Evaluating COVID-19 Mitigation Strategies in Schools with a Spatially-Explicit Agent-Based Model of Infection Dynamics

使用基于空间显式代理的感染动态模型评估学校的 COVID-19 缓解策略

基本信息

  • 批准号:
    2139740
  • 负责人:
  • 金额:
    $ 25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-10-01 至 2024-09-30
  • 项目状态:
    已结题

项目摘要

This project will develop and refine a simulation modeling system to help schools and school districts evaluate the effects of interventions to control COVID-19 infections among students, focusing first on schools in San Diego County, CA. The goal is to help individual schools choose the most effective strategies for their unique circumstances, particularly each school’s population, classroom layouts and ventilation, neighborhood infection rates, and school bus commutes. The interactive model will allow decision makers at the school and district levels to evaluate the potential impacts of both pharmaceutical interventions, like vaccination and testing, and non-pharmaceutical safety measures including social distancing, mask-wearing, limiting interactions between different student cohorts, decreasing classroom occupancy, and improving ventilation. Finding the best combination of such measures is central to safe school re-opening, which is critical for improving child education and development and allowing parents to return to work. As school-aged children, many of whom are not vaccinated, are disproportionately affected by new and more dangerous COVID-19 variants, this simulation service will provide much-needed insights to our partners among decision-makers at the school and district level in San Diego County and elsewhere in the nation. The school infection model simulates aerosol and droplet transmission as students, teachers, and staff (modeled as human agents) interact during typical school day activities, including classroom instruction, cafeteria lunch, recess, and traveling on a school bus. The likelihood that a healthy agent is exposed to the virus increases as they come near infected, asymptomatic agents or spend significant time in poorly ventilated spaces. The model considers spatial information about room layouts and ventilation, and simulates school day schedules down to 5-minute intervals. Building on a successful prototype for elementary schools, this project will extend the model to middle and high schools and to neighborhoods with different socio-economic and demographic characteristics. Additionally, it will enable simulation of infection dynamics for athletics activities and analysis of infection patterns under different COVID-19 variants. Making the model accessible via a science gateway will let school administrators, researchers, teachers, and students run simulations on a supercomputer, then visualize and compare model outputs under different scenarios. As in the prototype phase, the project will engage undergraduate students in all aspects of model development, and in presenting results to public health and education experts and to the general public – an essential component of their training as data scientists working on societally-impactful topics like education and health equity.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.
该项目将开发和完善一个模拟建模系统,以帮助学校和学区评估控制学生COVID-19感染的干预措施的效果,首先关注加利福尼亚州圣地亚哥县的学校。其目标是帮助个别学校根据其独特的情况选择最有效的策略,特别是每所学校的人口,教室布局和通风,社区感染率和校车通勤。 互动模型将允许学校和地区层面的决策者评估药物干预措施(如疫苗接种和检测)和非药物安全措施(包括社交距离,戴口罩,限制不同学生群体之间的互动,减少教室占用率和改善通风)的潜在影响。找到这些措施的最佳组合是安全学校重新开放的核心,这对改善儿童教育和发展以及让父母重返工作岗位至关重要。由于学龄儿童(其中许多人没有接种疫苗)受到新的和更危险的COVID-19变种的不成比例的影响,这项模拟服务将为我们在圣地亚哥县和全国其他地方的学校和地区层面的决策者提供急需的见解。学校感染模型模拟了学生、教师和工作人员(模拟为人类代理)在典型的学校活动中相互作用时的气溶胶和飞沫传播,这些活动包括课堂教学、食堂午餐、课间休息和乘坐校车。健康的病原体接触病毒的可能性随着他们接近感染的、无症状的病原体或在通风不良的空间中度过相当长的时间而增加。该模型考虑了有关房间布局和通风的空间信息,并模拟了每隔5分钟的学校日程安排。该项目以小学的成功原型为基础,将把这一模式推广到初中和高中以及具有不同社会经济和人口特征的社区。此外,它将能够模拟体育活动的感染动态,并分析不同COVID-19变体下的感染模式。通过科学网关访问模型将使学校管理人员,研究人员,教师和学生在超级计算机上运行模拟,然后在不同的场景下可视化和比较模型输出。与原型阶段一样,该项目将让本科生参与模型开发的各个方面,并向公共卫生和教育专家以及公众展示结果-这是他们作为社会数据科学家培训的重要组成部分-该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准。

项目成果

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Ilya Zaslavsky其他文献

Community utilization of a co-created COVID-19 testing program in a US/Mexico border community
  • DOI:
    10.1186/s12889-024-20527-4
  • 发表时间:
    2024-11-18
  • 期刊:
  • 影响因子:
    3.600
  • 作者:
    Breanna J. Reyes;Stephenie Tinoco Calvillo;Arleth A. Escoto;Angel Lomeli;Maria Linda Burola;Luis Gay;Ariel Cohen;Isabel Villegas;Linda Salgin;Kelli L. Cain;Dylan Pilz;Paul Watson;Bill Oswald;Cesar Arevalo;Jessica Sanchez;Marjorie Richardson;Jennifer Nelson;Pricilla Villanueva;Garrett McGaugh;Ilya Zaslavsky;Robert H. Tukey;Nicole A. Stadnick;Borsika A. Rabin;Louise C. Laurent;Marva Seifert
  • 通讯作者:
    Marva Seifert
Service-Oriented Architecture
  • DOI:
    10.1007/978-3-319-17885-1_1199
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ilya Zaslavsky
  • 通讯作者:
    Ilya Zaslavsky
Looking back and to the future of the INCF Digital Atlasing Program
INCF 数字地图计划的回顾和未来
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jyl Boline;Mike Hawrylycz;Ilya Zaslavsky;INCF Digital Atlasing Standards;Waxholm Space;and Digital Atlasing Infrastructure Task Forces
  • 通讯作者:
    and Digital Atlasing Infrastructure Task Forces

Ilya Zaslavsky的其他文献

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{{ truncateString('Ilya Zaslavsky', 18)}}的其他基金

Collaborative Research: EAGER: IMPRESS-U: Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine (GRANDE-U)
合作研究:EAGER:IMPRESS-U:通过乌克兰综合数据探索进行地下水恢复力评估 (GRANDE-U)
  • 批准号:
    2409395
  • 财政年份:
    2024
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Conference: Towards a mass shooting early alert network by modeling 9-1-1 data streams
会议:通过对 9-1-1 数据流建模建立大规模枪击早期警报网络
  • 批准号:
    2330460
  • 财政年份:
    2023
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EarthCube Building Blocks: Collaborative Proposal: EarthCube Data Discovery Hub
EarthCube 构建模块:协作提案:EarthCube 数据发现中心
  • 批准号:
    1639764
  • 财政年份:
    2016
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EarthCube IA: Collaborative Proposal: Interdisciplinary Earth Data Alliance as a Model for Integrating Earthcube Technology Resources and Engaging the Broad Community
EarthCube IA:协作提案:跨学科地球数据联盟作为整合 Earthcube 技术资源和广泛社区参与的模型
  • 批准号:
    1540945
  • 财政年份:
    2015
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EarthCube Building Blocks Collaborative Proposal: Digital Crust ? An Exploratory Environment for Earth Science Research and Learning
EarthCube 构建块协作提案:数字地壳?
  • 批准号:
    1440301
  • 财政年份:
    2014
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EAGER: Development of a Novel Online Visual Survey Data Analysis Tool and Assessment of its Capabilities to Enhance Learning of Quantitative Research Methods
EAGER:开发新型在线视觉调查数据分析工具并评估其增强定量研究方法学习的能力
  • 批准号:
    1443082
  • 财政年份:
    2014
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EarthCube Building Blocks: Community Inventory of EarthCube Resources for Geoscience Interoperability (CINERGI)
EarthCube 构建模块:用于地球科学互操作性的 EarthCube 资源社区清单 (CINERGI)
  • 批准号:
    1343816
  • 财政年份:
    2013
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EarthCube Conceptual Design: Enterprise Architecture for Transformative Research and Collaboration Across the Geosciences
EarthCube 概念设计:跨地球科学领域变革性研究与协作的企业架构
  • 批准号:
    1343813
  • 财政年份:
    2013
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Collaborative Research: SI2-SSI: The Community-Driven Big-CZ Software System for Integration and Analysis of Bio- and Geoscience Data in the Critical Zone
合作研究:SI2-SSI:社区驱动的 Big-CZ 软件系统,用于整合和分析关键区域的生物和地球科学数据
  • 批准号:
    1339793
  • 财政年份:
    2013
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
EAGER: Readiness of Disciplinary Data Systems for Cross-Domain Interoperability within a Standards-Based EarthCube Reference Framework
EAGER:学科数据系统已准备好在基于标准的 EarthCube 参考框架内实现跨域互操作性
  • 批准号:
    1238420
  • 财政年份:
    2012
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant

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