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.

随着人类免疫缺陷病毒（HIV/AIDS）在全球范围内的传播，传染病的数学建模在20世纪80年代受到了越来越多的关注。2003年的严重急性呼吸系统综合征（SARS）和2009年的猪流感等大流行病的爆发，突出了数学和计算机建模的必要性和重要性，这些建模是有价值的工具，可以帮助公共卫生政策制定者制定疫苗接种策略，应对计划和控制措施。最近全球爆发的冠状病毒大流行显示公共卫生应对计划的波动性，以及世界对面对此类大流行病的准备不足。 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建模和识别算法，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沿着公布的数据，以及世界各地政府和卫生官员在过去几个月里就该流行病的演变采取的控制措施。 最终目标是开发一套软件，供决策者和卫生官员使用，通过估计疫情参数和根据实时数据预测疫情演变，在早期阶段发现疫情。支持公司将通过开发一个可以快速部署用于一系列自定义用例的软件包，来研究健康信息学市场工具集的进一步开发和商业化。