Evidence map›Paper›PMID 32330124›Full record

ArticlePLoS biology2020

Leveraging open hardware to alleviate the burden of COVID-19 on global health systems.

Andre Maia Chagas, Jennifer C Molloy, Lucia L Prieto-Godino, Tom Baden

Open access · goldAbstract read
In one paragraph

Article in PLoS biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
7.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 97 citations in OpenAlex.

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  15. High-throughput and automated screening for COVID-19.Frontiers in medical technology · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 3 countries.

Andre Maia ChagasSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0003-2609-3017
Jennifer C MolloyGathering for Open Science Hardware.ORCID 0000-0003-3477-8462
Lucia L Prieto-GodinoTReND in Africa, Brighton, United Kingdom.ORCID 0000-0002-2980-362X
Tom BadenSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0003-2808-4210
University of Sussex · GBThe Francis Crick Institute · GBUniversity of Cambridge · GB

Funding

European Research CouncilMedical Research Council MC_PC_15071
6 · The paper itself

Abstract

With the current rapid spread of COVID-19, global health systems are increasingly overburdened by the sheer number of people that need diagnosis, isolation and treatment. Shortcomings are evident across the board, from staffing, facilities for rapid and reliable testing to availability of hospital beds and key medical-grade equipment. The scale and breadth of the problem calls for an equally substantive response not only from frontline workers such as medical staff and scientists, but from skilled members of the public who have the time, facilities and knowledge to meaningfully contribute to a consolidated global response. Here, we summarise community-driven approaches based on Free and Open Source scientific and medical Hardware (FOSH) as well as personal protective equipment (PPE) currently being developed and deployed to support the global response for COVID-19 prevention, patient treatment and diagnostics.

Indexed as

BetacoronavirusCoronavirus InfectionsEquipment and Supplies, HospitalPandemicsPneumonia, ViralCommunity ParticipationCOVID-19Global HealthHumansSARS-CoV-2

Identifiers

PMID32330124
PMCPMC7182255
OpenAlexW3013313861

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.