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

该项目解决了当今医疗保健效率低下的一个主要问题：对患者护理的信息不足、同质化的方法，没有以可操作的方式考虑社区疾病流行及其对个人疾病风险的影响。该方法是通过一种易于使用的、基于漱口水的免疫分析检测测试，将来自选定社区成员的实时诊断信息与通过在线信息学平台提供的更丰富的同期社区症状报告相结合。其假设是，使用来自社区的实时流感自我诊断和症状信息，可以准确预测个人对流感（流感）进行病毒学诊断的可能性，并可以影响用户采取适当措施防止疾病传播。这种方法可以测试以下几个概念：(1)与实验室聚合酶链反应测试相比，快速流感诊断测试检测甲型和乙型流感的特异性和敏感性；(2)大规模生成有效的用户贡献诊断信息；(3)实时上下文数据用于计算流感风险的潜力；(4)个人对这些信息的使用和接受程度。该团队汇集了在建立和研究用于疾病监测的新型众包数据源方面的经验，以及软件、平面设计、流行病学、医学和工程方面的专业知识，以开发社区将大规模使用的用户友好系统。提议的系统通过促进和改变人们对待医疗保健的方式，对有益的社会影响具有巨大的潜力。赋予个人能力，使他们能够产生卫生信息并根据这些信息采取行动，从而使他们认识到监测的重要性，并教育他们更多地参与并对自己的健康负责。为了使系统的影响和可持续性最大化，该系统还可以作为教育工具。以一种易于解释的方式向公众公开公开匿名和隐私保护数据，将有助于个人、决策者和其他研究人员使用相关疾病风险信息。来自不同背景的本科生和研究生将有机会参与研究。美国公共卫生协会的合作者及其与少数民族人口健康有关的相关团体，如少数民族卫生专业学校协会和拉丁裔卫生项目，将协助动员全国不同群体的参与者。

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.