计算流行病学的交互式、基于网络的高性能建模环境。

IF 2.5 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Suruchi Deodhar, Keith R Bisset, Jiangzhuo Chen, Yifei Ma, Madhav V Marathe
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引用次数: 15

摘要

我们提出了一个集成的交互式建模环境,以支持公共卫生流行病学。该环境将高分辨率的基于个人的模型与用户友好的基于web的界面相结合,该界面允许分析人员从桌面或移动设备远程访问模型和分析后端。该环境基于松散耦合的面向服务的体系结构,允许分析人员探索各种反事实场景。随着公共卫生流行病学的建模工具变得越来越复杂,非计算科学家越来越难以有效地使用包含这些模型的系统。因此,集成建模环境的一个重要设计考虑因素是提高易用性,以便实验模拟可以由用户驱动。这是通过设计直观和用户友好的界面来实现的,允许用户设计和分析计算实验,并根据系统的状态引导实验。支持这一设计目标的系统的一个关键特征是能够交互式地启动、停止、暂停和回滚疾病传播和干预应用过程。分析人员可以在任何时间点访问系统的状态,并根据通过状态评估获得的附加信息制定动态干预措施。此外,该环境为实验设置和管理提供自动化服务,从而减少了进行端到端实验研究的总体时间。我们通过描述基于现实流行病规划情景的计算实验来说明该系统的适用性。实验旨在证明系统的功能和提高用户的工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

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来源期刊
ACM Transactions on Management Information Systems
ACM Transactions on Management Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
6.30
自引率
20.00%
发文量
60
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