Spatial analysis of dengue and the socioeconomic context of the city of Rio de Janeiro (Southeastern Brazil)

• Published in: Revista de saúde pública Vol. 43; no. 4; pp. 666 - 673
• Main Authors: Almeida, Andréa Sobral de, Medronho, Roberto de Andrade, Valencia, Luís Iván Ortiz
• Format: Journal Article
• Language: English; Portuguese
• Published: Brazil 01-08-2009
• Subjects: Animals; Brazil - epidemiology; Demography; Dengue - epidemiology; Dengue - transmission; Humans; Insect Vectors - physiology; Linear Models; Multivariate Analysis; Risk Factors; Socioeconomic Factors; Space-Time Clustering; Urban Population - statistics & numerical data; Brazil
• ISSN: 1518-8787
• DOI: 10.1590/S0034-89102009000400013

To analyze the dengue epidemic in relation to the socioeconomic context according to geographical areas.
An ecological study was conducted in the municipality of Rio de Janeiro (Southeastern Brazil), in areas delimited as neighborhoods, based on information about notified dengue cases concerning residents in the municipality. The average incidence rate of dengue was calculated between the epidemiological weeks: 48th of 2001 and 20th of 2002. The occurrence of dengue was correlated with socioeconomic variables through Pearsons' correlation coefficient. Moran's global and local indexes were used to assess the spatial auto-correlation between dengue and the variables that significantly correlated with the disease. The multiple linear regression model and the conditional auto-regression spatial model were used to analyze the relationship between dengue and socioeconomic context.
The neighborhoods located in the west zone of the municipality presented high rates of average dengue incidence. The variables presenting significant correlation were: percentage of households connected with the general sanitary network, households with washing machines, and population density per urban area. Moran's spatial auto-correlation index revealed spatial dependence between dengue and the selected variables. The utilized models indicated percentage of households connected with the general sanitary network as the sole variable significantly associated with the disease. The residual figures in both models revealed significant spatial auto-correlation, with a positive Moran Index (p<0.001) for linear regression model, and a negative one (p=0.005) for the conditional auto-regression one.
Problems related to basic sanitation contribute decisively to increase the risk of the disease.