Real-time Identification of the Covid-19 Pandemic: Intelligent Toolset to Predict and Optimally Control Viral Outbreaks

实时识别 Covid-19 大流行：预测和优化控制病毒爆发的智能工具集

• 批准号: 553982-2020
• 负责人: Moallem, Mehrdad
• 金额: $ 3.64万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=704722
• 关键词: Real; time; Identification; Covid; 19

Mathematical modeling of infectious diseases received increased attention in the 1980s with the spread of the global pandemic Human Immunodeficiency Virus (HIV/AIDS). Pandemic outbreaks such as the Severe Acute Respiratory Syndrome (SARS), in 2003, and swine flu, in 2009, have highlighted the need and importance of mathematical and computer modeling as valuable tools that can help public health policy makers in making decisions about vaccination strategies, response plans, and control measures. The recent outbreak of Coronavirus pandemic throughout the world has shown the volatility of public health response plans and that the world was not prepared enough to face this kind of pandemic. In this project, we will develop computational models and identification algorithms for real-time estimation of the dynamic parameters of the Coronavirus pandemic. The goal is to develop improved computational modeling and identification algorithms for real-time estimation of the dynamic parameters of a pandemic infection such as the Coronavirus. The project will utilize published data from multiple sources along with control measures taken by government and health officials worldwide over the past few months regarding the evolution of the pandemic. The ultimate goal is to develop a software suite that can be used by policy makers and health officials to detect such outbreaks at early stages by estimating their parameters and predicting their evolution based on real-time data. The supporting company will look into further development and commercialization of the toolset for the health informatics market by developing a software package that can be quickly deployed for a range of custom use cases.

20 世纪 80 年代，随着人类免疫缺陷病毒 (HIV/AIDS) 在全球的传播，传染病的数学模型受到越来越多的关注。 2003 年的严重急性呼吸系统综合症 (SARS) 和 2009 年的猪流感等流行病爆发凸显了数学和计算机建模作为有价值的工具的必要性和重要性，可以帮助公共卫生政策制定者制定疫苗接种策略决策、响应计划和控制措施。最近在世界各地爆发的冠状病毒大流行表明，公共卫生应对计划的波动性以及世界没有做好足够的准备来应对这种流行病。 在这个项目中，我们将开发计算模型和识别算法，用于实时估计冠状病毒大流行的动态参数。目标是开发改进的计算模型和识别算法，用于实时估计冠状病毒等大流行感染的动态参数。该项目将利用多个来源发布的数据以及过去几个月世界各地政府和卫生官员针对疫情演变采取的控制措施。 最终目标是开发一套软件套件，供政策制定者和卫生官员使用，通过估计其参数并根据实时数据预测其演变，在早期阶段检测此类疫情。支持公司将通过开发可快速部署用于一系列自定义用例的软件包，研究健康信息学市场工具集的进一步开发和商业化。