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Revista de Saúde Pública

Print version ISSN 0034-8910

Abstract

RESENDES, Ana Paula da Costa; SILVEIRA, Nelson Artur Prado Rodrigues da; SABROZA, Paulo Chagastelles  and  SOUZA-SANTOS, Reinaldo. Determination of priority areas for dengue control actions. Rev. Saúde Pública [online]. 2010, vol.44, n.2, pp.274-282. ISSN 0034-8910.  http://dx.doi.org/10.1590/S0034-89102010000200007.

OBJECTIVE: To identify areas at risk of dengue transmission by means of cluster analysis. METHODS: A cluster analysis in which the primary analysis units were the 48 districts of the municipality of Niterói, Southeastern Brazil, was conducted. The districts were grouped into six strata according to sociodemographic conditions, using the k-means cluster analysis method. After defining the strata, the incidence of dengue was calculated for each stratum in relation to four different periods: 1998 - 2000; 2001; 2002; 2003 - 2006. RESULTS: The analysis on the incidence showed that the rates for the last three study periods were greatest in the stratum 2.1, which had the worst sanitation infrastructure conditions and high population increases, and in stratum 3.1, which had the highest percentage of shantytowns. Stratum 1.2 presented the lowest incidence and the best sanitation and income indicators, along with small increases in population and a low proportion of shantytowns. The incidence rates in 2001 and 2002 were high in most strata except for stratum 1.2, which had the districts with the least heterogeneity in relation to the indicators used. In 2001, the strata presented high rates of incidence when group immunity had supposedly become established for serotype I, thus expressing the transmission strength of this agent. CONCLUSIONS: The cluster analysis technique made it possible to recognize priority areas. It indicated areas where the dengue control and surveillance actions needed to be improved, along with structural improvements that influenced the living conditions and health of the municipality's population.

Keywords : Dengue [epidemiology]; Cluster Analysis; Risk Factors.

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