Spatial point analysis based on dengue surveys at household level in central Brazil
Spatial point analysis based on dengue surveys at household level in central Brazil
复制标题
DOI：
10.1186/1471-2458-8-361
复制
发表时间：
2008-10-20
影响因子：
4.5
通讯作者：
Martelli, Celina M. T.
中科院分区：
文献类型：
--
作者：
Siqueira-Junior, Joao B.;Maciel, Ivan J.;Martelli, Celina M. T.
背景：登革热病毒（DENV）影响热带和亚热带地区的非免疫人群。在美洲，登革热在过去二十年急剧增加，巴西被认为是受影响最严重的国家之一。无症状感染者的高频率使得利用登记病例估计感染流行率以及从人口层面定位城市内高风险地区变得困难。该空间点分析的目标是利用从家庭层面调查收集的数据来确定城市内潜在的登革热高风险地区。方法：2001 年和 2002 年在巴西中部戈亚尼亚市（人口约 110 万）进行了两次家庭调查。第一次调查筛查了 1,586 名 5 岁以上无症状个体。第二次调查使用可用的数字地图，通过多阶段抽样（人口普查区、街区、家庭）选出了 2,906 名相同年龄组的无症状志愿者。 EIA 对参与者的血清进行了登革热病毒特异性 IgM/IgG 检测。使用广义加性模型（GAM）来检测该区域的空间变化风险。最初没有任何固定的协变量，以描绘总体风险图，然后是包含主要协变量和年份的模型，其中生成的图显示与居住地相关的风险，并控制各个风险因素。该方法的优点是可以生成平滑的危险因素图，并通过社会人口统计学协变量进行调整。结果：2002 年抗登革热感染抗体的流行率为 37.3%（95% CI [35.5-39.1]）；一年间隔增长 7.8%。与 2001 年和 2002 年相比，登革热感染风险的空间变异发生了显着变化（OR 调整 = 1.35；p < 0.001），同时使用 GAM 模型控制了潜在的混杂因素。此外，年龄增长和教育水平低也与登革热感染有关。结论：本研究表明，在短时间间隔内使用空间多变量方法时，登革热风险区域存在空间异质性。住户调查数据显示，2001年调查的低流行地区连续一年向高风险地区转变。登革热风险图应该为城市地区的控制干预措施提供见解。
Background: Dengue virus (DENV) affects nonimunne human populations in tropical and subtropical regions. In the Americas, dengue has drastically increased in the last two decades and Brazil is considered one of the most affected countries. The high frequency of asymptomatic infection makes difficult to estimate prevalence of infection using registered cases and to locate high risk intra-urban area at population level. The goal of this spatial point analysis was to identify potential high-risk intra-urban areas of dengue, using data collected at household level from surveys.Methods: Two household surveys took place in the city of Goiania (similar to 1.1 million population), Central Brazil in the year 2001 and 2002. First survey screened 1,586 asymptomatic individuals older than 5 years of age. Second survey 2,906 asymptomatic volunteers, same age-groups, were selected by multistage sampling (census tracts; blocks; households) using available digital maps. Sera from participants were tested by dengue virus-specific IgM/IgG by EIA. A Generalized Additive Model (GAM) was used to detect the spatial varying risk over the region. Initially without any fixed covariates, to depict the overall risk map, followed by a model including the main covariates and the year, where the resulting maps show the risk associated with living place, controlled for the individual risk factors. This method has the advantage to generate smoothed risk factors maps, adjusted by sociodemographic covariates.Results: The prevalence of antibody against dengue infection was 37.3% (95% CI [35.5-39.1]) in the year 2002; 7.8% increase in one-year interval. The spatial variation in risk of dengue infection significantly changed when comparing 2001 with 2002, (ORadjusted = 1.35; p < 0.001), while controlling for potential confounders using GAM model. Also increasing age and low education levels were associated with dengue infection.Conclusion: This study showed spatial heterogeneity in the risk areas of dengue when using a spatial multivariate approach in a short time interval. Data from household surveys pointed out that low prevalence areas in 2001 surveys shifted to high-risk area in consecutive year. This mapping of dengue risks should give insights for control interventions in urban areas.