Spatial vulnerability to dengue in a Brazilian urban area during a 7-year surveillance

J Urban Health. 2007 May;84(3):334-45. doi: 10.1007/s11524-006-9154-2.

Abstract

This study considers the vulnerability of the urban area of the City of Belo Horizonte to dengue. A total number of 89,607 cases registered in the surveillance system from 1996 to 2002 were analyzed. Seven epidemic waves were identified during this period. Cases were grouped into 2,563 census areas, and three risk categories were proposed based on how many times each area reached a threshold established for each epidemic wave. The association between the risk categories and the socioeconomic, demographic and urban-infrastructure characteristics was evaluated. Analysis included Kruskal-Wallis test variance comparisons and multivariate regression using multinomial models. Incidence rates differed significantly among the three risk categories in most of the epidemic waves. The factors that best characterized the areas were low educational level (< or =4 years of schooling), low income of the head of the family (< or =2 minimum wages per household), household density, and proportion of children and elderly women. Information related to basic sanitation was not enough to discriminate levels of susceptibility to dengue, and study of population density and concentration of establishments considered vulnerable to vector infestation yielded questionable results. It is important to consider different levels of exposure of the population to explain the heterogeneous pattern of distribution of dengue cases in an urban setting. Understanding the dynamics of dengue fever is essential for surveillance purposes, to improve control measures and to avoid epidemics of this disease.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aedes
  • Animals
  • Brazil / epidemiology
  • Demography
  • Dengue / economics
  • Dengue / epidemiology*
  • Disease Outbreaks / economics
  • Disease Outbreaks / statistics & numerical data*
  • Humans
  • Incidence
  • Insect Vectors
  • Population Surveillance
  • Risk Assessment
  • Risk Factors
  • Sanitation
  • Socioeconomic Factors
  • Urban Health / statistics & numerical data*
  • Vulnerable Populations / statistics & numerical data*