Wastewater data integration and modelling to accurately predict community and organizational outbreaks due to viral pathogens

项目摘要。2019冠状病毒病大流行加剧了对提高准确 预测未来由于新的和地方性病毒病原体而爆发的疫情。如果没有系统的监控， 在疫情发生之前阻止疫情的能力是具有挑战性的：来自阳性人体测试结果的数据往往是 尽管采取了大量的封锁措施，但为时已晚，无法防止重大疫情的发生。的关键原因 这种延迟是指人们在被诊断为阳性之前（以及如果被诊断为阳性）的几天内具有传染性。我们不能再 依赖于基于人口的测试，（a）被延迟;（B）是非随机和昂贵的，加剧了- 已知和理解的健康差异;（c）依赖于高度准确、广泛分布的测试可用性 和使用.在过去的14个月里，我们的附属科学家团队开发并实施了一个 废水采样方法，以监测COVID-19和其他病毒病原体。我们的方法利用 SARS-CoV-2（导致COVID-19的病毒）的独特基因组特征，以检测这种病原体， 废水，提供社区COVID-19感染的廉价和无偏见的实时数据， 组织的我们的团队已经开始与市政当局、学术实体和大型制造业签订合同 公司提供关于COVID-19存在的实时，无偏见的数据。目前，废水 COVID-19数据主要仅用于确定 样品我们认为这是一个极具创新性和影响力的机会，可以进一步利用这些数据来预测未来 SARS-CoV-2和其他新型和地方性病毒未来爆发的时间、地点和严重程度 病原体上级统计研究（SSR）研发团队是国际公认的 废水和公共卫生专家，在统计、数据分析、建模、 计算，废水监测，以及将废水和健康信息转化为 为组织和社区采取可行的步骤。为了抓住这个机会，我们提出了第一阶段的证明- 具有两个目标的概念SBIR项目。首先，我们将证明预测位置是可能的， 未来爆发COVID-19的组织需要大量的准备时间。其次，我们将展示如何 模型预测可以被优化以用于市政当局和组织。可行性将是 通过具有良好预测能力的模型（R2>0.90）（目标1）和通过证明 商业化途径的盈利能力（目标2）。第一阶段的可行性将使我们能够扩展建模 超越SARS-CoV-2的能力到其他病毒病原体（例如，流感、诺如病毒、艾滋病毒）：扩大 这些额外的病原体的废水检测能力，并进一步推出和改善 第二阶段的机器学习/建模工作。最终，我们将拥有一套全面的商业服务， 预测模型（第三阶段），可与社区废水监测计划相结合 和组织水平，导致病毒性疾病爆发的急剧减少。

Project Summary. The COVID-19 pandemic has magnified the need for enhanced ability to accurately anticipate future outbreaks due to novel and endemic viral pathogens. Without systematic surveillance, the ability to head off outbreaks before they occur is challenging: the data from positive human test results is often too late to prevent a major outbreak from occurring, despite substantial lockdown efforts. The key reason for this delay is that people are infectious for days before (and if) they are diagnosed positive. We can no longer rely on population-based testing, which (a) is delayed; (b) is non-random and expensive, exacerbating well- known and understood health disparities; and (c) relies on highly accurate, widely distributed test availability and use. Over the last fourteen months, our team of affiliated scientists has developed and implemented a wastewater-sampling approach to monitor for COVID-19 and other viral pathogens. Our approach utilizes unique genomic signatures of SARS-CoV-2 (the virus that causes COVID-19) to detect this pathogen in wastewater, providing inexpensive and unbiased real-time data on COVID-19 infections in communities and organizations. Our group has begun to contract with municipalities, academic entities and large manufacturing companies to provide real-time, unbiased data on the presence of COVID-19. Currently, however, wastewater COVID-19 data has primarily been used solely to determine the presence/absence of SARS-CoV-2 in samples. We see a highly innovative and impactful opportunity to leverage these data further to anticipate the timing, location, and severity of future outbreaks from SARS-CoV-2 and other novel and endemic viral pathogens. The Superior Statistical Research (SSR) R&D team is an internationally recognized group of wastewater and public health experts with cross-cutting expertise in statistics, data analysis, modelling, computing, wastewater monitoring, and the ability to translate wastewater and health information into actionable steps for organizations and communities. To address this opportunity, we propose a Phase I proof- of-concept SBIR project with two Aims. First, we will demonstrate that it is possible to anticipate locations and organizations with future outbreaks of COVID-19 with significant lead time. Second, we will demonstrate how model predictions can be optimized to be useful for municipalities and organizations. Feasibility will be determined by having models with excellent predictive ability (R2>0.90) (Aim 1) and by demonstrating the profitability of the commercialization pathway (Aim 2). Phase I feasibility will allow us to extend modelling capabilities beyond SARS-CoV-2 to other viral pathogens (e.g., influenza, norovirus, HIV): expanding wastewater testing capabilities for these additional pathogens, and further roll-out and improvement of the machine-learning/modelling effort in Phase II. Ultimately, we will have a full-service commercial set of predictive models (Phase III) that can be combined with wastewater-monitoring programs at the community and organizational level, leading to dramatic reductions in viral disease outbreaks.