Spatiotemporal Bayesian modeling of the risk of congenital syphilis in São Paulo, SP, Brazil

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology Pub Date : 2024-04-22 DOI:10.1016/j.sste.2024.100651

Renato Ferreira da Cruz , Joelma Alexandra Ruberti , Thiago Santos Mota , Liciana Vaz de Arruda Silveira , Francisco Chiaravalloti-Neto

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引用次数: 0

Abstract

The aim of this study is to analyze the spatiotemporal risk of congenital syphilis (CS) in high-prevalence areas in the city of São Paulo, SP, Brazil, and to evaluate its relationship with socioeconomic, demographic, and environmental variables. An ecological study was conducted based on secondary CS data with spatiotemporal components collected from 310 areas between 2010 and 2016. The data were modeled in a Bayesian context using the integrated nested Laplace approximation (INLA) method. Risk maps showed an increasing CS trend over time and highlighted the areas that presented the highest and lowest risk in each year. The model showed that the factors positively associated with a higher risk of CS were the Gini index and the proportion of women aged 18–24 years without education or with incomplete primary education, while the factors negatively associated were the proportion of women of childbearing age and the mean per capita income.

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巴西圣保罗先天性梅毒风险的时空贝叶斯模型

本研究旨在分析巴西圣保罗市高发区先天性梅毒（CS）的时空风险，并评估其与社会经济、人口和环境变量的关系。这项生态学研究基于2010年至2016年期间从310个地区收集的具有时空成分的梅毒二级数据。研究人员使用综合嵌套拉普拉斯近似法（INLA）对数据进行了贝叶斯建模。风险地图显示 CS 随时间呈上升趋势，并突出显示了每年风险最高和最低的地区。模型显示，与较高 CS 风险正相关的因素是基尼指数和 18-24 岁未受过教育或未完成初等教育的妇女比例，而与较高 CS 风险负相关的因素是育龄妇女比例和平均人均收入。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

5.10

自引率

8.80%

发文量