RAPID: Collaborative Research: The effects of evolutionary adaptations on the spreading of COVID-19

RAPID：合作研究：进化适应对 COVID-19 传播的影响

• 批准号: 2026985
• 负责人: Osman Yagan
• 金额: $ 7.5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026985&HistoricalAwards=false
• 关键词: RAPID; Collaborative; Research; effects; evolutionary

Started in December 2019, the novel coronavirus (known to cause a respiratory disease known as COVID-19) has spread rapidly and broadly and is proving to be one of the most devastating events that affect the health and well-being of humans all around the world. A key scientific goal concerning COVID-19 is to develop mathematical models that help in understanding and predicting its spreading behavior, as well as supporting guidelines on what can be done to limit its spread. In this project, the PIs aim to achieve these goals by applying their recent findings on a new epidemic model to the spread of COVID-19. The PIs will work on a model that considers the possibility of COVID-19 mutating into different strains with different spreading characteristics. By also considering changes in the spreading behavior of COVID-19 due to environmental factors and changes in human behavior (seasonal changes, travel bans, etc.), they aim to obtain results that will help assess the effectiveness of countermeasures that can be taken against the spread of the virus and to help better prepare for different mutation scenarios, including worst-cases. Most existing models of epidemics assume that an infectious individual passes the same pathogen strain that she was infected with to a susceptible individual in her contact network. This assumption may not hold in real-life as pathogens often evolve over time, and the ways a pathogen evolves might lead to significant changes in its spreading dynamics. This project aims to improve the state-of-the-art mathematical and computational models for predicting the spread of COVID-19 to incorporate the effects of evolution and mutations. This will be done by leveraging recent work of the PIs in which they developed a mathematical model to predict the spreading dynamics for multiple-strain epidemics models with mutations. By incorporating the potential changes in the reproduction number R0 (due to countermeasures or mutations), the PIs aim to obtain a better understanding of the future progress of the COVID-19 spread; obtain different predictions of the spread of COVID-19 under different scenarios including extensive bans on travel, school/shop closures, as well as potential evolution into different strains; and add to the public discourse on the expected effectiveness of various countermeasures that can be taken to slow down the spread of COVID-19. Project outcomes will be disseminated broadly and incorporated into teaching curricula. The project will also engage students from underrepresented groups.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

始于2019年12月，新型的冠状病毒（已知引起的呼吸道疾病称为Covid-19）已迅速而广泛地传播，事实证明，这是影响世界各地人类健康和福祉的最毁灭性的事件之一。关于Covid-19的关键科学目标是开发数学模型，以帮助理解和预测其传播行为，并支持有关限制其传播的方法的指南。在这个项目中，PI通过将其最新的发现在新的流行病模型上应用于Covid-19的传播，旨在实现这些目标。 PI将在一个模型上使用，该模型认为COVID-19将其突变为具有不同传播特征的不同菌株。通过考虑环境因素和人类行为的变化（季节性变化，旅行禁令等）导致Covid-19的扩散行为的变化，它们的目标是获得结果，以帮助评估可以评估病毒传播并帮助更好地准备不同突变场景的对抗的有效性，以包括最差的情况，包括最差的情况。大多数现有的流行病模型都认为，感染性的人通过与她的接触网络中易感人相同的病原体菌株传递。随着病原体通常会随着时间的流逝而演变，并且病原体演变可能导致其扩散动力学变化的重大变化，因此这种假设可能不会存在。该项目旨在改善最新的数学和计算模型，以预测COVID-19的传播以纳入进化和突变的影响。这将通过利用PI的最新工作来完成，在该工作中，他们开发了一个数学模型来预测具有突变的多种晶体流行病模型的扩散动力学。通过纳入繁殖数R0的潜在变化（由于对策或突变），PIS旨在更好地了解Covid-19的未来进步。在不同的情况下，在包括广泛的旅行，学校/商店关闭以及潜在发展为不同菌株的不同情况下，获得了Covid-19的传播的不同预测；并增加了有关各种对策的预期有效性，可以采取的预期有效性，以减缓19 covid-19的蔓延。项目成果将广泛传播，并将其纳入教学课程中。该项目还将吸引来自代表性不足的小组的学生。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来评估值得支持的。

项目成果

Analysis of the Impact of Mask-wearing in Viral Spread: Implications for COVID-19

分析戴口罩对病毒传播的影响：对 COVID-19 的影响

• DOI: 10.23919/acc50511.2021.9482733
• 发表时间: 2021
• 期刊: 2021 American Control Conference (ACC
• 作者: Tian, Yurun;Sridhar, Anirudh;Yagan, Osman;Poor, H. Vincent
• 通讯作者: Poor, H. Vincent

Leveraging A Multiple-Strain Model with Mutations in Analyzing the Spread of Covid-19

• DOI: 10.1109/icassp39728.2021.9414595
• 发表时间: 2021-06
• 期刊: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
• 作者: Anirudh Sridhar;Osman Yağan;Rashad M. Eletreby;S. Levin;J. Plotkin;H. Poor

The Interplay of Clustering and Evolution in the Emergence of Epidemics on Networks

网络流行病出现时集群与进化的相互作用

• DOI: 10.1109/icc45041.2023.10279814
• 发表时间: 2023
• 期刊: IEEE International Conference on Communications
• 作者: Sood, Mansi;Eletreby, Rashad;Kumar, Swarun;Wu, Chai Wah;Yağan, Osman
• 通讯作者: Yağan, Osman