Spatial Vulnerability to Dengue in a Brazilian Urban Area During a 7-Year Surveillance

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 ( e 4 years of schooling), low income of the head of the family ( e 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.

Characterization of dengue epidemics in mainland China over the past decade

“…Recent studies have revealed that all dengue epidemics in China are caused by imported dengue cases [9][10][11]. In addition to the direct role of imported cases, the epidemics are also attributed to natural factors that affect the breeding and survival of the Aedes mosquitoes, such as climatic (temperature, humidity), vegetative, and socio-economic factors that affect human-mosquito contact, such as population density, population mobility, economic development, and living conditions of a specific city [7,[12][13][14]. These studies provide strong support for the necessity of appropriate prevention and control measures against dengue in China.…”

La dengue, maladie complexe

“…Cependant si ces facteurs influencent potentiellement le cycle de contamination, ils ne sont pas systéma-tiquement identifiés comme tels, car le résultat des causalités non linéaires entre ces facteurs dépend des contextes locaux. La connaissance de ces relations permet malgré tout la mise en oeuvre d'actions à différentes échelles pour tenter d'améliorer les conditions de santé publique : contrôle régulier des gîtes en eau (Abe et al, 2005), mesures de protection intra domiciliaires (Singh et al, 2011), amélioration des conditions d'accès à l'eau des populations (Schmidt et al, 2011), interventions selon les types d'usages du sol (Thammapalo et al, 2008) ou encore politiques de planification urbaine (De Mattos Almeida et al, 2007).…”

“…Les zones de concentration des indices vectoriels en milieu urbain ont pu être calculées à partir de facteurs environnementaux tels que la densité de maisons en briques ou l'absence de réseau de collecte des ordures en Thaïlande (Thammapalo et al, 2008). Les corrélations entre des données sociodémographiques (éducation, revenu, taille du ménage) et des données épidémiologiques ont permis d'identifier les populations les plus vulnérables au Brésil (De Mattos Almeida et al, 2007). L'intégration d'images satellites dans la chaîne de traitement permet d'identifier et de caractériser de manière automatique et à petite échelle les zones à risques vectoriels (Fuller et al, 2010).…”

Heterogeneidade espacial da dengue em estudos locais, Niterói, RJ

“…1 As a result, some studies on these associations identified the occurrence of dengue fever in heterogeneous areas in terms of socioeconomic and environmental indicators.…”