Baudouhat, Max Jacob
à
SYSTEME D'INFORMATION GEOGRAPHIQUE
POUR LA LUTTE CONTRE LA MALADIE DU SOMMEIL
EN COTE D'IVOIRE (SIG-THA)
Max-Jacob BAUDOUHAT*, Yatié DIOMANDE*"*, Kouadio KONAN", Eric BAHINTCHIE*
Jean-Pierre HERVOUET**
*Centre de Cartographie et de Télédétection (CCT)
Bureau National d'Etudes Techniques et de Développement (BNETD)
bahintch@bnetd.sita.net
**Institut Pierre Richet (IPR)
Organisation de Coordination et de Coopération pour la lutte contre les Grandes Endémies (OCCGE)
hervouet@bouake.ird.ci
Inter-technical Commission IC-24
ABSTRACT
In the course of the last few decades, some outstanding technics of fighting against sleeping sickness have been
implemented. However, the situationrelated to this endemo-epidemic has never been so dramatic. Today, more than
55,000,000 people ara exposed to the evil in 36 vulnerable sub-saharan Africa, particularly in Cóte d'Ivoire. The
World Health Organisation thinks that 300,0000 people are stuck down by this deadly disease (1994 estimation). In
addition, the dynamics of this pathology, in absence of detection and care , has a real danger hung heavily on the
economies of the countries concerned and particularly on the plantation economies.
In order to allow the medical authorities to identify, to mark and to form into hearchchy the areas likely to be stuck
down by the disease and thus to set up a proper medical supervision of this areas so as to minimize the risks, CCT and
IPR have developped a geographical investigation system made up of the following four modules :
A descriptive module, whose objective is to make the medical authorities to be aware of the very existence of the
disease in Cóte d'Ivoire, thanks to the epidemiological research carried out by IPR and IRD on many known sources.
In fact, due to lack detection capacity, this disease is most of the time said to be eradicated.
An Explanatory Module permitting, thanks to those data analysis in their geographical context cartographed at scale of
1: 50,000, to put into relif the correlation between the geographical topology ( geo-type) of the areas concerned and the
prevalence of the disease (like for example, camp density and the growth rate of the population, etc);
A predictive module, whose objectif is to pre-identify the risk areas and to quantify this risk, on the basis f the geo-
type in the region of supervision; the risk factor which is simply based on five risk conditions that estimate exploits the
pertinent geographical data from SPOT satellite pictures and data from population and housing a census.
And decision support module capable of facilitating the organization of the logistics and human means to be carried
out so as to eradicate the disease ( detection planning and organization, care, campains, etc ).
The three first modules of the system have been developped with ESRI Arc View and its Spatial Analyst extension,
and CartoMapFlux [SERTIT-France]. The decision support module is to be implemented in with ESRI Network
analyst. A Microsoft ACCESS database contains the epidemiological and demographical information.
156 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.
