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- Climate change
cannot explain
the upsurge of
tick-borne
encephalitis
in the
baltics.: PLoS ONE, Vol.
2
(2007)BACKGROU
ND: Pathogens
transmitted by
ticks cause
human disease
on a greater
scale than any
other
vector-borne
infections in
Europe, and
have increased
dramatically
over the past
2-3 decades.
Reliable
records of
tick-borne
encephalitis
(TBE) since
1970 show an
especially
sharp upsurge
in cases in
Eastern Europe
coincident
with the end
of Soviet
rule,
including the
three Baltic
countries,
Estonia,
Latvia and
Lithuania,
where national
incidence
increased from
1992 to 1993
by 64, 175 and
1,065%,
respectively.
At the county
level within
each country,
however, the
timing and
degree of
increase
showed marked
heterogeneity.
Climate has
also changed
over this
period,
prompting an
almost
universal
assumption of
causality. For
the first
time, we
analyse
climate and
TBE
epidemiology
at
sufficiently
fine spatial
and temporal
resolution to
question this
assumption.
METHODOLOGY/PR
INCIPAL
FINDING:
Detailed
analysis of
instrumental
records of
climate has
revealed a
significant
step increase
in spring-time
daily maximum
temperatures
in 1989. The
seasonal
timing and
precise level
of this
warming were
indeed such as
could promote
the
transmission
of TBE virus
between larval
and nymphal
ticks
co-feeding on
rodents. These
changes in
climate,
however, are
virtually
uniform across
the Baltic
region and
cannot
therefore
explain the
marked
spatio-tempora
l
heterogeneity
in TBE
epidemiology.
CONCLUSIONS/SI
GNIFICANCE:
Instead, it is
proposed that
climate is
just one of
many different
types of
factors, many
arising from
the
socio-economic
transition
associated
with the end
of Soviet
rule, that
have acted
synergisticall
y to increase
both the
abundance of
infected ticks
and the
exposure of
humans to
these ticks.
Understanding
the precise
differential
contribution
of each factor
as a cause of
the observed
epidemiologica
l
heterogeneity
will help
direct control
strategies.
Source: PLoS ONE, Vol. 2 (2007) - Deriving
meteorological
variables
across Africa
for the study
and control of
vector-borne
disease: a
comparison of
remote sensing
and spatial
interpolation
of climate.: Trop Med Int
Health, Vol.
4, No. 1.
(January
1999), pp.
58-71.This
paper presents
the results of
an
investigation
into the
utility of
remote sensing
(RS) using
meteorological
satellites
sensors and
spatial
interpolation
(SI) of data
from
meteorological
stations, for
the prediction
of spatial
variation in
monthly
climate across
continental
Africa in
1990.
Information
from the
Advanced Very
High
Resolution
Radiometer
(AVHRR) of the
National
Oceanic and
Atmospheric
Administration
's (NOAA)
polar-orbiting
meteorological
satellites was
used to
estimate land
surface
temperature
(LST) and
atmospheric
moisture. Cold
cloud duration
(CCD) data
derived from
the High
Resolution
Radiometer
(HRR) on-board
the European
Meteorological
Satellite
programme's
(EUMETSAT)
Meteosat
satellite
series were
also used as a
RS proxy
measurement of
rainfall.
Temperature,
atmospheric
moisture and
rainfall
surfaces were
independently
derived from
SI of
measurements
from the World
Meteorological
Organization
(WMO) member
stations of
Africa. These
meteorological
station data
were then used
to test the
accuracy of
each
methodology,
so that the
appropriatenes
s of the two
techniques for
epidemiologica
l research
could be
compared. SI
was a more
accurate
predictor of
temperature,
whereas RS
provided a
better
surrogate for
rainfall; both
were equally
accurate at
predicting
atmospheric
moisture. The
implications
of these
results for
mapping short
and long-term
climate change
and hence
their
potential for
the study and
control of
disease
vectors are
considered.
Taking into
account
logistic and
analytical
problems,
there were no
clear
conclusions
regarding the
optimality of
either
technique, but
there was
considerable
potential for
synergy.
Source: Trop Med Int Health, Vol. 4, No. 1. (January 1999), pp. 58-71. - Predicting the
distribution
of tsetse
flies in West
Africa using
temporal
Fourier
processed
meteorological
satellite
data.: Ann Trop Med
Parasitol,
Vol. 90, No.
3. (June
1996), pp.
225-241.An
example is
given of the
application of
remotely-sense
d, satellite
data to the
problems of
predicting the
distribution
and abundance
of tsetse
flies in West
Africa. The
distributions
of eight
species of
tsetse,
Glossina
morsitans, G.
longipalpis,
G. palpalis,
G.
tachinoides,
G. pallicera,
G. fusca, G.
nigrofusca and
G. medicorum
in Côte
d'Ivoire and
Burkina Faso,
were analysed
using
discriminant
analysis
applied to
temporal
Fourier-proces
sed surrogates
for
vegetation,
temperature
and rainfall
derived from
meteorological
satellites.
The vegetation
and
temperature
surrogates
were the
normalized
difference
vegetation
index and
channel-4-brig
htness
temperature,
respectively,
from the
advanced,
very-high-reso
lution
radiometers on
board the
National
Oceanic and
Atmospheric
Administration
's
polar-orbiting
,
meteorological
satellites.
For rainfall
the surrogate
was the
Cold-Cloud-Dur
ation (CCD)
index derived
from the
geostationary,
Meteosat
satellite
series. The
presence or
absence of
tsetse was
predicted with
accuracies
ranging from
67%-100% (mean
= 82.3%). A
further
data-set, for
the abundance
of five tsetse
species across
the northern
part of Côte
d'Ivoire (an
area of about
140,000 km2),
was analysed
in the same
way, and
fly-abundance
categories
predicted with
accuracies of
30%-100% (mean
= 73.0%). The
thermal data
appeared to be
the most
useful of the
predictor
variables,
followed by
vegetation and
rainfall
indices.
Refinements of
the analytical
technique and
the problems
of extending
the
predictions
through space
and time are
discussed.
Source: Ann Trop Med Parasitol, Vol. 90, No. 3. (June 1996), pp. 225-241. - Remotely
sensed
surrogates of
meteorological
data for the
study of the
distribution
and abundance
of arthropod
vectors of
disease.: Ann Trop Med
Parasitol,
Vol. 90, No.
1. (February
1996), pp.
1-19.This
paper gives an
overview of
how certain
meteorological
data used in
studies of the
population
dynamics of
arthropod
vectors of
disease may be
predicted
using remotely
sensed,
satellite
data. Details
are given of
the stages of
processing
necessary to
convert
digital data
arising from
satellite
sensors into
ecologically
meaningful
information.
Potential
sources of
error in these
processing
steps are also
highlighted.
Relationships
between
ground-measure
d
meteorological
variables
(saturation
deficit,
ground
temperature
and rainfall)
and data from
both the
National
Oceanic and
Atmospheric
Administration
's,
polar-orbiting
,
meteorological
satellites and
the
geostationary,
Meteosat
satellite are
defined and
examples
detailed for
Africa.
Finally, the
current status
of existing
satellite
platforms and
future
satellite
missions are
reviewed and
potential data
availability
discussed. How
such
satellite-base
d predictions
have proved
valuable in
understanding
the
distribution
of tsetse fly
species in
Côte d'Ivoire
and Burkina
Faso will be
the subject of
a future
review.
Source: Ann Trop Med Parasitol, Vol. 90, No. 1. (February 1996), pp. 1-19. - Temperature
and
precipitation
variability in
Italy in the
last two
centuries from
homogenised
instrumental
time series: International
Journal of
Climatology,
Vol. 26, No.
3. (2006), pp.
345-381.The
Italian
monthly
temperature
(mean, maximum
and minimum)
and
precipitation
secular data
set was
updated and
completely
revised.
Station
density and
metadata
availability
were greatly
improved and
the series
were subjected
to a detailed
quality
control and
homogenisation
procedure. The
data
homogenisation
is described
in detail. The
bias affecting
original data
is quantified
by studying
the temporal
evolution of
the mean
adjustments
applied to the
series and
examined in
the light of
the stations
history. The
results stress
the importance
of
homogenisation
in climate
change
studies.The
final data set
was clustered
into
climatically
homogeneous
regions by
means of a
Principal
Component
Analysis.
Yearly and
seasonal trend
analyses were
performed both
on regional
average series
and on the
mean Italian
series. The
results
highlight a
positive trend
for mean
temperature of
about 1 K per
century all
over Italy; it
is generally
higher for
minimum
temperature
than for the
maximum
temperature.
The
progressive
application of
trend analysis
shows that, in
the last 50
years,
behaviour is
the opposite;
the maximum
temperature
trend being
stronger than
that of the
minimum
temperature.
This has led
to a negative
trend in the
daily
temperature
range that for
the last 50
years has
become
positive.
Precipitation
shows a
decreasing
tendency, even
if low and
rarely
significant,
the negative
trend being
only 5% per
century on a
yearly basis.
Copyright ©
2006 Royal
Meteorological
Society.
Source: International Journal of Climatology, Vol. 26, No. 3. (2006), pp. 345-381.
If you would like to find additional social bookmark based links on the topic of Meteorology we recommend the Open Tag Directory > Meteorology. If you would like to find related tags we recommend Tag Patterns > Meteorology.
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