 Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease RiskMariana Kikuti, Geraldo M Cunha, Igor A D Paploski, Amelia M Kasper, Monaise M O Silva, Aline S Tavares, Jaqueline S Cruz, Tássia L Queiroz, Moreno S Rodrigues, Perla M Santana, Helena C A V Lima, Juan Calcagno, Daniele Takahashi, André H O Gonçalves, Josélio M G Araújo, Kristine Gauthier, Maria A Diuk-Wasser, Uriel Kitron, Albert I Ko, Mitermayer G Reis and Guilherme S Ribeiro PLOS Neglected Tropical Diseases, 2015, vol. 9, issue 7, 1-18 Abstract: Background: Few studies of dengue have shown group-level associations between demographic, socioeconomic, or geographic characteristics and the spatial distribution of dengue within small urban areas. This study aimed to examine whether specific characteristics of an urban slum community were associated with the risk of dengue disease. Methodology/Principal Findings: From 01/2009 to 12/2010, we conducted enhanced, community-based surveillance in the only public emergency unit in a slum in Salvador, Brazil to identify acute febrile illness (AFI) patients with laboratory evidence of dengue infection. Patient households were geocoded within census tracts (CTs). Demographic, socioeconomic, and geographical data were obtained from the 2010 national census. Associations between CTs characteristics and the spatial risk of both dengue and non-dengue AFI were assessed by Poisson log-normal and conditional auto-regressive models (CAR). We identified 651 (22.0%) dengue cases among 2,962 AFI patients. Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. All the four dengue serotypes were identified, but DENV2 predominated (DENV1: 8.1%; DENV2: 90.7%; DENV3: 0.4%; DENV4: 0.8%). Multivariable CAR regression analysis showed increased dengue risk in CTs with poorer inhabitants (RR: 1.02 for each percent increase in the frequency of families earning ≤1 times the minimum wage; 95% CI: 1.01-1.04), and decreased risk in CTs located farther from the health unit (RR: 0.87 for each 100 meter increase; 95% CI: 0.80-0.94). The same CTs characteristics were also associated with non-dengue AFI risk. Conclusions/Significance: This study highlights the large burden of symptomatic dengue on individuals living in urban slums in Brazil. Lower neighborhood socioeconomic status was independently associated with increased risk of dengue, indicating that within slum communities with high levels of absolute poverty, factors associated with the social gradient influence dengue transmission. In addition, poor geographic access to health services may be a barrier to identifying both dengue and non-dengue AFI cases. Therefore, further spatial studies should account for this potential source of bias. Author Summary: Dengue is influenced by the environment; however, few studies have investigated the relationship between neighborhood characteristics and the spatial distribution of dengue within small urban areas. We examined whether specific characteristics of an urban slum community were associated with dengue risk. From January 2009 to December 2010, we conducted community-based surveillance in a slum in Salvador, Brazil to identify patients with acute febrile illness (AFI) and to test them for dengue. We identified 651 (22.0%) patients with laboratory evidence of dengue infection among 2,962 AFI patients. All the four dengue serotypes were detected, but DENV2 predominated (DENV1 8.1%; DENV2 90.7%; DENV3 0.4%; DENV4 0.8%). Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. We found that neighborhood poverty level and proximity to the health center were associated with higher risk of detection of dengue and other AFI. This study highlights the large burden of dengue in poor urban slums of Brazil and indicates that socioeconomic development could potentially mitigate risk factors for both dengue and non-dengue AFI cases. In addition, we found that residential proximity to a health care facility was associated with improved case detection. Therefore, further studies on disease distribution should consider household proximity to health care facilities when assessing risk. Date: 2015 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pntd00:0003937 DOI: 10.1371/journal.pntd.0003937 Access Statistics for this article More articles in PLOS Neglected Tropical Diseases from Public Library of Science |
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