In this paper we attempt to answer the following question: ``Is it possible to obtain reliable estimates for the prevalence of anemia rates in children under five years in the districts of Peru?'' Specifically, the interest of the present paper is to understand to which extent employing the basic and the spatial Fay-Herriot models can compensate for inadequate sample size in most of the sampled districts, and whether the way of choosing the spatial neighbors has an impact on the resulting inference. Furthermore, it is raised the question of how to choose an optimal way to define the neighbours. We present an illustrative analysis using the data from the Demographic and Family Health Survey of the year 2019, and the National Census carried out in 2017.

翻译：在本文中,我们试图回答以下问题:“能否对秘鲁各区5岁以下儿童贫血率的流行情况获得可靠的估计?”具体地说,本文件的兴趣是了解在多大程度上使用Fay-Herriot基本和空间模型可以弥补大多数抽样区的抽样规模不足,以及选择空间邻居的方式是否对由此得出的推断产生影响;此外,还提出了如何选择最佳方式界定邻居的问题,我们利用2019年人口和家庭健康调查以及2017年全国人口普查提供的数据进行了说明性分析。