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重新思考被忽视热带病流行情况调查设计和分析:一个地理空间范例。

Rethinking neglected tropical disease prevalence survey design and analysis: a geospatial paradigm.

机构信息

Medical School, Lancaster University, Lancaster, LA1 4YF, UK.

Health Data Research, 215 Euston Road, London, NW1 2BE, UK.

出版信息

Trans R Soc Trop Med Hyg. 2021 Mar 6;115(3):208-210. doi: 10.1093/trstmh/trab020.

Abstract

Current methods for the design and analysis of neglected tropical disease prevalence surveys largely rely on classical survey sampling ideas that treat prevalence data from different locations as an independent random sample from the probability distribution induced by a random sampling design. We set out an alternative, explicitly geospatial paradigm that can deliver much more precise estimates of the geospatial variation in prevalence over a country or region of interest. We describe the advantages of this approach under three headings: streamlining, whereby more precise results can be obtained with smaller sample sizes; integrating, whereby a joint analysis of data from two or more diseases can bring further gains in precision; and adapting, whereby the choice of future sampling location is informed by past data.

摘要

目前设计和分析被忽视热带病流行率调查的方法在很大程度上依赖于经典的调查抽样思想,即把来自不同地点的流行率数据视为随机抽样设计所产生的概率分布的独立随机样本。我们提出了一种替代的、明确的地理空间范例,可以更精确地估计感兴趣的国家或地区内流行率的地理空间变化。我们从三个方面描述了这种方法的优势:简化,通过使用更小的样本量可以获得更精确的结果;整合,通过联合分析两种或多种疾病的数据,可以进一步提高精度;以及适应,通过利用过去的数据为未来的抽样地点选择提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c91/7946792/b974f59eed04/trab020fig1.jpg

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