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通过风险测绘来控制沙眼:以南苏丹为例。

Targeting trachoma control through risk mapping: the example of Southern Sudan.

机构信息

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

出版信息

PLoS Negl Trop Dis. 2010 Aug 17;4(8):e799. doi: 10.1371/journal.pntd.0000799.

Abstract

BACKGROUND

Trachoma is a major cause of blindness in Southern Sudan. Its distribution has only been partially established and many communities in need of intervention have therefore not been identified or targeted. The present study aimed to develop a tool to improve targeting of survey and control activities.

METHODS/PRINCIPAL FINDINGS: A national trachoma risk map was developed using Bayesian geostatistics models, incorporating trachoma prevalence data from 112 geo-referenced communities surveyed between 2001 and 2009. Logistic regression models were developed using active trachoma (trachomatous inflammation follicular and/or trachomatous inflammation intense) in 6345 children aged 1-9 years as the outcome, and incorporating fixed effects for age, long-term average rainfall (interpolated from weather station data) and land cover (i.e. vegetation type, derived from satellite remote sensing), as well as geostatistical random effects describing spatial clustering of trachoma. The model predicted the west of the country to be at no or low trachoma risk. Trachoma clusters in the central, northern and eastern areas had a radius of 8 km after accounting for the fixed effects.

CONCLUSION

In Southern Sudan, large-scale spatial variation in the risk of active trachoma infection is associated with aridity. Spatial prediction has identified likely high-risk areas to be prioritized for more data collection, potentially to be followed by intervention.

摘要

背景

沙眼是苏丹南部地区主要致盲原因。其分布情况仅部分确定,因此许多需要干预的社区尚未被识别或确定。本研究旨在开发一种工具,以改善调查和控制活动的针对性。

方法/主要发现:利用贝叶斯地统计学模型,结合 2001 年至 2009 年期间调查的 112 个地理位置社区的沙眼流行数据,制定了全国沙眼风险图。使用 6345 名 1-9 岁儿童的活动性沙眼(滤泡性和/或严重性沙眼)作为结局,开发了逻辑回归模型,并纳入年龄、长期平均降雨量(从气象站数据插值)和土地覆盖(即植被类型,来自卫星遥感)的固定效应,以及描述沙眼空间聚类的地统计学随机效应。该模型预测该国西部的沙眼风险较低或无。考虑到固定效应后,中部、北部和东部地区的沙眼聚类半径为 8 公里。

结论

在苏丹南部,活动性沙眼感染风险的大规模空间变化与干旱有关。空间预测确定了可能的高风险地区,这些地区应优先收集更多数据,可能随后进行干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a73/2923154/ddffad4f4f46/pntd.0000799.g001.jpg

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4
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5
A comparative study of the spatial distribution of schistosomiasis in Mali in 1984-1989 and 2004-2006.
PLoS Negl Trop Dis. 2009;3(5):e431. doi: 10.1371/journal.pntd.0000431. Epub 2009 May 5.
6
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PLoS Negl Trop Dis. 2009;3(3):e396. doi: 10.1371/journal.pntd.0000396. Epub 2009 Mar 17.
7
Trachoma survey methods: a literature review.
Bull World Health Organ. 2009 Feb;87(2):143-51. doi: 10.2471/blt.07.046326.
8
Spatial heterogeneity of parasite co-infection: Determinants and geostatistical prediction at regional scales.
Int J Parasitol. 2009 Apr;39(5):591-7. doi: 10.1016/j.ijpara.2008.10.014. Epub 2008 Dec 3.
9
Mapping the probability of schistosomiasis and associated uncertainty, West Africa.
Emerg Infect Dis. 2008 Oct;14(10):1629-32. doi: 10.3201/eid1410.080366.
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