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Record W4411964674 · doi:10.2196/68600

Identifying Optimal Testing Modalities to Increase COVID-19 Testing Access in Baltimore, Maryland: Protocol for a Household Randomized Controlled Trial

2025· article· en· W4411964674 on OpenAlexvenueno aff
Jessica Wagner, Saifuddin Ahmed, Jamie Perin, Courtney Borsuk, J. E. TROWELL, Kelly Lowensen, Steven Huettner, Andy Peytchev, Jason E. Farley, Shruti H. Mehta, Jacky M. Jennings

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious Diseases
KeywordsPreprintCoronavirus disease 2019 (COVID-19)Randomized controlled trialSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)ModalitiesProtocol (science)2019-20 coronavirus outbreakMedicineGerontologyComputer scienceVirologyAlternative medicineWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic disproportionately affected low-income and racial and ethnic minority populations. Testing plays a critical role in disrupting disease transmission, but complex barriers prevent optimal testing access, particularly for Black and Latinx communities. There is limited evidence regarding the optimal testing modalities to increase testing access for these populations. OBJECTIVE: This study aimed to define the optimal COVID-19 testing modalities for maximizing testing acceptance, uptake, and timeliness of receipt of results. METHODS: The Community Collaboration to Combat COVID-19 (C-FORWARD) trial was a household randomized comparative effectiveness trial conducted in a representative sample of an urban population. Households across 653 census block groups were sampled using a probability proportional to size approach. The primary outcome was the completion of SARS-CoV-2 or COVID-19 testing within 30 days of randomization. RESULTS: Between February 2021 and December 2022, a total of 1083 individuals were enrolled, including 881 (81.35%) index participants and 202 (18.65%) household members. The mean age of participants was 51 (SD 18) years.Of the total sample, 43% (n=460) of participants identified as Black or African American, 48.6% (n=526) as White, and 9% (n=91) as other, including Asian, American Indian, Native Hawaiian or Pacific Islander, and multiple races; 4.8% (n=48) of participants identified as Hispanic or Latino. At the time of enrollment, 51.1% (n=553) were currently working either full time or part time, and 32.9% (n=342) of participants had an advanced degree. In total, 80% (n=809) of participants had been tested for COVID-19 previously, with 22.3% (n=179) reporting a prior positive test for COVID-19, and 86.8% (n=890) reporting receiving at least one COVID-19 vaccination before enrollment. CONCLUSIONS: Data from the C-FORWARD trial will be used to address important questions regarding COVID-19 testing acceptance and uptake in an urban population. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/68600.

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)0.016
metaresearch head score (Gemma)0.149
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.132
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.149
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.533
GPT teacher head0.612
Teacher spread0.079 · 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 designRandomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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