The malaria is a parasitic disease caused by Protozoa of genus Plasmodium that
completes its complex cycle of development alternating between human hosts and
mosquitoes of the genus Anopheles. In the world-wide context, it constitutes a serious
problem of public health that mainly affects the developing countries of tropical and
subtropical climate. In Brazil, one gives credit that 99.5% of the registered cases of
malaria meet in the Legal Amazonian. Much of the success of this complaint in this
region must it biological and environmental factors that favor levels high of vectors,
beyond social factors that compromise the efforts to control the disease. Thus, the
objective of this work was to study the profile epidemiologist of the malaria in Pará,
during a historical series (1999 - 2003), analyzing the influence of environmental and
socioeconomic variable on the prevalence of the cases. For such the annual parasitic
indices (IPA) of each city had been calculated and, through a SIG, these data they had
been georreferencied and studied of temporal and spatial form. Data on the
deforestation in the State had been analyzed, through a regression for permutation, to try
to explain the temporal variation of the malaria. For the spatial study (multiple
regression) the influence of the variable: temperature, rainfall, altitude, education,
longevity and income; was tested on the prevalence of the malaria. In the secular study
the malaria presented a decreasing trend in the State, however, only 31 cities had
presented the same trend, did not have increasing trend, the 112 remaining cities had
presented steady trend. Moreover, many cities had alternated increase and reduction of
the cases throughout the series, having indicated a good action of control, but a weak
performance of the monitoring. In this context the deforestation seems to influence the
secular series of the malaria, was gotten resulted significant in two (2001 and 2002) of
the three studied years. In the space study the adopted final model, although a low
clarifying power (R²=0.31), presented three significant variable: number of dry months,
income and education. However, the result of the two first ones is not presented of a
direct form, being reflected of other activities. Although the scale adopted and of
problems in the aggregation of the data (they are only available for city), this work
presents resulted excellent that can assist the managers of the health (or endemic
diseases) to direct action of control for the pointed areas as critical, acting in the factors
of bigger significance, thus getting better exploitation of available the human resources
and material.
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