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基于模型的地质统计学在寄生虫病流行病学和控制中的应用。

The applications of model-based geostatistics in helminth epidemiology and control.

机构信息

University of Queensland, School of Population Health, Herston, Queensland, Australia.

出版信息

Adv Parasitol. 2011;74:267-96. doi: 10.1016/B978-0-12-385897-9.00005-7.

Abstract

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes.

摘要

资助机构正在投入大量资源来解决寄生虫感染问题。可靠的寄生虫感染分布图谱可以通过将控制资源靶向到最需要的地区来帮助这些努力。由于高质量调查数据的可用性增加以及基于模型的地统计学(MBG)的使用,寄生虫感染分布的定义能力在区域、国家和次国家各级都得到了极大的提高,从而能够在未采样的地点进行空间预测。MBG 风险制图方法的一个主要优势是,它们为处理和表示不同来源的不确定性提供了一个灵活的统计平台,为寄生虫感染的空间分布提供了合理和稳健的信息,以便为控制规划的设计和实施提供信息。本文以血吸虫病和土壤传播性寄生虫病为例,同时也有关于淋巴丝虫病和盘尾丝虫病的例子,回顾了迄今为止在大规模实际控制规划中应用 MBG 工具所取得的进展,并提出了一个将其应用于寄生虫病控制规划综合空间规划的通用框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/291b/3037997/10d303013aa4/ukmss-34264-f0002.jpg

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