Sleeping Sickness in Southeastern Uganda: A Spatio-Temporal Analysis of Disease Risk, 1970-2003
Sleeping Sickness in Southeastern Uganda: A Spatio-Temporal Analysis of Disease Risk, 1970-2003
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DOI：
10.1089/vbz.2008.0196
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发表时间：
2010-12-01
影响因子：
2.1
通讯作者：
Abdelrahman, Lubowa
中科院分区：
文献类型：
--
作者：
Berrang-Ford, Lea;Berke, Olaf;Abdelrahman, Lubowa
昏睡病是撒哈拉以南非洲地区人类健康的主要威胁。乌干达东南部在过去 100 年中经历了多次重大流行病，最近一次是 1976 年至 1989 年。该疾病最近持续的传播凸显了当前研究解释和预测感染分布能力的差距。由于采采蝇媒介的栖息地偏好，植被覆盖和植被变化可能是传播和疾病风险的重要决定因素。本研究调查了 1970 年至 2003 年乌干达东南部昏睡病分布和发病率的决定因素，涵盖了整个流行区域和周期，并特别关注植被覆盖和变化。昏睡病数据是从乌干达卫生部、各个昏睡病治疗中心的记录以及对公共卫生官员的采访中收集的。从卫星图像中获取了流行期间四个日期（1973 年、1986 年、1995 年和 2001 年）的植被数据。零膨胀回归模型用于对疾病存在和严重程度的预测因子进行建模。评估了县级以下疾病发病率与归一化植被指数（NDVI）之间的相关性。结果表明，昏睡病感染主要与靠近水源和空间位置有关，而在中等到高 NDVI 的县中，疾病发病率最高。在整个研究期间，昏睡病发病率达到峰值的植被密度（NDVI）各不相同。能够支持昏睡病传播的最佳植被密度可能低于流行地区数据显示的水平，这表明在适当的条件下疾病传播的可能性增加。
Sleeping sickness is a major threat to human health in sub-Saharan Africa. Southeastern Uganda has experienced a number of significant epidemics in the past 100 years, most recently from 1976 to 1989. Recent and continued spread of the disease has highlighted gaps in the ability of current research to explain and predict the distribution of infection. Vegetation cover and changes in vegetation may be important determinants of transmission and disease risk because of the habitat preferences of the tsetse fly vector. This study examines the determinants of sleeping sickness distribution and incidence in southeastern Uganda from 1970 to 2003, spanning the full epidemic region and cycle, and focusing in particular on vegetation cover and change. Sleeping sickness data were collected from records of the Ugandan Ministry of Health, individual sleeping sickness treatment centers, and interviews with public health officials. Vegetation data were acquired from satellite imagery for four dates spanning the epidemic period, 1973, 1986, 1995, and 2001. Zero-inflated regression models were used to model predictors of disease presence and magnitude. Correlations between disease incidence and the normalized difference vegetation index (NDVI) at the subcounty level were evaluated. Results indicate that sleeping sickness infection is predominantly associated with proximity to water and spatial location, while disease incidence is highest in subcounties with moderate to high NDVI. The vegetation density (NDVI) at which sleeping sickness incidence peaked differed throughout the study period. The optimal vegetation density capable of supporting sleeping sickness transmission may be lower than indicated by data from endemic regions, indicating increased potential for disease spread under suitable conditions.