登录
 机构网站
  1. 首页
  2. 情报产品
  3. 快讯详情

《MedRxiv，3月21日，Building a COVID-19 Vulnerability Index》

  • 来源专题：COVID-19科研动态监测
  • 编译者： zhangmin
  • 发布时间：2020-03-23

  • Building a COVID-19 Vulnerability Index

    Dave DeCaprio, Joseph A Gartner III, Thadeus Burgess, Sarthak Kothari, Shaayaan Sayed, Carol J McCall

    doi: https://doi.org/10.1101/2020.03.16.20036723

    Abstract

    COVID-19 is an acute respiratory disease that has been classified as a pandemic by the World Health Organization. Information regarding this particular disease is limited, however, it is known to have high mortality rates, particularly among individuals with preexisting medical conditions. Creating models to identify individuals who are at the greatest risk for severe complications due to COVID-19 will be useful to help for outreach campaigns in mitigating the diseases worst effects. While information specific to COVID-19 is limited, a model using complications due to other upper respiratory infections can be used as a proxy to help identify those individuals who are at the greatest risk. We present the results for three models predicting such complications, with each model having varying levels of predictive effectiveness at the expense of ease of implementation.

    *注，本文为预印本论文手稿，是未经同行评审的初步报告，其观点仅供科研同行交流，并不是结论性内容，请使用者谨慎使用.

  • 原文来源：https://www.medrxiv.org/content/10.1101/2020.03.16.20036723v1
99浏览量
原文链接
相关报告

  • 《3月21日_构建COVID-19脆弱性指数》
    • 来源专题：COVID-19科研动态监测
    • 编译者：zhangmin
    • 发布时间：2020-03-24
    • 1.时间：2020年3月21日 2.机构或团队：美国ClosedLoop.ai公司 3.事件概要： 美国ClosedLoop.ai公司在medRxiv预印版平台发表论文“Building a COVID-19 Vulnerability Index”，文章通过构建COVID-19脆弱性指数以识别可能更容易遭受COVID-19严重并发症的人群。 文章称COVID-19是一种急性呼吸系统疾病，这种特殊疾病的信息是有限的，然而，众所周知，它有很高的死亡率，特别是在患有既往疾病的个体中。建立模型以识别因COVID-19而导致严重并发症的风险最高的个体，将有助于开展宣传活动，以减轻疾病的最严重影响。尽管COVID-19的特异性信息有限，但利用其他上呼吸道感染引起的并发症的模型可以作为一个替代模型来帮助识别风险最大的个体。文章提供了三种模型预测此类并发症的结果，每种模型具有不同水平的预测有效性。研究人员希望通过将这些模型快速提供给医疗保健数据科学界，广泛采用将导致更有效的干预策略，并最终帮助减少这种流行病的最坏影响。 *注，本文为预印本论文手稿，是未经同行评审的初步报告，其观点仅供科研同行交流，并不是结论性内容，请使用者谨慎使用。 4.附件： 原文链接：https://www.medrxiv.org/content/10.1101/2020.03.16.20036723v1
    52浏览量
    原文链接

  • 《MedRxiv，3月18日，Understanding Epidemic Data and Statistics: A case study of COVID-19》
    • 来源专题：COVID-19科研动态监测
    • 编译者：zhangmin
    • 发布时间：2020-03-19
    • Understanding Epidemic Data and Statistics: A case study of COVID-19 Amirhoshang Hoseinpour Dehkordi, Majid Alizadeh, Pegah Derakhshan, Peyman Babazadeh, Arash Jahandideh doi: https://doi.org/10.1101/2020.03.15.20036418 Abstract The 2019-Novel-Coronavirus (COVID-19) has affected 115 countries and out of more than 118,000 confirmed cases. Understanding the transmission dynamics of the infection in each country which affected on a daily basis and evaluating the effectiveness of control policies is critical for our further actions. To date, the statistics of COVID-10 reported cases show more than 80 percent of infected had a mild case of disease, while around 14 percent of infected experienced a severe one and about 5 percent are categorized as critical disease victims. Today's report (2020-03-12; daily updates in the prepared website) shows the confirmed cases of COVID-19 in China, South Korea, Italy, and Iran are 80932, 7869, 12462 and 10075; respectively. *注，本文为预印本论文手稿，是未经同行评审的初步报告，其观点仅供科研同行交流，并不是结论性内容，请使用者谨慎使用.
    109浏览量
    原文链接