Wastewater Assessment for Coronavirus in Kentucky: Implementing Enhanced Surveillance Technology
肯塔基州冠状病毒废水评估:实施强化监测技术
基本信息
- 批准号:10264317
- 负责人:
- 金额:$ 183.43万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-01-01 至 2023-05-31
- 项目状态:已结题
- 来源:
- 关键词:2019-nCoVAppalachian RegionBiological AssayBiological MarkersCOVID-19 assayCOVID-19 detectionCOVID-19 outbreakCOVID-19 surveillanceCOVID-19 testingCharacteristicsCitiesClinicalCold ChainsCommunitiesCoronavirusDetectionDiseaseDisease SurveillanceEvaluationExclusionFecesGoalsHealthcareHeatingHourIndividualInfectionInfection preventionInfrastructureKentuckyLaboratoriesMeasuresMediatingMethodsMolecular Biology TechniquesMonitorNursing HomesPerceptionPerformancePersonsPlantsPopulationPreparationPrevention MeasuresPrisonsRADx RadicalRNARNA DegradationReach, Effectiveness, Adoption, Implementation, and MaintenanceResourcesReverse Transcriptase Polymerase Chain ReactionRibonucleasesRiskRuralRural AppalachiaRural CommunityRural PopulationSARS-CoV-2 infectionSamplingSchoolsSensitivity and SpecificitySeriesSideSignal TransductionSurveillance MethodsSyncopeSystemTechniquesTechnologyTechnology AssessmentTest ResultTestingTimeTrainingUnited StatesUnited States National Institutes of HealthUniversitiesViralVulnerable Populationsauthoritybasecitizen sciencecommunity based participatory researchexperiencefield studyhigh riskimprovedinnovationisothermal amplificationnew technologynext generationpoint of carepreventrecruitresearch clinical testingresponserural arearural settingsample collectionscience teachertrendusabilitywastewater sampleswastewater samplingwastewater screeningwastewater surveillancewastewater testing
项目摘要
Wastewater Assessment for Coronavirus in Kentucky – Implementing Enhanced Surveillance
Technology
Surveillance for SARS-CoV-2 is hindered by the availability of testing, particularly in remote and rural
areas. Screening of wastewater for SARS-CoV-2 viral biomarkers offers a viable alternative to individual
testing and it can identify communities and facilities that are at risk of becoming hotspots.Wastewater
surveillance overcomes several limitations of clinical surveillance, such as the need for robust healthcare
and laboratory infrastructure and the lack of representative and comprehensive testing within
communities. Conventional wastewater surveillance takes samples from sewer systems or wastewater
treatment facilities and uses a series of extraction steps prior to advanced PCR technology to quantitate
the viral biomarker (RNA). This approach is time and resource-intensive, which limits its wide-scale
application. Developing next generation technology to simplify wastewater RNA extraction and
quantitation will make it feasible to use more broadly at facilities and in rural communities. The limited
clinical testing for COVID-19 in rural Southeastern Kentucky hampers disease surveillance and prevents
informed public action to mitigate and contain the spread of disease. Wastewater testing for SARS-CoV-
2 in these communities using field-friendly technology will provide important information to local
authorities and citizens about the spread and trend of SARS-CoV-2 infection in their communities. Our
project will accomplish two aims: 1) Develop next generation wastewater assessment technology and 2)
Implement and evaluate the next generation wastewater assay. For Aim 1 we adapt technology invented
by our team termed exclusion-based sample preparation (ESP) to simplify and improve RNA extraction
from wastewater. We will pair ESP with loop-mediated isothermal amplification (LAMP) technology for
RNA detection to create a sensitive, robust, and field-friendly platform for testing wastewater for SARS-
CoV-2 RNA. We will compare the next generation assay with established techniques on metrics of
sensitivity, specificity, and usability (e.g., assay time, number of assay steps). For Aim 2 we will first
validate the next generation assay in the field at congregate living facilities in a side-by-side comparison
with conventional wastewater surveillance. Next, building on existing relationships in Appalachian
Kentucky, we will recruit and train a purposive group of wastewater treatment plant operators, watershed
watch citizen scientists, and school science teachers to test wastewater in their communities and schools
using the field-friendly next generation wastewater assay. Field results will be validated in the lab. A
robust mixed methods evaluation using the RE-AIM framework will assess community perceptions of
feasibility, acceptability, and utility of wastewater surveillance for SARS-CoV-2 and identify community
measures taken in response to test results.
肯塔基州冠状病毒废水评估——实施强化监测
技术
对 SARS-CoV-2 的监测因检测的可用性而受到阻碍,特别是在偏远和农村地区
对废水进行 SARS-CoV-2 病毒生物标志物筛查为个体提供了可行的替代方案。
测试,它可以识别有可能成为热点的社区和设施。废水
监测克服了临床监测的一些局限性,例如需要强大的医疗保健
和实验室基础设施以及内部缺乏代表性和全面的测试
传统的废水监测从下水道系统或废水中采集样本。
处理设施,并在先进的 PCR 技术之前使用一系列提取步骤来定量
这种方法需要大量时间和资源,限制了其大规模应用。
开发下一代技术以简化废水 RNA 提取和应用。
定量将使在有限的设施和农村社区更广泛地使用变得可行。
肯塔基州东南部农村地区的 COVID-19 临床检测阻碍了疾病监测和预防
告知公众采取行动以减轻和遏制疾病的传播,对废水进行 SARS-CoV 检测。
2 在这些社区中使用现场友好型技术将为当地提供重要信息
当局和公民了解 SARS-CoV-2 感染在其社区中的传播和趋势。
项目将实现两个目标:1) 开发下一代废水评估技术;2)
为了实现目标 1,我们采用了发明的技术,并对其进行评估。
由我们的团队称为基于排除的样品制备 (ESP),以简化和改进 RNA 提取
我们将 ESP 与环介导等温扩增 (LAMP) 技术结合起来,
RNA 检测创建一个灵敏、强大且现场友好的平台,用于检测废水中的 SARS-
我们将把下一代检测方法与已建立的技术进行比较。
对于目标 2,我们首先考虑灵敏度、特异性和可用性(例如检测时间、检测步骤数)。
通过并排比较在聚集生活设施现场验证下一代检测方法
接下来,以阿巴拉契亚地区现有的关系为基础。
肯塔基州,我们将有目的地招募和培训废水处理厂操作人员、流域
观看公民科学家和学校科学教师测试社区和学校的废水
使用现场友好的下一代废水测定结果将在实验室进行验证。
使用 RE-AIM 框架的混合稳健评估方法将评估社区对
SARS-CoV-2 废水监测的可行性、可接受性和效用并确定社区
根据测试结果采取的措施。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Scott M Berry其他文献
Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction
通过快速 RNA 提取稳定废水中的 SARS-CoV-2 RNA
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
S. Torabi;Atena Amirsoleimani;Mohammad Dehghan Banadaki;William Strike;Alexus Rockward;Ann Noble;Matthew Liversedge;James W Keck;Scott M Berry - 通讯作者:
Scott M Berry
Dose‐finding results in an adaptive, seamless, randomized trial of once‐weekly dulaglutide combined with metformin in type 2 diabetes patients (AWARD‐5)
每周一次度拉鲁肽联合二甲双胍治疗 2 型糖尿病患者的适应性、无缝、随机试验的剂量探索结果 (AWARD-5)
- DOI:
10.1111/dom.12305 - 发表时间:
2014-08-01 - 期刊:
- 影响因子:7.7
- 作者:
Z. Skrivanek;Brenda L. Gaydos;J. Chien;M. Geiger;M. Heathman;Scott M Berry;JamesH. Anderson;T. Forst;Z. Milicevic;Don Berry - 通讯作者:
Don Berry
Wastewater Surveillance for Identifying SARS-CoV-2 Infections in Long-Term Care Facilities, Kentucky, USA, 2021–2022
2021 年至 2022 年美国肯塔基州长期护理机构中用于识别 SARS-CoV-2 感染的废水监测
- DOI:
10.3201/eid3003.230888 - 发表时间:
2024-03-01 - 期刊:
- 影响因子:11.8
- 作者:
James W Keck;R. Adatorwovor;Matthew Liversedge;Blazan Mijotavich;Cullen Olsson;William Strike;Atena Amirsoleimani;Ann Noble;S. Torabi;Alexus Rockward;Mohammad Dehghan Banadaki;Ted Smith;Parker Lacy;Scott M Berry - 通讯作者:
Scott M Berry
Scott M Berry的其他文献
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{{ truncateString('Scott M Berry', 18)}}的其他基金
Wastewater Assessment for Coronavirus in Kentucky: Implementing Enhanced Surveillance Technology
肯塔基州冠状病毒废水评估:实施强化监测技术
- 批准号:
10320997 - 财政年份:2021
- 资助金额:
$ 183.43万 - 项目类别:
The Dual Reporter Sensor Cell (DRSC) Assay: An Enhanced Tool for Measuring the Viral Reservoir
双报告传感器细胞 (DRSC) 检测:测量病毒库的增强工具
- 批准号:
10079343 - 财政年份:2020
- 资助金额:
$ 183.43万 - 项目类别:
Enhancing Pediatric Diagnosis of Tuberculosis with FLOW Technology
利用 FLOW 技术增强儿科结核病诊断
- 批准号:
9907972 - 财政年份:2020
- 资助金额:
$ 183.43万 - 项目类别:
The Dual Reporter Sensor Cell (DRSC) Assay: An Enhanced Tool for Measuring the Viral Reservoir
双报告传感器细胞 (DRSC) 检测:测量病毒库的增强工具
- 批准号:
10254314 - 财政年份:2020
- 资助金额:
$ 183.43万 - 项目类别:
Getting More from Less: Multi-omic Capture and Analysis from Patient Samples
事半功倍:从患者样本中进行多组学捕获和分析
- 批准号:
9545010 - 财政年份:2016
- 资助金额:
$ 183.43万 - 项目类别:
Getting More from Less: Multi-omic Capture and Analysis from Patient Samples
事半功倍:从患者样本中进行多组学捕获和分析
- 批准号:
9140592 - 财政年份:2016
- 资助金额:
$ 183.43万 - 项目类别:
VERSA: An Integrated, Multi-Endpoint Platform for Circulating Tumor Cell Analysis
VERSA:用于循环肿瘤细胞分析的集成多端点平台
- 批准号:
8720248 - 财政年份:2014
- 资助金额:
$ 183.43万 - 项目类别:
VERSA: An Integrated, Multi-Endpoint Platform for Circulating Tumor Cell Analysis
VERSA:用于循环肿瘤细胞分析的集成多端点平台
- 批准号:
9228340 - 财政年份:2014
- 资助金额:
$ 183.43万 - 项目类别:
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