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A GIS-based modeling of environmental health risks in populated areas of Port-au-prince, Haiti

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par Myrtho Joseph
University of Arizona - Master in Natural Resources Information System 1987

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This study took place in a context of unavailability and/or inaccessibility of data. Even the basic spatial information could not be obtained from official sources on the Internet. The web pages of the institutions in charge of the production and distribution of spatial data, or information in general were projected to be constructed soon or were under perpetual construction. It took a great amount of effort to generate most of the features through a long and arduous process of digitization of most of the data. Often assumptions had to be made to avoid having to collect more data. The difficulties encountered reveal the requirements for a greater flexibility of data exchange conditions between institutions, and between institution and the public, as well as the needs for a better integration of spatial data available. Furthermore, it is a pressing demand to produce geographic information at higher resolution in a way to enable researchers to address issues at the level of communities. Very general spatial information can not lead to anything but this congenital practice of confounding semantics and pragmatism. Information, particularly in such disinherited and poor environment as Haiti, may not be used to confer power to individuals or institutions. Rather it may constitute a power to promote changes starting at individual and community levels. We advocate cost efficient strategies to produce spatial data and make them available to anyone anywhere through the Internet, even for purchasing.

This study, a first of its kind for Port-au-Prince, attempted to delineate at-risk neighborhoods for nine environmental health hazards. Though traditionally the focus has been oriented toward natural hazards, which in nature are more discreet and whose manifestation leads to direct observation and quantification, this study reveals that health hazards are not a mental invention. These hazards are continuous, constant, perilous, and daily affect a large part of the population. The lack of information and the complexity posed by quantitative assessment must not lead to the minimization or the abstraction of such a precarious and deadly phenomenon. This work may represent a first geographic inventory of environmental health-related hazards in Port-au-Prince. By relating its occurrence to the underlying causes, it offers the ability to intervene in specific areas and targeting a specific factor. To this respect, we strongly encourage the use of the SDE as a suitable spatial study unit for the collection of data pertaining to a large array of fields. This approach can strongly facilitate the insight of phenomena at small community level and promote participation.

High housing density, traffic, waste, streams, and the sea coast represent the main sources or pollution in Port-au-Prince. However the impact of the other sources must not be overlooked. They are very serious in the specific environment and institutional setting of Port-au-Prince.

While the geographic delineation of the hazards may not be exact in its spatial shape and extent, one confidence remains: the issues addressed exist and exist in the neighborhoods indicated. Without any field data the categorization brought out by the ordinal approach remains subjective and depends on the researcher's perception of the reality under study. Nevertheless it has the merits of pinpointing areas where environmental health risks might reasonably be incident and offers the ability to make different assumptions and adjusting the results on the fly. Various combination and reclassification techniques likely to influence the output were assessed and demonstrated the high sensitivity of the model to change in its parameters.

As a specific outcome of this study, the prime interest of any program aiming to reduce population's vulnerability to health hazards should focus on these areas identified as at very high risk. They are located particularly in neighborhoods with very high housing density, which also host an array of other environmental hazards such as air pollution from traffic, waste, water bodies and the coastline. By relating these risked areas specific hazards that threaten them the strategy to adopt becomes less ambiguous.

This study is not complete without a ground truth survey consisting of collecting information and taking specific measurements on various pollution factors included in the model. Very limited in time, budget and other resources, the scope of this study would not allow such investigation. Information gathered on the field not only would allow validating the results but equally would enable establishing strong rationale for hazards delineation and vulnerability scaling. At least the outcome is deemed a first but important step by defining specific area where distinct interventions can be done.

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