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SCH: EXP: Smart integration of community crowdsourced data for real-time individualized disease risk assessment

SCH: EXP: Smart integration of community crowdsourced data for real-time individualized disease risk assessment
SCH:EXP:智能整合社区众包数据,进行实时个体化疾病风险评估
批准号:
1551036
负责人:
Rumi Chunara
金额:
$45.75万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-08-01 至 2017-09-30

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中文摘要
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英文摘要
This project addresses a major inefficiency in healthcare today: an under-informed, homogeneous approach to patient care that doesn't consider community disease prevalence and its effect on an individual's disease risk in an actionable manner. The approach is to combine real-time diagnostic information from select community members via an easy to use, gargle-based immunoassay detection test with more abundant contemporaneous community symptom reports via an online informatics platform. The hypothesis is that the likelihood of a virological diagnosis of influenza (flu) can be accurately predicted for the individual using real-time flu self-diagnostics and symptom information from their community, and can influence a user to take appropriate measures to prevent disease spread. This approach enables testing of several concepts regarding (1) the specificity and sensitivity of a rapid flu diagnostic test for Influenza A and B detection compared to a laboratory polymerase chain reaction test, (2) generation of valid user-contributed diagnostic information at scale (3), potential of real-time contextual data to be used to calculate influenza risk, (4) use and acceptance of this information by individuals. The team brings together experience in building and studying novel crowdsourced data sources for disease surveillance and expertise in software, graphic design, epidemiology, medicine, and engineering, to develop user-friendly systems that the community will employ at scale.The proposed system has substantial potential for beneficial societal impact through acertaining and changing the way people approach healthcare. Empowering individuals to generate and act on health information impresses on them the importance of surveillance and educates them to become more involved and accountable for their health. In order to maximize the impact and sustainability of the system, this system also functions as an educational tool. Clear open communication of anonymized and privacy-protected data to the general public in an easy to interpret manner will assist individuals, policy-makers and other researchers in using contextual disease risk information. Undergraduate and graduate students from a variety of backgrounds will have opportunity to participate in the research. Collaborators at the American Public Health Association and their associated groups concerned with the health of minority populations such as The Association of Minority Health Professions Schools and The Latina Health Project will assist in engaging a diverse group of participants nationwide.
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CAREER: Learning from When, Where and by Whom Data is Generated for Advancing Public Health Studies
  • 批准号:
    1845487
  • 项目类别:
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  • 资助金额:
    $55.0万
  • 财政年份:
    2019
  • 负责人:
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  • 依托单位:
ATD: Collaborative Research: Algorithms and Data for High-Frequency, Real-Time Anomaly Detection
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    1737987
  • 项目类别:
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  • 资助金额:
    $10.0万
  • 财政年份:
    2017
  • 负责人:
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EAGER: Collaborative Research: Combining Community and Clinical Data for Augmenting Influenza Modeling
  • 批准号:
    1643576
  • 项目类别:
    Standard Grant
  • 资助金额:
    $18.09万
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    2016
  • 负责人:
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SCH: EXP: Smart integration of community crowdsourced data for real-time individualized disease risk assessment
  • 批准号:
    1343968
  • 项目类别:
    Standard Grant
  • 资助金额:
    $67.3万
  • 财政年份:
    2013
  • 负责人:
    Rumi Chunara
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