The One Hour COVID Test: A Rapid Colorimetric Reverse-Transcription LAMP–Based COVID-19 Test Requiring Minimal Equipment

Jorgensen, E. Verena; Monaco, Christopher M.

doi:10.7171/jbt.21-3203-008

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…The speed and cost-efficiency of the community review process has allowed for a reactive response to the high-pressure environment created by the pandemic. This agility has meant that within the short time frame given, projects have been able to produce literature, methods and hardware and put them to use (21)(22)(23)(24)(25)(26). Overall, the community review system allows for a rapid, agile, iterative, distributed and scalable review process for volunteer action and micro-grant attribution.…”

Section: Discussionmentioning

confidence: 99%

Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Graham

Landrain²,

Vjestica

et al. 2022

Preprint

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Resource allocation is essential to the selection and implementation of innovative projects in science and technology. With large stakes involved in concentrating large fundings over a few promising projects, current winner-take-all models for grant applications are time-intensive endeavours that mobilise significant researcher time in writing extensive project proposals, and rely on the availability of a few time-saturated volunteer experts. Such processes usually carry over several months, resulting in high effective costs compared to expected benefits. Faced with the need for a rapid response to the Covid19 pandemic in 2020, we devised an agile community review system to allocate micro-grants for the fast prototyping of innovative solutions. Here we describe and evaluate the implementation of this community review across 147 projects from the OpenCOVID19 and Helpful Engineering open research communities. The community review process uses granular review forms and requires the participation of grant applicants in the review process. Within a year, we organised 7 rounds of review, resulting in 614 reviews from 201 reviewers, and the attribution of 48 micro-grants of up to 4,000 euros. We show that this system is fast, with a median process duration of 10 days, scalable, with a median of 4 reviewers per project independent of the total number of projects, and fair, with project rankings highly preserved after the synthetic removal of reviewers. We investigate the potential bias introduced by involving applicants in the process, and find that review scores from both applicants and non-applicants have a similar correlation of r=0.28 with other reviews within a project, matching previous observations using traditional approaches. Finally, we find that the ability of projects to apply to several rounds allows to both foster the further implementation of successful early prototypes, as well as provide a pathway to constructively improve an initially failing proposal in an agile manner. Overall, this study quantitatively highlights the benefits of a frugal, community review system acting as a due diligence for rapid and agile resource allocation in open research programs, with particular implications for decentralised communities.

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Section: Discussionmentioning

confidence: 99%

Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Graham

Landrain²,

Vjestica

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…This agility has meant that within the short time frame given, projects have been able to produce literature, methods and hardware and put them to use. [23][24][25][26][27][28] Overall, the community review system allows for a rapid, agile, iterative, distributed and scalable review process for volunteer action and micro-grant attribution. It is particularly suited for open research and innovation communities collaborating in a decentralized manner and looking for ways to distribute common resources fairly and swiftly.…”

Section: Discussionmentioning

confidence: 99%

Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Graham

Landrain²,

Vjestica³

et al. 2022

F1000Res

View full text Add to dashboard Cite

Resource allocation is essential to selection and implementation of innovative projects in science and technology. Current “winner-take-all” models for grant applications require significant researcher time in writing extensive project proposals, and rely on the availability of a few time-saturated volunteer experts. Such processes usually carry over several months, resulting in high effective costs compared to expected benefits. We devised an agile “community review” system to allocate micro-grants for the fast prototyping of innovative solutions. Here we describe and evaluate the implementation of this community review across 147 projects from the “Just One Giant Lab’s OpenCOVID19 initiative” and “Helpful Engineering” open research communities. The community review process uses granular review forms and requires the participation of grant applicants in the review process. Within a year, we organised 7 rounds of review, resulting in 614 reviews from 201 reviewers, and the attribution of 48 micro-grants of up to 4,000 euros. The system is fast, with a median process duration of 10 days, scalable, with a median of 4 reviewers per project independent of the total number of projects, and fair, with project rankings highly preserved after the synthetic removal of reviewers. Regarding potential bias introduced by involving applicants in the process, we find that review scores from both applicants and non-applicants have a similar correlation of r=0.28 with other reviews within a project, matching traditional approaches. Finally, we find that the ability of projects to apply to several rounds allows to foster the further implementation of successful early prototypes, as well as provide a pathway to constructively improve an initially failing proposal in an agile manner. Overall, this study quantitatively highlights the benefits of a frugal, community review system acting as a due diligence for rapid and agile resource allocation in open research and innovation programs, with implications for decentralised communities.

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“…Ultimately, we settled on LAMP as the method of choice and developed the One Hour COVID Test (Monaco, Jorgensen, and Ware 2021). To aid in the rapid development of our test, we chose to evaluate several different published primer sets rather than design our own.…”

Section: Developing An Open Diagnostic Testmentioning

confidence: 99%

Structural Challenges in Deployment of an Open-Source Diagnostic by Independent Researchers During a Public Health Emergency

Monaco¹,

Monaco²

2022

Citizen Science: Theory and Practice

Self Cite

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Open-source diagnostic products have the potential to address some of the major challenges of diagnostic access revealed during the COVID-19 pandemic. However, as it stands, the current approval model in the US is poorly suited for such tests. In March 2020, early in the COVID-19 pandemic, a small group of independent scientists with members located in Illinois, New York, and Georgia collaborated on developing an open-source, patent-free COVID-19 diagnostic test. Within a few short months, we had developed a reliable test and published the protocol online with the hope that this simple, yet sensitive test would be adopted for widespread testing in laboratories, schools, and workplaces. However, we encountered several unexpected barriers to deployment of the test. This essay describes our experience and proposes a novel solution to reduce the barriers that limit meaningful contributions by independent researchers to addressing healthcare challenges in the United States.

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The One Hour COVID Test: A Rapid Colorimetric Reverse-Transcription LAMP–Based COVID-19 Test Requiring Minimal Equipment

Cited by 3 publications

References 8 publications

Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Structural Challenges in Deployment of an Open-Source Diagnostic by Independent Researchers During a Public Health Emergency

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