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

项目摘要。新冠肺炎疫情加剧了人们对增强准确预测能力的需求 预测由于新的和地方性的病毒病原体而导致的未来疫情。如果没有系统的监督， 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通常是 尽管采取了大量的封锁措施，但为时已晚，无法阻止大规模疫情的发生。的主要原因是 这种延迟是因为人们在被诊断为阳性之前(以及如果)是有传染性的。我们再也不能 依赖基于人口的检测，这(A)被推迟；(B)非随机和昂贵，加剧了 已知和了解的健康差距；以及(C)依赖高度准确、分布广泛的测试可用性 并加以利用。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种 废水采样方法，用于监测新冠肺炎和其他病毒病原体。我们的方法利用 SARS-CoV-2(导致新冠肺炎的病毒)独特的基因组特征检测到这种病原体 提供关于社区和城市中新冠肺炎感染的廉价和公正的实时数据 组织。我们集团已经开始与市政当局、学术实体和大型制造企业签订合同 公司为新冠肺炎的存在提供实时、公正的数据。然而，目前，废水 新冠肺炎数据主要被用来确定在中国是否存在SARS-CoV-2 样本。我们看到了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 SARS-CoV-2和其他新的地方性病毒未来爆发的时间、地点和严重程度 病原体。卓越统计研究(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、废水监控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- Of-Concept SBIR项目有两个目标。首先，我们将演示可以预测位置和 未来爆发新冠肺炎的组织，具有很长的交付期。第二，我们将演示如何 可以对模型预测进行优化，使其对市政当局和组织有用。可行性将是 通过具有出色预测能力的模型(R2&>0.90)(目标1)和通过演示 商业化途径的盈利能力(目标2)。第一阶段的可行性将允许我们扩展建模 超越SARS-CoV-2到其他病毒病原体(例如流感、诺沃克病毒、艾滋病毒)的能力：扩大 对这些额外病原体的废水测试能力，以及进一步推出和改进 第二阶段的机器学习/建模工作。最终，我们将拥有一套全面服务的商业 预测模型(第三阶段)，可与社区的废水监测计划相结合 和组织层面，导致病毒疾病暴发大幅减少。

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.