Download EXACUTIVE SUMMARY The Project Objectives were to answer the

EXACUTIVE SUMMARY
The Project Objectives were to answer the following key questions:
1) Are there signs in the historical record of Landsat imagery of significant land-use, land-cover
changes in WNV outbreak areas over the last 30 years?
2) Can modern high resolution (Quickbird) imagery provide useful classified maps of WNV
outbreak areas?
3) Are there any signs of significant changes in habitat seasonality in and around WNV areas in
Europe over the last 20 years (AVHRR, coarse resolution data back to 1982)?
4) Can we relate habitat seasonality as detected by new generations of higher spatial resolution
multi-temporal satellites/sensors (e.g. Terra/MODIS and possibly MSG/SEVIRI) to seasonality
as detected by the older, lower resolution multi-temporal satellites (e.g. NOAA/AVHRR)?
5) Can we combine land-use and land-cover maps derived from Landsat (and Quickbird) with
the habitat seasonality information derived from AVHRR, MODIS or SEVIRI data to produce
spatially detailed risk maps of WNV in Europe?
6) In the light of answers to 1) to 5), above, can we identify any areas within the UK that may be
considered to be at risk of WNV establishment and spread?
Objectives 1 and 2 were not met because of the lack of any precise data on recent WNV outbreaks in
Europe (there was none during the project’s lifetime). Instead, historical data on WNV were collected
from a variety of sources, to form as complete a picture as possible of the WNV situation in Europe
over the last c. 30 years.
The 1982-1999 series of NOAA AVHRR global 8km imagery was temporal Fourier processed in
overlapping 2-year window segments and changes over time in the values of the various Fourier
components were examined. Significant changes were highlighted and mapped. The recorded WNV
outbreaks in Europe tended not to coincide with regions of significant change in most of the major
Fourier components. Results should be interpreted cautiously, however, since the AVHRR time series
was subject to instrumental and orbital drift over time. Nevertheless it seems that major WNV
outbreak areas in Europe have not been exposed to major environmental changes over the c. 20 year
period of analysis (Objective 3).
Temporal Fourier variables from the earlier NOAA satellites’ AVHRR sensors and the more recent
Terra and Aqua satellites’ MODIS sensor were extracted at a regular grid of points covering both the
European region in general and the UK in particular and were compared by linear regression. This
was to investigate whether the habitat seasonality captured by Fourier analysis is comparable in the
two sensor time series. There were significant correlations between AVHRR and MODIS Land
Surface Temperature (LST) and NDVI data, ranging from 0.54 to 0.98 for LST and 0.86 to 0.94 for
NDVI across Europe; the equivalent ranges for the UK alone were 0.50 to 0.91 for LST and 0.64 to
0.85 for NDVI. In general correlations of the timing of the annual cycle (phase 1) gave the weakest
values in each case (the lowest numbers given above, except in the case of UK NDVI, where the
lowest value was for NDVI maximum). (Objective 4).
Risk maps of WNV in Europe were prepared using the WNV database as the training set and the
series of temporal Fourier MODIS data, together with a few additional layers (rainfall derived from
microwave passive sensors or from instrumental records, digital elevation and human population
density), as predictors. 100 bootstrap samples were taken from this training set for each of three
cluster combinations (1 absence/1 presence; 2 absence/1 presence; 2 absence/2 presence) and a
non-linear discriminant analysis model was developed for each sample. The average of 100 models
for each cluster combination represents our ‘best guess’ risk map for WNV in Europe, and the variety
of variables selected across all bootstrap models indicates both the type and importance of key
variables in determining the distribution of WNV in Europe (Objective 5).
Risk maps developed under Objective 5 were examined for indications of risk areas within the UK.
These seem to be rather few and patchy, with a small concentration in East Anglia in one of the
models. Even here, however, the similarity of environmental conditions to those in which WNV
flourishes in Europe is slight. It appears that very few areas in the UK are similar to areas in Europe
from which WNV has been recorded. This does not mean that the UK is definitely not suitable for
WNV (a disease capable of exploiting a wide variety of ecological situations, as shown by its
expansion across N. America). The disease should perhaps go on a ‘watch list’ rather than an ‘alert
list’ for the UK (Objective 6).
Additional work done within this project, but not falling under any of the stated objectives, examined
the reasons for the differences between WNV epidemiology in N. America and Europe. Previous
work on the N. American situation had produced risk maps for the c. 70 species of mostly native (and
a few introduced) mosquito species in America that have been implicated in WNV transmission there.
These species have been classified as ornithophilic (exclusively bird-biting), mammalophilic
(mammal-biting) or bridge (biting both) vectors and occur in a wide variety of habitats. Conventional
wisdom suggests that WNV in N. America is transmitted to humans in situations where there is a
strong ornithophilic cycle (i.e. ornithophilic vectors) complemented by bridge vectors that ‘bring’ the
disease to the human host. This of course requires a spatial (i.e. environmental) co-incidence of
ornithophilic and bridge vectors. By examining the similarity of environmental conditions determining
the presence of the 70 N. American potential vector species it was possible to identify areas where
ornithophilic and bridge vectors occur together. It was thought that the same approach should be
applied to European mosquito vectors.
To this end, a database was constructed of the European mosquito species that have been implicated
as – or are considered to be - vectors of WNV in Europe (based on the Foresight review of WNV
produced by project staff). This database, of c. 30 species, was obtained through a comprehensive
search of the published literature, from key websites (such as the UK NBN gateway) and from
colleagues (e.g. Jolyon Medlock at the HPA), and was modelled at both high (1/120 th degree) and low
(1/15th degree) resolution, again using mostly MODIS data. The results were excellent in terms of
model performance, but very disappointing in terms of predicting species’ distributions, because the
point records of species known to be quite widespread in Europe are in fact very poor. No
compendium exists for Europe, showing the likely geographical distribution of the European species,
that is at all comparable to Darsie & Ward’s classic text ‘Identification and geographical distribution of
the mosquitoes in North America, North of Mexico’ that contains not only taxonomic descriptions of all
species but also maps of their geographical distribution in N. America. Doubtless Darsie & Ward’s
maps are inaccurate in places but they are far better than any we have for European vectors across
Europe (the nearest we have in Europe is Norbert Becker’s ‘Mosquitoes and their Control’, with a
second edition due from Springer in January 2010, but this appears to give mosquito distributions only
by list of European countries from which each species has been recorded). Nevertheless the
information we have for the European species was processed in the same way as that for the N.
American species and environmental ‘finger-prints’ of the species were extracted from the MODIS
satellite data. Dendrograms were produced on the basis of the environmental distances between
each species for the European mosquitoes and for both European and America mosquitoes together.
Within the dendrogram for all species combined the European species occupied a quite distinct
subset of environmental conditions (i.e. they appeared more or less contiguously on the joint
dendrogram), whilst the American species occupied a much wider range of environmental conditions.
In addition, there appears to be a more frequent coincidence of ornithophilic and bridge vectors in N.
America than in Europe (partly due to the fact that Europe appears to have proportionately fewer,
definite ornithophilic species). These results go some way towards explaining the different
epidemiologies of WNV in Europe compared with America, but the Report emphasises that this
conclusion may change when we know more about European mosquitoes.
The Report concludes with some suggestions for future investigations. Key here must be to find out
more about the geographic distribution of European mosquitoes – something which individual
countries in Europe (e.g. Belgium, The Netherlands) are already addressing – along with more details
of their biology (feeding behaviour etc.) and ecology. It seems that we are now entering an era when
we have far more, and more detailed, environmental data than ever before (from satellites) but are
held up by a lack of knowledge of what is happening on the ground. Satellite data can never replace
good field data but they can make field sampling more efficient (by directing where sampling should
take place) and they can turn field data into detailed risk maps of both vectors and diseases. The
better the field data, the better the resulting risk maps.
Acknowledgements
Victoria Sanderson was the RA on this project during the first few months and was the main writer of
the Foresight Report on West Nile Virus. David Benz took over the RA role in the project at a later
stage. I am especially grateful to him for all his help with the wealth of image processing and
modelling involved. Finally I thank DEFRA for its financial support and understanding in allowing an
extension to complete the work.