The Effects of City Streets on an Urban Disease Vector
The Effects of City Streets on an Urban Disease Vector
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DOI：
10.1371/journal.pcbi.1002801
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发表时间：
2013-01-01
影响因子：
4.3
通讯作者：
Levy, Michael Z.
中科院分区：
文献类型：
--
作者：
Barbu, Corentin M.;Hong, Andrew;Levy, Michael Z.
随着城市化程度的提高，媒介传播疾病在城市中迅速发展，需要城市控制策略。如果街道被证明是疾病媒介的屏障，城市街区可以被用作研究和控制的方便和相关的空间单元。不幸的是，现有的空间分析工具不能评估城市电网对疾病病原体存在的影响。在这里，我们首先提出了一种基于Moran空间自相关指数分解的方法来检验街道对媒介感染的影响的重要性；其次，发展了高斯场潜在类模型来精细地描述街道的影响，同时控制余因子和不完善的矢量检测。我们将这些方法应用于秘鲁阿雷基帕市恰加斯病病媒Triatoma inestans感染的横断面数据。我们的Moran分解测试显示，在这个城市环境中，毛滴虫的分布明显受到街道的限制(p<；0.05)。利用高斯场潜伏类模型，我们证实了街道提供了一种抵抗虫害的屏障，并进一步表明，媒介存在概率的空间分量中，90%以上是由城市街区内房屋之间的相关性来解释的。因此，城市街区很可能是在城市环境中描述和控制毛滴虫的合适空间单元。城市电网的特点会影响媒介传播疾病的空间动态，在设计公共卫生政策时应予以考虑。
With increasing urbanization vector-borne diseases are quickly developing in cities, and urban control strategies are needed. If streets are shown to be barriers to disease vectors, city blocks could be used as a convenient and relevant spatial unit of study and control. Unfortunately, existing spatial analysis tools do not allow for assessment of the impact of an urban grid on the presence of disease agents. Here, we first propose a method to test for the significance of the impact of streets on vector infestation based on a decomposition of Moran's spatial autocorrelation index; and second, develop a Gaussian Field Latent Class model to finely describe the effect of streets while controlling for cofactors and imperfect detection of vectors. We apply these methods to cross-sectional data of infestation by the Chagas disease vector Triatoma infestans in the city of Arequipa, Peru. Our Moran's decomposition test reveals that the distribution of T. infestans in this urban environment is significantly constrained by streets (p < 0.05). With the Gaussian Field Latent Class model we confirm that streets provide a barrier against infestation and further show that greater than 90% of the spatial component of the probability of vector presence is explained by the correlation among houses within city blocks. The city block is thus likely to be an appropriate spatial unit to describe and control T. infestans in an urban context. Characteristics of the urban grid can influence the spatial dynamics of vector borne disease and should be considered when designing public health policies.