogeneous
results
across
different
locations.
However,
significant
gaps
remain
in
understanding
rural
areas
China.
We
conducted
a
pioneering
study
to
quantify
Anhua
County,
Hunan
Province,
China,
from
June
October
2021,
when
there
were
minimal
coronavirus
disease-related
restrictions
area.
Additionally,
we
simulated
epidemics
under
assumptions
regarding
relative
risks
various
types
(e.g.,
indoor
versus
outdoor,
and
physical
non-physical).
Participants
reported
an
average
12.0
contacts
per
day
(95%
confidence
interval:
11.3-12.6),
with
higher
number
compared
outdoor
contacts.
The
was
associated
socio-demographic
characteristics,
including
age,
education
level,
income,
household
size,
travel
patterns.
Contact
assortative
by
age
varied
based
on
type
reproduction
number,
daily
incidence,
infection
attack
rate
remarkably
stable.
found
many
intergenerational
households
that
pose
challenges
preventing
controlling
infections
among
elderly
Our
also
underscores
importance
integrating
pattern
data
into
epidemiological
models
provides
guidance
public
health
authorities
other
major
stakeholders
preparing
responding
infectious
disease
threats
Язык: Английский
Social contact patterns and their impact on the transmission of respiratory pathogens in rural China
Опубликована: Окт. 22, 2024
Abstract
Introduction
Social
contact
patterns
significantly
influence
the
transmission
dynamics
of
respiratory
pathogens.
Previous
surveys
have
quantified
human
social
patterns,
yielding
heterogeneous
results
across
different
locations.
However,
significant
gaps
remain
in
understanding
rural
areas
China.
Methods
We
conducted
a
pioneering
study
to
quantify
Anhua
County,
Hunan
Province,
China,
from
June
October
2021,
when
there
were
minimal
coronavirus
disease-related
restrictions
area.
Additionally,
we
simulated
epidemics
under
assumptions
regarding
relative
risks
various
types
(e.g.,
indoor
versus
outdoor,
and
physical
non-physical).
Results
Participants
reported
an
average
12.0
contacts
per
day
(95%
confidence
interval:
11.3–12.6),
with
higher
number
compared
outdoor
contacts.
The
was
associated
socio-demographic
characteristics,
including
age,
education
level,
income,
household
size,
travel
patterns.
Contact
assortative
by
age
varied
based
on
type
reproduction
number,
daily
incidence,
infection
attack
rate
remarkably
stable.
Discussion
found
many
intergenerational
households
that
pose
challenges
preventing
controlling
infections
among
elderly
Our
also
underscores
importance
integrating
pattern
data
into
epidemiological
models
provides
guidance
public
health
authorities
other
major
stakeholders
preparing
responding
infectious
disease
threats
Язык: Английский