首页> 外文期刊>Revista da Sociedade Brasileira de Medicina Tropical >Spatial distribution of leprosy in areas of risk in Vitoria, State of Espirito Santo, Brazil, 2005 to 2009
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Spatial distribution of leprosy in areas of risk in Vitoria, State of Espirito Santo, Brazil, 2005 to 2009

机译:2005年至2009年,巴西圣埃斯皮里图州维多利亚市高危地区麻风病的空间分布

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Introduction Leprosy remains a relevant public health issue in Brazil. The objective of this study was to analyze the spatial distribution of new cases of leprosy and to detect areas with higher risks of disease in the City of Vitória. Methods The study was ecologically based on the spatial distribution of leprosy in the City of Vitória, State of Espírito Santo between 2005 and 2009. The data sources used came from the available records of the State Health Secretary of Espírito Santo. A global and local empirical Bayesian method was used in the spatial analysis to produce a leprosy risk estimation, and the fluctuation effect was smoothed from the detection coefficients. Results The study used thematic maps to illustrate that leprosy is distributed heterogeneously between the neighborhoods and that it is possible to identify areas with high risk of disease. The Pearson correlation coefficient of 0.926 (p = 0.001) for the Local Method indicated highly correlated coefficients. The Moran index was calculated to evaluate correlations between the incidences of adjoining districts. Conclusions We identified the spatial contexts in which there were the highest incidence rates of leprosy in Vitória during the studied period. The results contribute to the knowledge of the spatial distribution of leprosy in the City of Vitória, which can help establish more cost-effective control strategies because they indicate specific regions and priority planning activities that can interfere with the transmission chain.
机译:简介麻风病在巴西仍然是一个相关的公共卫生问题。这项研究的目的是分析新的麻风病病例的空间分布,并检测维托里亚市患疾病风险较高的地区。方法该研究是基于2005年至2009年在圣埃斯皮里图州维托里亚市麻风的空间分布进行的生态研究。所用数据来源来自圣埃斯皮里图州卫生部长的可用记录。在空间分析中使用全局和局部经验贝叶斯方法进行麻风风险估计,并从检测系数中平滑波动效果。结果该研究使用专题图来说明麻风病在各社区之间的分布不均,并且有可能确定高疾病风险地区。本地方法的Pearson相关系数为0.926(p = 0.001),表明相关系数很高。计算Moran指数以评估相邻地区的发病率之间的相关性。结论我们确定了在研究期间维托里亚麻风病发病率最高的空间环境。结果有助于了解维托里亚市麻风病的空间分布,这有助于建立更具成本效益的控制策略,因为它们指出了可能干扰传播链的特定区域和优先计划活动。

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