Fuzzy expert systems and GIS for cholera health risk prediction in southern Africa
Fuzzy expert systems and GIS for cholera health risk prediction in southern Africa
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DOI：
10.1016/j.envsoft.2005.12.008
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发表时间：
2007-04-01
影响因子：
4.9
通讯作者：
McFerren, Graeme
中科院分区：
文献类型：
--
作者：
Fleming, Gavin;van der Merwe, Mama;McFerren, Graeme
霍乱（霍乱弧菌）是南部非洲的地方病，经常在东部沿海沿着爆发流行病。为防治霍乱投入了大量资源，但霍乱仍然是一个严重问题。如果有可能在空间和时间上评估疾病暴发的风险，就可以更好地将有限的资源用于预防疾病暴发。南非的科学和工业研究委员会正在研究根据国家优先事项预测健康风险的技术。本文介绍了一个早期预警地理信息系统原型工具，旨在确定有利的先决条件，霍乱爆发。这些先决条件是使用专家系统方法定义的。由此确定的变量输入到一个空间模糊逻辑模型，输出风险。该模型是基于这样的假设，即发生霍乱的地方性水库，以及环境条件，特别是藻华，触发自然环境中的弧菌生长。如果这些先决条件得到满足，霍乱随后的传播主要取决于社会经济因素，如人的行为和获得安全供水和卫生设施的机会。本文重点论述了环境前提条件。所述方法依赖于获取专家知识和历史数据，将气候和生物物理参数与流行病学数据相结合，以产生霍乱暴发风险潜力的模糊表面。(c)2006爱思唯尔有限公司保留所有权利。
Cholera (Vibrio cholerae) is endemic in southern Africa and frequently breaks out in epidemics along the eastern seaboard. Extensive resources are directed at combating cholera yet it remains a significant problem. Limited resources could better be directed to prevent outbreaks if it were possible to assess the risk of an outbreak in space and time. The CSIR in South Africa is investigating technologies to predict health risk in line with national priorities. This paper describes an early warning GIS prototype tool aimed at identifying favourable preconditions for cholera outbreaks. These preconditions were defined using an expert system approach. The variables thus identified were input into a spatial fuzzy logic model that outputs risks. The model is based on the assumption that endemic reservoirs of cholera occur and that environmental conditions, especially algal blooms, trigger Vibrio growth in the natural environment. If the preconditions are met, the subsequent spread of cholera depends mainly on socio-economic factors such as human behaviour and access to safe water supply and sanitation. This paper focuses on the environmental preconditions. The methodology described relies on capturing expert knowledge and historic data that integrate climatic and biophysical parameters with epidemiological data to produce a fuzzy surface of cholera outbreak risk potential. (c) 2006 Elsevier Ltd. All rights reserved.