Current WHO guidelines set prevalence thresholds below which a Neglected Tropical Disease can be considered to have been eliminated as a public health problem, and specify how surveys to assess whether elimination has been achieved should be designed and analysed, based on classical survey sampling methods. In this paper we describe an alternative approach based on geospatial statistical modelling. We first show the gains in efficiency that can be obtained by exploiting any spatial correlation in the underlying prevalence surface. We then suggest that the current guidelines implicit use of a significance testing argument is not appropriate; instead, we argue for a predictive inferential framework, leading to design criteria based on controlling the rates at which areas whose true prevalence lies above and below the elimination threshold are incorrectly classified. We describe how this approach naturally accommodates context-specific information in the form of georeferenced covariates that have been shown to be predictive of disease prevalence. Finally, we give a progress report of an ongoing collaboration with the Guyana Ministry of Health Neglected Tropical Disease program on the design of an IDA (Ivermectin, Diethylcarbamazine and Albendazole) Impact Survey (IIS) of lymphatic filariasis to be conducted in Guyana in early 2023

翻译：当前WHO指南设定了患病率阈值，低于该阈值的被忽视热带病可被视为已作为公共卫生问题消除，并基于经典调查抽样方法规定了评估消除是否实现的调查设计与分析方法。本文描述了一种基于地理空间统计建模的替代方法。我们首先展示了通过利用潜在患病率表面的空间相关性所能获得的效率提升。继而指出现行指南隐含采用的显著性检验论证并不恰当；相反，我们主张采用预测性推断框架，进而设计以控制真实患病率高于和低于消除阈值的区域被错误分类比率为基础的设计标准。我们阐述了该方法如何自然地容纳已被证明可预测疾病患病率的地理参考协变量形式的情境特定信息。最后，我们报告了与圭亚那卫生部被忽视热带病项目正在进行的合作进展，该项目涉及2023年初在圭亚那开展的淋巴丝虫病IDA（伊维菌素、乙胺嗪和阿苯达唑）影响调查（IIS）的设计。