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

这个项目解决了当今医疗保健中一个主要的低效问题：一种信息不足、同质化的病人护理方法，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。该方法是通过易于使用的、基于漱口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平台更丰富的同期社区症状报告相结合。该假设是，使用实时流感自我诊断和来自其社区的症状信息，可以准确地为个人预测流感(流感)的病毒学诊断的可能性，并可以影响用户采取适当的措施来防止疾病传播。这一方法能够测试以下几个概念：(1)与实验室聚合酶链式反应检测相比，甲型和乙型流感快速诊断试验的特异性和敏感性；(2)在规模上生成有效的用户贡献的诊断信息；(3)用于计算流感风险的实时背景数据的可能性；(4)个人对这些信息的使用和接受。该团队汇集了构建和研究用于疾病监测的新型众包数据源的经验，以及软件、图形设计、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。拟议的系统通过加速和改变人们处理医疗保健的方式，具有巨大的社会影响潜力。增强个人生成健康信息并对其采取行动的能力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。为了最大限度地发挥该制度的影响力和可持续性，该制度还发挥了教育工具的作用。以易于解释的方式向公众清楚、公开地传达匿名和受隐私保护的数据，将有助于个人、政策制定者和其他研究人员利用与背景相关的疾病风险信息。来自不同背景的本科生和研究生将有机会参与研究。美国公共卫生协会及其与少数群体健康有关的团体，如少数民族保健专业学校协会和拉丁裔保健项目的协作者，将协助全国范围内不同的参与者群体的参与。

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.