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BackgroundA considerable proportion of SARS-CoV-2 transmission occurs from asymptomatic and pre-symptomatic cases. Therefore, different polymerase chain reaction (PCR)- or rapid antigen test (RAT)-based approaches are being discussed and applied to identify infectious cases that would have gone undetected (e.g., in nursing homes). In this article, we provide a framework to estimate the time-dependent risk of being infectious after a negative SARS-CoV-2 test and we simulate the number of expected cases over time in populations of individuals who initially tested negative. MethodsA Monte Carlo approach is used to simulate infections that occurred over a one-week period in populations with 1,000 individuals following a negative SARS-Cov-2 test. Parameters representing the application of PCR tests or RATs are utilized, and SARS-CoV-2 7-day incidences between 25 and 200 per 100,000 people are considered. Simulation results are compared to case numbers predicted via a mathematical equation. ResultsThe simulations showed a linear increase in cases over time in populations of individuals who initially tested SARS-CoV-2 negative. The different false negative rates of PCR tests and RATs have a strong impact on the number of simulated cases. The simulated and the mathematically predicted case numbers were comparable. However, Monte Carlo simulations highlight that, due to random effects, infectious cases can exceed predicted case numbers even shortly after a test was conducted. ConclusionsThe analysis demonstrates that the number of infectious cases in a population can be effectively reduced by the screening of asymptomatic individuals. However, the time since the negative test and the underlying SARS-CoV-2 incidence are critical parameters in determining the observed subsequent number of cases in tested populations.
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BackgroundSARS-CoV-2 molecular diagnostics is facing material shortages and long turnaround times due to exponential increase of testing demand. ObjectiveWe evaluated the analytic performance and handling of four rapid Antigen Point of Care Tests (AgPOCTs) I-IV (Distributors: (I) Roche, (II) Abbott, (III) MEDsan and (IV) Siemens). Methods100 RT-PCR negative and 84 RT-PCR positive oropharyngeal swabs were prospectively collected and used to determine performance and accuracy of these AgPOCTs. Handling was evaluated by 10 healthcare workers/users through a questionnaire. ResultsThe median duration from symptom onset to sampling was 6 days (IQR 2-12 days). The overall relative sensitivity was 49.4%, 44.6%, 45.8% and 54.9 % for tests I, II, III and IV, respectively. In the high viral load subgroup (containing >106 copies of SARS-CoV-2 /swab, n=26), AgPOCTs reached sensitivities of 92.3% or more (range 92.3%-100%). Specificity was 100% for tests I, II and IV and 97% for test III. Regarding handling, test I obtained the overall highest scores, while test II was considered to have the most convenient components. Of note, users considered all assays, with the exception of test I, to pose a significant risk for contamination by drips or spills. DiscussionBesides some differences in sensitivity and handling, all four AgPOCTs showed acceptable performance in high viral load samples. However, due to the significantly lower sensitivity compared to RT-qPCR, a careful consideration of pro and cons of AgPOCT has to be taken into account before clinical implementation.
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Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aimed to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We conducted a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality was extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses included patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine was 1.11 (95% CI: 1.02, 1.20; I2=0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I2=0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine was associated with increased mortality in COVID-19 patients, and there was no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.