基于GIS的城市流动的人际传染综合流行病学模拟

Hedi Haddad, B. Moulin, M. Thériault, Daniel Navarro-Velazquez
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引用次数: 2

摘要

近年来,健康地理学、地理流行病学和公共卫生信息学的进展使得地理信息系统(GIS)被广泛用于研究各种公共卫生问题。考虑到传染病暴发,时间成为一个关键因素,公共卫生官员需要工具来支持快速决策。在这种背景下,GIS技术呈现出一些局限性。主要是传染病的研究需要建立复杂的时空模型,这往往是费时费力的。此外,这种类型的动态分析很难通过现有的GIS功能来实现。针对这些限制,我们在本文中提出了一种新的基于gis的时空模拟方法和软件,以支持传染病背景下的公共卫生决策。我们的方法以其提供的综合视角和明确的空间方面脱颖而出。一方面,它在总人口一级充分整合流行病学、人口流动和地理信息系统数据模型,以支持公共卫生决策。这之所以成为可能,是因为我们的方法是建立在自动处理的交通调查数据之上的,这些数据是广泛可用的,至少在北美和欧洲是这样。因此,我们的方法很简单,可以迅速投入使用。另一方面,我们的方法特别旨在支持决策者关于“空间化”干预政策。主要是对研究区不同空间位置的不同公共干预行动进行评估,评价其对疾病空间演变和分布的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated epidemiologic simulation for person to person contagion through urban mobility within GIS
In recent years, advances in Health Geography, Geographical Epidemiology and Public Health Informatics have led to an extensive use of Geographic Information Systems (GIS) to study a variety of public health issues. Considering infectious disease outbreaks, time becomes a critical factor and Public Health officers require tools to support rapid decision making. In this context, GIS technology presents some limits. Mainly, the study of communicable diseases requires the development of complicated spatial-temporal models which is often time and effort consuming. In addition, this type of dynamic analysis is hard to realize by means of the GIS functionalities commonly available. Addressing such limits, we present in this paper a new GIS-based spatial-temporal simulation approach and software to support public health decision making in the context of communicable diseases. Our approach stands out by the integrative perspective and the explicit spatial aspect that it offers. On the one hand, it fully integrates epidemiological, mobility and GIS-data models at an aggregate population level in order to support public health decision making. This is made possible because our approach is built on data automatically processed from transportation surveys that are widely available, at least in North America and Europe. Our approach is thus simple and can be promptly put into use. On the other hand, our approach particularly aims at supporting decision makers with respect to "spatialized" intervention policies. Mainly, it allows for the assessment of different public intervention actions in different spatial locations of the studied area and the evaluation of their effects on the disease spatial evolution and distribution.
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