SIRTEM:基于空间信息的流行病建模和COVID-19响应快速测试

IF 1.2 Q4 REMOTE SENSING
Fahim Tasneema Azad, Robert W. Dodge, Allen M. Varghese, Jaejin Lee, Giulia Pedrielli, K. Candan, Gerardo Chowell-Puente
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引用次数: 2

摘要

2020年3月11日,世界卫生组织宣布新冠肺炎疫情为大流行。为了最大限度地减少伤亡和对经济的影响,已经采取了各种缓解措施来减缓感染的传播,例如完全封锁、保持社交距离和随机检测。这篇文章的主要贡献有两方面。首先,我们提出了一种新的扩展的空间知情流行病模型SIRTEM,用于新冠肺炎流行病建模和响应的空间知情快速测试,该模型集成了考虑测试准确性的多模式测试策略。我们的第二个贡献是一个优化模型,当有多种测试类型可用时,它可以提供一种具有成本效益的测试策略。所开发的优化模型包含了现实的基于空间的约束,如检测能力和病床限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SIRTEM: Spatially Informed Rapid Testing for Epidemic Modeling and Response to COVID-19
COVID-19 outbreak was declared a pandemic by the World Health Organization on March 11, 2020. To minimize casualties and the impact on the economy, various mitigation measures have being employed with the purpose to slow the spread of the infection, such as complete lockdown, social distancing, and random testing. The key contribution of this article is twofold. First, we present a novel extended spatially informed epidemic model, SIRTEM, Spatially Informed Rapid Testing for Epidemic Modeling and Response to COVID-19, that integrates a multi-modal testing strategy considering test accuracies. Our second contribution is an optimization model to provide a cost-effective testing strategy when multiple test types are available. The developed optimization model incorporates realistic spatially based constraints, such as testing capacity and hospital bed limitation as well.
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来源期刊
CiteScore
4.40
自引率
5.30%
发文量
43
期刊介绍: ACM Transactions on Spatial Algorithms and Systems (TSAS) is a scholarly journal that publishes the highest quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective in that it spans a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually) such as geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.
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