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

基本信息

批准号：
2026982
负责人：
Harold Vincent Poor
金额：
$ 7.5万
依托单位：
Princeton 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=2026982&HistoricalAwards=false
关键词：
RAPID Collaborative Research effects evolutionary

项目摘要

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.

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Fundamental limitations on efficiently forecasting certain epidemic measures in network models

网络模型中有效预测某些流行病指标的基本限制

DOI：
10.1073/pnas.2109228119
发表时间：
2022-01
期刊：
Proceedings of the National Academy of Sciences
影响因子：
0
作者：
Rosenkrantz, Daniel J.;Vullikanti, Anil;Ravi, S. S.;Stearns, Richard E.;Levin, Simon;Poor, H. Vincent;Marathe, Madhav V.
通讯作者：
Marathe, Madhav V.

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

利用带有突变的多菌株模型分析 Covid-19 的传播

DOI：
10.1109/icassp39728.2021.9414595
发表时间：
2021-06
期刊：
Speech and Signal Processing (ICASSP
影响因子：
0
作者：
Sridhar, Anirudh;Yagan, Osman;Eletreby, Rashad;Levin, Simon A.;Plotkin, Joshua B.;Poor, H. Vincent
通讯作者：
Poor, H. Vincent

Analyzing Social Distancing and Seasonality of COVID-19 with Mean Field Evolutionary Dynamics

用平均场进化动力学分析 COVID-19 的社交距离和季节性

DOI：
10.1109/gcwkshps50303.2020.9367567
发表时间：
2020-12
期刊：
2020 IEEE Globecom Workshops
影响因子：
0
作者：
Gao, Hao;Li, Wuchen;Pan, Miao;Han, Zhu;Poor, H. Vincent
通讯作者：
Poor, H. Vincent

A fiber optic–nanophotonic approach to the detection of antibodies and viral particles of COVID-19

用于检测 COVID-19 抗体和病毒颗粒的光纤-纳米光子方法

DOI：
10.1515/nanoph-2020-0357
发表时间：
2020-09-29
期刊：
Nanophotonics
影响因子：
7.5
作者：
Navid Rajil;A. Sokolov;Zhenhuan Yi;G. Adams;Girish Agarwal;V. Belousov;R. Brick;Kimberly R. Chapin;J. Cirillo;V. Deckert;Sahar Delfan;Shahriar Esmaeili;Alma Fernández;Edward Fry;Zehua Han;P. Hemmer;G. Kattawar;Moochan B. Kim;Ming;Chaoyang Lu;J. Mogford;Ben Neuman;Jian;Tao Peng;Vincent Poor;S. Scully;Y. Shih;S. Suckewer;A. Svidzinsky;A. Verhoef;Dawei Wang;Kai Wang;Lan Yang;A. Zheltikov;Shi;Suhail Zubairy;M. Scully
通讯作者：
M. Scully

Modeling COVID-19 with mean field evolutionary dynamics: Social distancing and seasonality

使用平均场进化动力学对 COVID-19 进行建模：社交距离和季节性