Field performance of NowCheck rapid antigen test for SARS-CoV-2 in Kisumu County, western Kenya
Bibliographic record
Abstract
Abstract Background Low- and middle-income countries (LMICs) are increasingly adopting low-cost Coronavirus disease 2019 (COVID-19) rapid antigen tests to meet the high demand for SARS-CoV-2 testing. Whilst testing using real-time polymerase chain reaction (RT-PCR) is the current gold standard, its widespread use in LMICs is limited by high costs, turnaround times and is not readily available in most places. COVID-19 antigen tests (Ag-RDT) provide a suitable alternative due to their low cost, rapid turnaround time and easy to set up and use. This study aimed to assess the field performance of the NowCheck COVID-19 antigen kit (Ag-RDT) as a point of care test (POCT) in select healthcare facilities in western Kenya. Methods We conducted a prospective multi-facility field evaluation study of the NowCheck COVID-19 rapid antigen test (Ag-RDT) compared to SARS-CoV-2 RT-PCR (RT-PCR). After obtaining informed consent, trained laboratory technicians collected two pairs of oropharyngeal and nasopharyngeal swabs, both antigen and RT-PCR testing, first for Ag-RDT and next for RT-PCR. We performed Ag-RDTs on-site and shared the results with both the study participants and their healthcare providers within 15-30 minutes. We carried out all RT-PCR tests in a central referral laboratory. The turnaround time for RT-PCR results was typically 24-48 hours. We captured the results of both methods using an electronic digital application. Findings Between December 2020 and March 2021, we enrolled 997 participants who met the Kenyan Ministry of Health COVID-19 case definition. The median age of study participants was 39 years (range one to 80 years), with 54% male. Ag-RDT had a sensitivity of 84.5% (76.0-90.8) and a specificity of 94.4% (95% CI: 92.7-95.8) with an accuracy of 94.2% (92.5-95.6) when a cycle threshold value (Ct value) of ≤35 was used. The highest sensitivity of 87.7% (77.2-94.5) was observed in samples with Ct values ≤ 30 and the highest specificity of 97.5% (96.2-98.5) at Ct value of <40. Interpretation The NowCheck COVID-19 Ag-RDT showed good performance in field evaluation in multiple healthcare facilities in a developing country. The sensitivity of the kit exceeded the minimum recommended cut-off of 80% as recommended by WHO 1 . The high specificity of this kit at 94.4% at Ct values ≤33 and 97.5% at Ct values <40 matched that of real-time PCR, making it a good rule-out test for symptomatic patients with COVID-19-like symptoms. The faster turnaround time to results, lower cost, simple analytical steps requiring no equipment or infrastructure makes antigen testing an attractive field-screening method to meet the high demand for COVID-19 testing. Funding Achmea Foundation, Pfizer Foundation, Dimagi and the Netherlands Ministry of Foreign Affairs supported this project. The funding sources did not have any role in study design, data collection, analysis, interpretation, summarizing the data or decision to submit the manuscript for publication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".