Serviços Personalizados
Journal
Artigo
Indicadores
- Citado por SciELO
- Acessos
Links relacionados
- Citado por Google
- Similares em SciELO
- Similares em Google
Compartilhar
Revista de Salud Pública
versão impressa ISSN 0124-0064
Resumo
JOHANSEN, Igor Cavallini; DO CARMO, Roberto Luiz; CORREIA ALVES, Luciana e BUENO, Maria do Carmo Dias. Environmental and demographic determinants of dengue incidence in Brazil. Rev. salud pública [online]. 2018, vol.20, n.3, pp.346-351. ISSN 0124-0064. https://doi.org/10.15446/rsap.v20n3.54315.
Objective
To analyze the spatial distribution of dengue fever cases within an urban area of the São Paulo State, southeast Brazil.
Methods
Based on a methodology created by the authors, it was possible to organize the Brazilian Census data of 2010 into a regular grid of 250x250 meters each cell. This cell was the unit of analysis. Then, the 1 688 residential addresses of autochthonous dengue cases reported in 2013 in Caraguatatuba city were geocoded to calculate the incidence rate by cell. The dependent variable was the dengue incidence rate and the independent variables were classified into two types: environmental and sociodemographic. Finally, a Zero-Inflated Negative Binomial Regression was performed using the software R.
Results
The statistical analysis showed an association between dengue incidence rate and the environmental variable "proximity to strategic points (junk yards, tire repair shops and deposits of recyclable materials)." Dengue was also associated to the sociodemographic variables "proportion of households with per capita income up to 3 minimum wages", "proportion of nonwhite people" and "proportion of not owned households".
Conclusion
Dengue is associated to several factors related to its epidemic outbreak. In this complex context, results suggest that this infectious disease is socially conditioned, since it is more likely to reach population groups with specific characteristics, notably those with low socioeconomic status.
Palavras-chave : Dengue; environmental health; population dynamics; regression analysis; Brazil (source: MeSH, NLM).