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Record W3130630945 · doi:10.1101/2021.02.22.21252219

Factors Associated with Timely Test Seeking, Test Turnaround, and Public Reporting of COVID-19: a retrospective analysis in Ontario, Canada

2021· preprint· en· W3130630945 on OpenAlexaffabout
Eugene Joh, Sarah A. Buchan, Nick Daneman, Lauren A. Paul, Kevin A. Brown

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoPublic Health OntarioToronto Public Health
Fundersnot available
KeywordsMedicineTest (biology)Logistic regressionOddsOdds ratioPublic healthPandemicDemographyCoronavirus disease 2019 (COVID-19)Retrospective cohort studyFamily medicineHealth careDiseaseNursingInfectious disease (medical specialty)SurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Minimizing delays in disease identification and reporting improves the timeliness of surveillance data, and can reduce transmission of COVID-19. Our study investigates factors associated with timely testing and reporting of COVID-19 during the first pandemic wave in one province of Canada. Methods We identified all persons with confirmed SARS-CoV-2 infection residing in private households across the largest province of Canada, Ontario from the date of the first confirmed case in Ontario (January 25) to July 19, 2020. Our primary outcomes consisted of: (1) specimen collection within 1 day of symptom onset (test seeking), (2) test result reported to local public health within 1 day of specimen collection (test turnaround), and (3) entry of case data into the provincial database within 1 day of reporting test results (reporting). We examined 14 covariates including eight case characteristics, and six neighborhood characteristics. In addition to descriptive measures, logistic regression models were fitted. Unadjusted models included the covariate alone, while adjusted models included age, gender, month, and region. Findings Among 27,198 COVID-19 cases from January 25 2020 to July 19 2020, 28·7% had timely test seeking, 40·2% had timely test turnaround, and 75·5% had timely reporting. Male gender had lower odds of timely test seeking (adjusted odds ratio [aOR] 0·79 [95% CI: 0·74-0·85]) compared to females. Healthcare worker status (aOR 2·77 [95% CI: 2·52-3·05] compared to non-healthcare workers), and age ≥80 years (aOR 1·59 [95% CI: 1·33-1·91] compared to 40-59 year olds) were associated with timely test seeking. Specimen collection on Fridays and Saturdays (aOR 0·88 [95% CI: 0·79-0·98], aOR 0·83 [95% CI: 0·74-0·92] respectively, compared to Wednesdays) had lower odds of timely test turnaround. Urban areas (aOR 1·55 [95% CI: 1·41-1·70] compared to rural areas) were associated with timely test turnaround. Urban areas (aOR 0·79 [95% CI: 0·70-0·89] compared to rural areas) were less likely to have timely reporting. Interpretation Individual, neighborhood, and administrative factors are associated with timely testing and reporting of SARS-CoV-2 infections. These findings present considerations for developing targeted strategies to minimize delays and improve timely testing and reporting of SARS-CoV-2 infections. Funding This study was funded by Public Health Ontario. Research in Context Evidence before this study We searched PubMed and medRxiv up to November 30 2020 to identify studies examining the impact of delays in the disease reporting process on the public health response to COVID-19. We used the search terms (“2019-nCoV” OR “COVID-19” OR “SARS-CoV-2”) AND (“delays” OR “timely” OR “reporting” OR “test” OR “turnaround”), and reviewed reference lists of any relevant articles in the original search. Numerous modeling studies have highlighted the importance of timely testing and reporting to effectively control the spread of COVID-19. Additional studies have also identified delays of only 1 day in testing were associated with increased risk of secondary transmission within households. However no study has described the multiple delays in the disease reporting process of COVID-19 and examined factors associated with timely disease reporting using a large population cohort. Added value of this study Our study described timely test seeking, test turnaround, and reporting for laboratory-confirmed COVID-19 cases in Ontario, Canada and identified associated individual, neighbourhood, and administrative factors. To the best of our knowledge, this study is the first to describe detailed delays in the disease reporting process of COVID-19 and identified associated factors using a large population cohort. Implications of all the available evidence Numerous individual, neighborhood, and administrative characteristics are associated with timely testing and reporting of COVID-19. These identified factors may be used to develop strategies such as broadened test access, prioritization of vulnerable populations, and increased testing capacity to reduce delays in testing and reporting and improve the effectiveness of public health response to COVID-19.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
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 head0.073
GPT teacher head0.292
Teacher spread0.219 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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