Mass Screening of SARS-CoV-2 With Rapid Antigen Tests in a Receding Omicron Wave: Population-Based Survey for Epidemiologic Evaluation
Bibliographic record
Abstract
BACKGROUND: The COVID-19 Omicron BA.2 epidemic wave in Hong Kong peaked in the first quarter of 2022. Following the implementation of stringent public health measures, the daily number of reported cases fell from over 50,000 to below 2000. Although outbreaks steadily receded, the government rolled out a 3-day "voluntary universal rapid testing" campaign to invite all citizens to self-perform a rapid antigen test (RAT) daily to identify undetected prevalent infections. OBJECTIVE: This study aimed to evaluate the uptake and results of RAT mass screening to estimate the population's residual epidemic burden and assess the risk of further transmission. METHODS: A cross-sectional study comprising an open web-based population-based survey was conducted a week after the RAT campaign. Participants were asked to report their COVID-19 vaccination and infection history and the RAT performance and test result during the period. They were also invited to report their coliving individuals' test performance and results. Reasons for nonuptake were enquired. Testing and positive rates were age-adjusted. Determinants of undergoing RAT were identified using univariable and multivariable logistic regression models. RESULTS: In total, particulars from 21,769 individuals were reported by 8338 participants. The overall age-adjusted testing rate was 74.94% (95% CI 73.71%-76.18%), with over 80% of participants in the age groups between 45-84 years having self-performed RAT during the campaign period. After age-adjustment, 1.03% (95% CI 0.86%-1.21%) of participants tested positive. The positive rates in the age groups between 20-29 years and >84 years exceeded 2%. Taking into account the positive rate and 5819 reported cases during the period, the cases identified in the campaign might account for 7.65% (95% CI 6.47%-9.14%) of all infections. Testers were more likely to be female, older, not previously diagnosed with COVID-19, and have received COVID-19 vaccination. Adjusting for the number of household members, those living with a child aged <12 years and whose household members were also tested were more likely to have self-performed an RAT. Main reasons for not performing an RAT included the absence of symptoms (598/1108, 53.97%), disbelief of the appropriateness of the campaign as an antiepidemic measure (355/1108, 32.04%), and a recent COVID-19 diagnosis (332/1108, 29.96%). CONCLUSIONS: The residual population burden remained substantial in spite of the clear evidence of a receding epidemic wave. Despite caution in generalization to the Hong Kong population, the high participation rate in mass screening indicated that the voluntary RAT was well accepted, making it a feasible option for implementation as a complementary means of public health surveillance.
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 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 | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".