COVID-19 Pandemic Vulnerability

COVID-19 流行病脆弱性

• 批准号: 10928616
• 负责人: Alison Motsinger-Reif
• 金额: $ 110.97万
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10928616
• 关键词: Address; Archives; COVID-19 pandemic; Communication; County; Data; Data Set; Decision Making; Development; Disease; Disparate; Emergency Situation; Government; Health; Incidence; Knowledge; Machine Learning; Methods; Modeling; Monitor; Resources; Update; Visualization; Visualization software; Weight; Work; dashboard; data streams; effective intervention; indexing; pandemic disease; predictive modeling; response; trend

There have been multiple updates to the PVI Dashboard as the emergency status of the pandemic has ended. The major use case of the Dashboard has moved from resource prioritization to the use and citation of the data collected in the model. We have also archived the Dashboard with a clear cutoff date for the data as many data streams have become unavailable. There has additionally been methods work in for the method that produces both the vulnerability ranks across counties and underlies the visualization tool. Jonathan Fleming has worked on developing and implementing a machine learning approach to optimize the weights for different data streams. Previously the weight have required expert knowledge by the analysis, but with the new method can be quantitatively determined using a minimal number of reference observations.

随着疫情紧急状态结束，PVI仪表板已多次更新。 仪表板的主要使用案例已从资源优先排序转向使用和引用模型中收集的数据。 由于许多数据流已不可用，我们还将仪表板存档，并为数据提供了明确的截止日期。 此外，还有方法工作的方法，产生跨县的脆弱性排名和可视化工具的基础。 Jonathan Fleming致力于开发和实现一种机器学习方法，以优化不同数据流的权重。 以前的重量需要专家知识的分析，但与新的方法可以定量确定使用最少数量的参考意见。