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Record W3195865288 · doi:10.15585/mmwr.mm7033a3

Use of Rapid Antigen Testing for SARS-CoV-2 in Remote Communities — Yukon-Kuskokwim Delta Region, Alaska, September 15, 2020–March 1, 2021

2021· article· en· W3195865288 on OpenAlexaboutno aff
Ellen Hodges, Brian Lefferts, Elizabeth J Bates, Christine Desnoyers, Dana Bruden, Michael G. Bruce, Joseph McLaughlin

Bibliographic record

VenueMMWR Morbidity and Mortality Weekly Report · 2021
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DeltaCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakVirologyImmunologyPathologyOutbreak

Abstract

fetched live from OpenAlex

Controlling the spread of SARS-CoV-2, the virus that causes COVID-19, in Alaska is challenging. Alaska includes many remote and isolated villages with small populations (ranging from 15 to >1,000 persons) that are accessible only by air from larger communities. Until rapid point-of-care testing became widely available, a primary challenge in the diagnosis of COVID-19 in rural Alaska was slow turnaround times for SARS-CoV-2 test results, attributable to the need to transport specimens to testing facilities. To provide more timely test results and isolation of cases, the Yukon Kuskokwim Health Corporation (YKHC) introduced Abbott BinaxNOW COVID-19 Ag rapid antigen test (BinaxNOW) on November 9, 2020, in the rural Yukon-Kuskokwim Delta region in southwestern Alaska. To evaluate the impact of implementing antigen testing, YKHC reviewed the results of 54,981 antigen and molecular tests for SARS-CoV-2 performed in the Yukon-Kuskokwim Delta during September 15, 2020-March 1, 2021. Introduction of rapid, point-of-care testing was followed by a more than threefold reduction in daily SARS-CoV-2 case rates during approximately 1 month before the introduction of COVID-19 vaccination. The median turnaround time for SARS-CoV-2 test results decreased by >30%, from 6.4 days during September 15-November 8, 2020, to 4.4 days during November 9, 2020-March 1, 2021 (p<0.001). Daily incidence decreased 65% after the introduction of BinaxNOW, from 342 cases per 100,000 population during the week of November 9 to 119 during the week of December 13 (p<0.001). These findings indicate that point-of-care rapid antigen testing can be a valuable tool in reducing turnaround times in rural communities where local access to laboratory-based nucleic acid amplification testing (NAAT) is not readily available and could thereby reduce transmission by facilitating rapid isolation of infected persons, contact tracing, and implementation of local mitigation strategies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.299
GPT teacher head0.418
Teacher spread0.118 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2021
Admission routes1
Has abstractyes

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