  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
