Geoscience Reference
In-Depth Information
3.4.3.2.
The case of the Gulf of Bengal, India and Bangladesh
A statistical model has been constructed relying on data on the
dynamic of cholera in Calcutta (India) and Matlab (Bangladesh) over
the period 1998-2006 [CON 08]. This model uses monthly data
provided by remote sensing of the SST and Chl
a
in the Gulf of
Bengal as well as pluviometry.
Because these data evolve seasonally, it is necessary to research
these anomalies, that is to say the events that are not linked to seasonal
cycles. These anomalies, calculated using averages for a given month
and over the entire period (SST, Chl
a
and pluviometry) are removed
from the data for each month. The authors also take account, in a
provisional model of the cholera dynamic, of a latency period of one
to two months between the variations of the two parameters (SST and
Chl
a
) and the epidemiology of the disease in the population. One of
the remarkable results of these studies shows that an increase of
1 mg/m
3
of the average anomaly of Chl
a
explains an increase of
approximately 32% of cholera cases in Matlab with a latency time of a
month.
By using such a predictive model on a regional scale (the Gulf of
Bengal), it is possible to predict the health risks of cholera epidemics
associated with climatic conditions, and above all, with their
variations.
3.4.4.
Application of remote monitoring to cyanobacteria
In Europe, cyanobacteria are the subject of particular monitoring
(European directive 76160/CEE and 2006-7/CE) in order to reduce the
population's exposure, which most often occurs when bathing.
The
bacteria's presence is locatable visually by a change in water color and
the formation of filaments.
This detection of change can be carried out
due to satellite sensors dedicated to the observation of the water color
(MERIS). In effect, the cyanobacteria have a spectral signature
(Figure 3.4) measurable by remote sensing, enabling cyanobacteria
blooms to be observed (Figure 3.5).
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