Diagnostic Accuracy of Rapid Antigen Tests in Asymptomatic Close Contacts of Individuals With Confirmed SARS-CoV-2 Infections in the Herat Province of Afghanistan in 2021: Cross-sectional Study
Bibliographic record
Abstract
Background Early detection and isolation are key strategies for containing the COVID-19 pandemic in resource-poor countries, including Afghanistan, where access to the vaccines is limited. These strategies could reduce burden on the health care system, which is already weak because of conflicts and war. The first COVID-19 case in Afghanistan was detected in the Herat province close to Iran. Currently, both rapid antigen tests and reverse transcription–polymerase chain reaction (RT-PCR) have been used for the diagnosis of COVID-19 in the Herat province. Objective This study aimed to assess the accuracy of the rapid antigen test in asymptomatic close contacts of individuals with confirmed COVID-19 in the Herat province. Methods This was a cross-sectional study conducted by contact-tracing surveillance teams in the Herat province. The teams listed 200 asymptomatic close contacts of individuals with confirmed COVID-19, and 2 separate nasopharyngeal specimens were collected. The rapid antigen test (Biosensor) was used on the fourth and seventh day after contact, and the second specimen was sent to the reference lab for RT-PCR testing. Descriptive statistics were calculated. The sensitivity and specificity of the rapid antigen tests were compared with those of RT-PCR. Results The median age of the contacts was 35 years (range 11-90 years), and 138 (70%) were women. Of the 196 (98%) contacts for whom RT-PCR was used, 105 (53%) had confirmed results for SARS-CoV-2 infection. Only 30 (15%) cases of SARS-CoV-2 infection were confirmed by the rapid antigen test, which indicates a sensitivity of 20.1%. However, the specificity of the rapid antigen test was high (90%). Conclusions The sensitivity of the rapid antigen tests was relatively low to confirm COVID-19 in asymptomatic close contacts of individuals with confirmed COVID-19. Therefore, if resources allow, RT-PCR would be the best choice with its high sensitivity rate to diagnose COVID-19 in asymptomatic close contacts of individuals with confirmed COVID-19. Further study with a large sample size is needed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".