[Dengue, geoprocessing, and socioeconomic and environmental indicators: a review].
OBJECTIVE
To further understand the disease behavior of dengue by analyzing studies on dengue and geoprocessing, as well as socioeconomic and environmental indicators.


METHODS
MEDLINE, SciELO, and Lilacs databases, as well as the CAPES dissertation databank, were searched using the following key words: dengue, geographic information system, spatial analysis, geoprocessing, remote sensing, and socioenvironmental indicators. A manual search of the bibliographies of select articles was also performed. All studies published in English, Portuguese, or Spanish, through December 2007, that focused on dengue, geoprocessing, and socioeconomic and environmental indicators were included. The relevant articles were grouped according to type (serologic surveys or secondary data analyses) and spatial analysis unit (municipality, health district, neighborhood, administrative region, census tracts, and city blocks).


RESULTS
Twenty-two studies from Latin America (19 from Brazil) were evaluated. Six were serologic surveys and 16 employed secondary data. Geographic information systems were employed in one survey, and 11 used secondary data analyses. Spatial clustering was similar in both types of studies. Poverty was not a major risk factor for the disease. Spatial heterogeneity of living conditions and incidence was reported by 15 of 16 studies with secondary data.


CONCLUSIONS
Since the complexity of dengue is closely tied to the ecological characteristics of the environment, studies based on spatial clusters plus local environmental determinants provide a more comprehensive view of the disease. These studies also allow for the identification of spatial heterogeneity, shown to be a key to understanding how dengue epidemics develop.
Flauzino
Regina Fernandes
RF
Universidade Federal Fluminense (UFF), Departamento de Epidemiologia, Rio de Janeiro, Brazil. rflauzino@uol.com.br
Souza-Santos
Reinaldo
R
Oliveira
Rosely Magalhães
RM
D003715:Dengue / Q000453:epidemiology*; D004777:Environment; D040362:Geographic Information Systems; D006801:Humans; D007843:Latin America / Q000453:epidemiology; D012959:Socioeconomic Factors