Validation of Smart Masks for Surveillance of COVID-19

用于监测 COVID-19 的智能口罩的验证

基本信息

批准号：
10273452
负责人：
Jesse Vincent Jokerst
金额：
$ 34.86万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-12-21 至 2022-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10273452
关键词：
3-Dimensional Adhesives Biological Assay Biological Markers Biometry Bulla COVID-19 COVID-19 diagnosis COVID-19 early detection COVID-19 surveillance COVID-19 susceptibility Caregivers Clinic Color Communities Complex Custom Data Coordinating Center Dialysis procedure Exposure to Future Goals Gold Health care facility Home Hospitals Human Human Resources Human Subject Research Individual Infrastructure Institution Laboratories Life Literature Masks Measures Methods Monitor N95 mask Outcome Papain Patient Care Patients Peptide Hydrolases Peptides Persons Population Predictive Value Pregnancy Tests Preparation Prisons RADx Radical Reagent Recombinants Reporter Reporting Research Research Design Respirators Risk SARS coronavirus SARS-CoV-2 exposure SARS-CoV-2 infection SARS-CoV-2 negative SARS-CoV-2 positive Saliva Sampling Sensitivity and Specificity Serology Severe Acute Respiratory Syndrome Skilled Nursing Facilities Specificity System Testing Time Training Vaccines Validation Viral Viral Load result Viral Physiology Virus Vulnerable Populations Work aerosolized base biobank coronavirus disease data sharing design detection limit experience high risk human subject infection risk innovation nanoGold novel strategies pandemic disease particle patient home care point of care protein aminoacid sequence saliva sample surgical mask test strip tool

项目摘要

Project Summary. Vulnerable populations do not just need testing—they need surveillance. The ideal surveillance tool would operate in the background with minimal involvement of the population to be tested; it would be simple, affordable, reliable, and accurate. Unfortunately, no such surveillance system yet exists. Here, we propose a “smart mask” that changes colors when the wearer has been exposed to biomarkers (proteases) of COVID-19. These proteases are known to be in saliva, and the smart mask will concentrate the proteases from aerosolized saliva when the subject breathes and speaks through the smart mask. This is a simple yet novel approach to surveillance because most people are already wearing masks—especially in high- risk settings. Our first goal is to optimize the reagents that will monitor the proteases. We will customize the peptide sequences such that the reagents change color only when two key SARS proteases are present. After characterizing the colorimetric reagents, Aim 2 will integrate these reagents into an adhesive strip (i.e., a sticker) that can be affixed to any existing cloth or surgical mask. Aim 3 is validation with human subjects. First, we will use biobanked saliva samples that are confirmed to be either COVID-19-positive or COVID-19-negative. Next, we will evaluate how long people infected with SARS-CoV-2 must breathe through the smart mask before it changes colors. Finally, we will use the smart mask for surveillance of a population that is concurrently being tested regularly via PCR. We will calculate the sensitivity and specificity of the smart masks through comparison to PCR. We will measure true positives, true negatives, false positives, and false negatives and estimate needing 800 subjects, which is very feasible at our institution. Our team is well-suited to conduct this research because of Dr. Jokerst’s training colorimetric sensing; Drs. Penny, Knight, and Laurent have decades of human subjects research experience, and Dr. Tu offers biostatistical experience to confirm study design. This work could have a significant impact on the pandemic because our proposed design combines the simplicity of the home pregnancy test with the specificity of expensive viral-based assays. It is practical because it uses the masks that are already common in daily life and reports the presence of SARS viruses via a simple color change. While a vaccine will hopefully be deployed during the course of this work, the proteases evaluated here have been implicated in a variety of SARS viruses. Thus, this work will be useful should future pandemics emerge.

项目摘要。脆弱的人群不仅需要测试，还需要监视。理想的监视工具将在背景下运行，以最少的测试人群参与；这很简单，负担得起，可靠和准确。不幸的是，尚无这样的监视系统。在这里，我们建议当穿着者暴露于生物标志物（蛋白酶）时，“智能面具”会改变颜色新冠肺炎。这些蛋白酶在唾液中已知，智能口罩将集中蛋白酶当受试者通过智能面具呼吸并说话时，从气雾化的唾液中。这很简单然而，新颖的监视方法是因为大多数人已经戴着口罩，尤其是在高处风险设置。我们的第一个目标是优化将监测蛋白酶的试剂。我们将自定义辣椒序列使试剂仅在两个关键的SARS蛋白酶时才改变颜色展示。表征比色试剂后，AIM 2将这些试剂整合到粘合剂中条带（即贴纸）可以固定在任何现有的布或外科面膜上。 AIM 3是对人的验证主题。首先，我们将使用确认为covid-19阳性或 covid-19-阴性。接下来，我们将评估被SARS-COV-2感染的人必须呼吸多长时间在更改颜色之前通过智能面具。最后，我们将使用智能面具进行监视通过PCR定期测试的人口。我们将计算灵敏度和通过与PCR进行比较，智能口罩的特异性。我们将衡量真正的积极因素，真正的负面因素，误报，假否定和估计需要800个主题，这对我们来说是非常可行的机构。由于Jokerst博士的培训比色法，我们的团队非常适合进行这项研究感应；博士。 Penny，Knight和Laurent拥有数十年的人类学科研究经验，博士 TU提供生物统计学经验来确认研究设计。这项工作可能会对大流行是因为我们提出的设计组合是家庭怀孕测试的简单性昂贵的基于病毒的测定的特异性。它是实用的，因为它使用了已经已经存在的口罩在日常生活中常见，并通过简单的颜色改变报告了SARS病毒的存在。而疫苗希望在这项工作过程中部署，这里评估的蛋白酶已经在各种SARS病毒中实施。这是，如果未来的大流派出现，这项工作将很有用。