The Cornell COVID-19 Testing Laboratory: A Model to High-Capacity Testing Hubs for Infectious Disease Emergency Response and Preparedness

Author:

Laverack Melissa1ORCID,Tallmadge Rebecca L.1ORCID,Venugopalan Roopa1,Sheehan Daniel2,Ross Scott2,Rustamov Rahim1,Frederici Casey3,Potter Kim S.1,Elvinger François1,Warnick Lorin D.1,Koretzky Gary A.45,Lawlis Robert3,Plocharczyk Elizabeth3,Diel Diego G.1ORCID

Affiliation:

1. Department of Population Medicine and Diagnostic Sciences, Animal Health Diagnostic Center (AHDC), College of Veterinary Medicine, Cornell COVID-19 Testing Laboratory (CCTL), Cornell University, Ithaca, NY 14853, USA

2. Information Technology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA

3. Cayuga Medical Center, Cayuga Health System, Ithaca, NY 14850, USA

4. Department of Microbiology and Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA

5. Department of Medicine, Weill Cornell Medicine, Cornell University, New York City, NY 10065, USA

Abstract

The unprecedented COVID-19 pandemic posed major challenges to local, regional, and global economies and health systems, and fast clinical diagnostic workflows were urgently needed to contain the spread of SARS-CoV-2. Here, we describe the platform and workflow established at the Cornell COVID-19 Testing Laboratory (CCTL) for the high-throughput testing of clinical samples from the university and the surrounding community. This workflow enabled efficient and rapid detection and the successful control of SARS-CoV-2 infection on campus and its surrounding communities. Our cost-effective and fully automated workflow enabled the testing of over 8000 pooled samples per day and provided results for over 2 million samples. The automation of time- and effort-intensive sample processing steps such as accessioning and pooling increased laboratory efficiency. Customized software applications were developed to track and store samples, deconvolute positive pools, track and report results, and for workflow integration from sample receipt to result reporting. Additionally, quality control dashboards and turnaround-time tracking applications were built to monitor assay and laboratory performance. As infectious disease outbreaks pose a constant threat to both human and animal health, the highly effective workflow implemented at CCTL could be modeled to establish regional high-capacity testing hubs for infectious disease preparedness and emergency response.

Funder

Cornell University

College of Veterinary Medicine

Animal Health Diagnostic Center

Publisher

MDPI AG

Subject

Virology,Infectious Diseases

Reference30 articles.

1. A Novel Coronavirus from Patients with Pneumonia in China, 2019;Zhu;N. Engl. J. Med.,2020

2. The Species Severe Acute Respiratory Syndrome-Related Coronavirus: Classifying 2019-NCoV and Naming It SARS-CoV-2;Gorbalenya;Nat. Microbiol.,2020

3. (2021, July 29). World Health Organization Director-General WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19–11 March 2020. Available online: https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020.

4. Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review;Oran;Ann. Intern. Med.,2020

5. Temporal Dynamics in Viral Shedding and Transmissibility of COVID-19;He;Nat. Med.,2020

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3