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Record W3135777963 · doi:10.2196/24811

Self-Sampling for SARS-CoV-2 Diagnostic Testing by Using Nasal and Saliva Specimens: Protocol for Usability and Clinical Evaluation

2021· article· en· W3135777963 on OpenAlexvenueno aff
Mohammed Majam, Vanessa Msolomba, Lesley Scott, Wendy Stevens, Fadzai Marange, Trish Kahamba, François Venter, Donaldson F. Conserve

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsMedicineUsabilityPandemicPopulationClinical trialSalivaData collectionProtocol (science)Sampling (signal processing)Coronavirus disease 2019 (COVID-19)Environmental healthDiseasePathologyStatisticsAlternative medicineInternal medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: SARS-CoV-2 is a novel coronavirus discovered in December 2019 and is currently the cause of the global COVID-19 pandemic. A critical aspect of fighting this pandemic is to obtain accurate and timely test results so that patients who have tested positive for COVID-19 can be identified and isolated to reduce the spread of the virus. Research has shown that saliva is a promising candidate for SARS-CoV-2 diagnostics because its collection is minimally invasive and can be reliably self-administered. However, little research has been conducted on saliva testing and SARS-CoV-2 self-sampling (SARS-CoV-2SS) in Sub-Saharan Africa. OBJECTIVE: The primary objective of this study is to comparatively evaluate the clinical sensitivity and specificity of nasal and oral samples self-collected by individuals for SARS-CoV-2 testing against a reference method involving sample collection and testing by a health care professional. The secondary objectives of this study are to evaluate the usability of nasal self-sampling and saliva self-sampling as a sample collection method for SARS-CoV-2 diagnostic testing by using failure mode and error assessment. METHODS: Participants will be recruited from the general population by using various methods, Participants will be screened progressively as they present at the clinical trial sites as well as in primary health care catchment areas in the inner city of Johannesburg, South Africa. In the event that recruitment numbers are low, we will use a mobile van to recruit participants from outlying areas of Johannesburg. We aim to enroll 250 participants into this study in approximately 6 weeks. Two sample types-a self-administered nasal swab and a self-administered saliva sample-will be collected from each participant, and a health care professional will collect a third sample by using a nasopharyngeal swab (ie, the standard reference method). RESULTS: This protocol has been approved by the University of the Witwatersrand Human Research Ethics Committee on July 31, 2020 (Protocol number EzCov003). As of May 13, 2021, 120 participants have been enrolled into the study. CONCLUSIONS: SARS-CoV-2SS may offer many benefits to individuals, by allowing for initial self-identification of symptoms and collection of samples without involving third parties and potential risk of infection provided the sample can be safely processed via a collection system. The results of this study will provide preliminary data on the acceptability, feasibility, and usability of SARS-CoV-2SS among the general population for its future implementation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24811.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.051
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.233
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.707
GPT teacher head0.662
Teacher spread0.044 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2021
Admission routes1
Has abstractyes

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