Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease Risk.
Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease Risk.
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DOI：
10.1371/journal.pntd.0003937
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发表时间：
2015
影响因子：
3.8
通讯作者：
Ribeiro GS
中科院分区：
文献类型：
--
作者：
Kikuti M;Cunha GM;Paploski IA;Kasper AM;Silva MM;Tavares AS;Cruz JS;Queiroz TL;Rodrigues MS;Santana PM;Lima HC;Calcagno J;Takahashi D;Gonçalves AH;Araújo JM;Gauthier K;Diuk-Wasser MA;Kitron U;Ko AI;Reis MG;Ribeiro GS
很少有关于登革热的研究表明，人口、社会经济或地理特征与登革热在小城市地区的空间分布之间存在群体水平的关联。本研究旨在检查城市贫民窟社区的特定特征是否与登革热风险相关。从2009年1月至2010年12月，我们在巴西萨尔瓦多贫民窟唯一的公共急诊单位开展了加强的社区监测，以确定有登革热感染实验室证据的急性发热性疾病（AFI）患者。在人口普查区（ct）内对患者家庭进行地理编码。人口、社会经济和地理数据来自2010年全国人口普查。ct特征与登革热和非登革热AFI的空间风险之间的关系通过泊松对数正态和条件自回归模型（CAR）进行评估。我们在2962例AFI患者中发现651例（22.0%）登革热病例。2009年和2010年，有症状登革热的估计风险分别为每1万名居民21.3例和70.2例。所有4种登革热血清型均得到鉴定，但以DENV2型为主（DENV1: 8.1%, DENV2: 90.7%, DENV3: 0.4%, DENV4: 0.8%）。多变量CAR回归分析显示，居民较贫穷的ct的登革热风险增加（收入≤最低工资1倍的家庭频率每增加1%，RR: 1.02; 95% CI: 1.01-1.04），而距离卫生单位较远的ct的风险降低（RR: 0.87，每增加100米；95% CI: 0.80-0.94）。同样的ct特征也与非登革热性AFI风险相关。这项研究强调了生活在巴西城市贫民窟的个体有症状的登革热的巨大负担。较低的社区社会经济地位与登革热风险增加独立相关，表明在绝对贫困程度较高的贫民窟社区，与社会梯度相关的因素影响登革热传播。此外，难以获得卫生服务的地理位置可能是确定登革热和非登革热AFI病例的障碍。因此，进一步的空间研究应该考虑到这种潜在的偏差来源。登革热受环境影响；然而，很少有研究调查了登革热在小城市地区的邻里特征与空间分布之间的关系。我们研究了城市贫民窟社区的特定特征是否与登革热风险相关。2009年1月至2010年12月，我们在巴西萨尔瓦多的一个贫民窟开展了社区监测，以确定急性发热性疾病（AFI）患者并对其进行登革热检测。我们在2962例AFI患者中发现651例（22.0%）有登革热感染的实验室证据。4种登革热血清型均检出，但以DENV2型为主（DENV1 8.1%、DENV2 90.7%、DENV3 0.4%、DENV4 0.8%）。2009年和2010年，有症状登革热的估计风险分别为每1万名居民21.3例和70.2例。我们发现，社区贫困水平和靠近卫生中心与登革热和其他AFI的较高检测风险相关。这项研究强调了巴西贫困城市贫民窟登革热的巨大负担，并表明社会经济发展可能潜在地减轻登革热和非登革热AFI病例的危险因素。此外，我们发现住宅靠近医疗机构与病例检出率的提高有关。因此，在评估风险时，对疾病分布的进一步研究应考虑家庭与卫生保健设施的接近程度。
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. 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. 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. 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.