LARGE-SCALE AGENT-BASED MODELING OF WEAPONIZED BIOLOGICAL ATTACKS ON A REALISTI

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 生物武器项目的主要目标是发展计算能力，以生成在现实人口中传播的武器化疾病的足够细节的真实模拟。这个项目对于政策分析员、政策制定者、卫生官员、急救人员和普通民众来说非常重要，他们需要一个相当准确的工具来思考、计划和应对疾病制剂释放事件。除了生物恐怖主义，该项目对公共卫生总体上也非常重要。最近对严重急性呼吸系统综合症(SARS)的恐慌突出了这一点的重要性和紧迫性。Biowar是一个大规模的基于代理的社交网络模型，它描述了武器化疾病如何在人群中传播，已经在匹兹堡超级计算中心的几个系统上运行，包括Jonas。Biowar模拟通常为100,000个代理运行5个小时，为期2年的模拟时间段。Biowar代码的最后一个稳定版本是多线程的；我们最近刚刚为Cray XT3的S Catmount操作系统编译了没有线程的代码。我们只在很短的时间内访问了Lemieux(PSC)，所以没有开发并行版本的Biowar。此外，需要验证BIOWAR模拟，以赋予基本的社会和流行病学模拟足够的信心来使用，例如如何使用和信任天气模拟来预测即将到来的飓风。为此，我们正在开发一个名为Wizer的自动化验证工具。Biowar建立在有限状态机、构造认知-结构协同进化算法和社会网络的基础上。与使用程式化城市的传统模型不同，BIOWAR加载真实的城市人口统计数据、人口普查数据、地理边界、天气、学区等。与传统的流行病学模型不同，BIOWAR允许跟踪次要结果，如缺课和购买药品，以及感染和死亡率。Biowar已经模拟了圣地亚哥、旧金山、华盛顿特区、诺福克、汉普顿和匹兹堡。WIZER建立在具有因果推理、统计测试(例如边界检查)和本体论推理的产生式系统之上。Wizer接受模拟结果、模拟器因果图、模拟参数和经验数据的输入，并对应该更改哪些参数和元模型变量进行推理，以在模拟和经验数据之间产生更好的匹配。我们已经针对炭疽和天花的传统流行病学模型进行了BIOWAR人工验证。怀泽补充的是验证的自动化，它帮助人类专家对模拟结果进行推理，并建议下一次模拟应该是什么。该开发分配委员会(DAC)或匹兹堡超级计算中心的Cray XT3“BigBen”的启动请求的目的有六个方面：(1)在多个节点上运行非线程单处理器BIOWAR代码以收集用于模型验证的统计数据，(2)开发用于单个处理器的自动化验证工具(WIZER)，利用多节点BIOWAR运行的优势，(3)开发BIOWAR的并行版本，(4)开发BIZER的并行版本，(5)准备提交BIOWAR和WIZER的中等资源分配委员会(MRAC)提案，培训和熟悉Cray XT3开发环境，包括但不限于pgCC编译器、MPI-2消息传递库、Apprentice和Craypat性能工具、Totalview调试器。该生物武器项目得到了美国国防部高级研究计划局疾病监测拨款和陆军研究实验室的支持。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The main objective of the BioWar Project is to develop computational capability for generating realistic simulations in sufficient details of weaponized disease spread on a realistic population. This project is of great importance to policy analysts, policy makers, health officials, first responders, and common folks who need a reasonably accurate tool to think about, plan for, and respond to the event of disease agent release. In addition to bioterrorism, the project is of great importance to public health in general. The recent scare of Severe Acute Respiratory Syndrome (SARS) accentuates the importance and the urgency. BioWar, the large-scale agent-based social-network modeling of how weaponized diseases spread in a population, has run on several Pittsburgh Supercomputing Center's systems, including Jonas. The BioWar simulations typically run for 5 hours for 100,000 agents for 2 year simulation-time period. The last stable version of BioWar code is multithreaded; we just recently compiled the code without threading for Cray XT3's Catamount operating system. We had only a short time access to Lemieux (of PSC), so a parallel version of BioWar is not developed. Moreover, validation of BioWar simulations is needed to endow the basically social and epidemiological simulations with sufficient confidence to be used like how weather simulations are used and trusted to forecast incoming hurricanes. We are developing an automated validation tool called Wizer for this purpose. BioWar is built upon finite state machines, the Construct cognitive-structural co-evolution algorithm, and social networks. Unlike traditional models which use stylized cities, BioWar loads real city demographics, census data, geographical boundaries, weather, school districts, etc. And unlike conventional epidemiological models, BioWar allows tracking of secondary outcomes such as school absenteeism and drug purchase, in addition to infection and mortality rates. BioWar has simulated San Diego, San Francisco, DC, Norfolk, Hampton, and Pittsburgh. Wizer is built upon production systems enhanced with causal reasoning, statistical tests (e.g. bound checking), and ontological reasoning. Wizer takes the inputs of simulation outcome, simulator causal diagrams, simulation parameters, and empirical data, and performs reasoning about which parameter and meta-model variable should be changed to produce a better fit between the simulation and the empirical data. We have done manual validation of BioWar against conventional epidemiological models of anthrax and smallpox. What Wizer adds is the automation of validation, which assists human experts in reasoning about simulation outcomes and in suggesting what the next simulation should be. The purpose for this Development Allocations Committee (DAC) or start-up request of Cray XT3 "BigBen" at the Pittsburgh Supercomputing Center is six folds: (1) running non-threaded single-processor BioWar code on multiple-nodes to gather statistics for model validation, (2) developing automated validation tool (Wizer) for a single processor, taking advantage of multiple-node BioWar runs, (3) developing a parallel version of BioWar, (4) developing a parallel version of Wizer, (5) preparation for submitting a Medium Resource Allocations Committee (MRAC) proposal for BioWar and Wizer, and (6) training and familiarization of Cray XT3 development environment, including but not limited to pgCC compiler, MPI-2 message passing library, Apprentice and Craypat performance tools, and Totalview debugger. The BioWar project was supported by DARPA's Disease Surveillance grant and the Army Research Labs.