Using GIS to create synthetic disease outbreaks
Using GIS to create synthetic disease outbreaks
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DOI：
10.1186/1472-6947-7-4
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发表时间：
2007-02-14
影响因子：
3.5
通讯作者：
Plant, Aileen J.
中科院分区：
文献类型：
--
作者：
Watkins, Rochelle E.;Eagleson, Serryn;Plant, Aileen J.
背景：早期发现疾病暴发的能力是有效控制和预防疾病的一个关键组成部分。随着电子医疗保健数据和时空分析技术的日益普及，开发算法以实现更有效的疾病监测的潜力很大。然而，为了确保算法是有效的，需要对其进行评估。为开发一种透明、友好的时空疾病爆发数据模拟方法，用于疾病爆发检测算法的评估，提出了一种基于状态转移的疾病爆发模型，该模型使用指定的疾病特异性参数，以日常时间步长模拟疾病爆发，用于模拟人与人接触传播的传染病传播。该软件是使用MapBasic编程语言开发的MapInfo专业地理信息系统environment.Results：开发的模拟模型是一个通用的和灵活的模型，它利用了人口的基本分布，并结合了疾病的传播模式，可以定制代表一系列的传染病和地理位置。该模型提供了一种方法来探索爆发检测算法的能力，以检测各种事件在大量的随机复制的不确定性的影响可以控制。该软件还允许历史数据，这是从已知的爆发与模拟爆发数据相结合，以产生文件的算法性能assessment.Conclusion：该模拟模型提供了一种灵活的方法来生成数据，这可能是有用的爆发检测算法的性能的评估和比较。
Background: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation.A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment.Results: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment.Conclusion: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance.