Honorato Taizi, Lapa Priscila Pagung de Aquino, Sales Carolina Maia Martins, Reis-Santos Barbara, Tristão-Sá Ricardo, Bertolde Adelmo Inácio, Maciel Ethel Leonor Noia
School of Statistics, Universidade Federal do Espírito Santo, Vitória, ES, Brazil.
School of Nursing, Universidade Federal do Espírito Santo, Vitória, ES, Brazil.
Rev Bras Epidemiol. 2014;17 Suppl 2:150-9. doi: 10.1590/1809-4503201400060013.
To study the relationship between the risk of dengue and sociodemographic variables through the use of spatial regression models fully Bayesian in the municipalities of Espírito Santo in 2010.
This is an ecological study and exploration that used spatial analysis tools in preparing thematic maps with data obtained from SinanNet. An analysis by area, taking as unit the municipalities of the state, was performed. Thematic maps were constructed by the computer program R 2.15.00 and Deviance Information Criterion (DIC), calculated in WinBugs, Absolut and Normalized Mean Error (NMAE) were the criteria used to compare the models.
We were able to geocode 21,933 dengue cases (rate of 623.99 cases per 100 thousand habitants) with a higher incidence in the municipalities of Vitória, Serra and Colatina; model with spatial effect with the covariates trash and income showed the best performance at DIC and Nmae criteria.
It was possible to identify the relationship of dengue with factors outside the health sector and to identify areas with higher risk of disease.
通过使用全贝叶斯空间回归模型，研究2010年圣埃斯皮里图州各市登革热风险与社会人口统计学变量之间的关系。
这是一项生态研究与探索，利用空间分析工具，结合从SinanNet获取的数据编制专题地图。以该州各市为单位进行区域分析。专题地图由计算机程序R 2.15.00构建，在WinBugs中计算偏差信息准则（DIC），使用绝对误差和归一化平均误差（NMAE）作为比较模型的标准。
我们能够对21933例登革热病例进行地理编码（发病率为每10万居民623.99例），在维多利亚、塞拉和科拉蒂纳等市发病率较高；包含协变量垃圾和收入的空间效应模型在DIC和Nmae标准下表现最佳。
能够确定登革热与卫生部门以外因素的关系，并识别疾病风险较高的地区。
