RESUMO
BackgroundSARS-CoV-2 self-tests may lower the threshold of testing and produce a result quickly. This could support the early detection of infectious cases and reduce further community transmission. However, the diagnostic accuracy of (unsupervised) self-testing with rapid antigen diagnostic tests (Ag-RDTs) is mostly unknown. We therefore conducted a large-scale head-to-head comparison of the diagnostic accuracy of a self-performed SARS-CoV-2 saliva and nasal Ag-RDT, each compared to a molecular reference test, in the general population in the Netherlands. MethodsIn this cross-sectional study we consecutively included individuals aged 16 years and older presenting for SARS-CoV-2 testing at three Dutch public health service test sites irrespective of their indication for testing, vaccination status, and symptomatology. Participants were sampled for molecular testing at the test site and received two self-tests (the Hangzhou AllTest saliva self-test and the SD Biosensor nasal self-test by Roche Diagnostics) to perform at home within a few hours without knowledge of their molecular test result. Information on presence and type of symptoms, user experiences, and results of both self-tests were collected via an online questionnaire. For each self-test, sensitivity, specificity, positive and negative predictive values were determined with molecular testing as reference standard. FindingsThe SARS-CoV-2 molecular reference test positivity rate was 6.5% in the 2,819 participants. Overall sensitivities with 95% confidence intervals were 46.7% (85/182; 39.3%-54.2%) for the saliva Ag-RDT, and 68.9% (124/180; 61.6%-75.6%) for the nasal Ag-RDT. With a viral load cut-off ([≥]5.2 log10 SARS-CoV-2 E-gene copies/mL) as a proxy of infectiousness, sensitivities increased to 54.9% (78/142; 46.4%-63.3%) for the saliva Ag-RDT and 83.9% (120/143; 76.9%-89.5%) for the nasal Ag-RDT. For the nasal Ag-RDT, sensitivities were 78.5% [71.1%-84.8%] and 22.6% [9.6%-41.1%] in those with and without symptoms at the time of sampling, which increased to 90.4% (113/125; 83.8%-94.9%) and 38.9% (7/18; 17.3%-64.3%) after applying the viral load cut-off. In those with and without prior confirmed SARS-CoV-2, sensitivities were 36.8% [19/372; 16.3%-61.6%] and 72.7% [161/2437; 65.1%-79.4%] for the nasal Ag-RDT, which increased to 100% (7/7; 59.0%-100%) and 83.1% (113/126; 75.7%-89.0%) after applying the viral load cut-off. The diagnostic accuracy of the nasal Ag-RDT did not differ by COVID-19 vaccination status, sex, and age. Specificities were >99%, positive predictive values >70% and negative predictive values >95%, for the saliva Ag-RDT, and >99%, >90%, and >95% for the nasal Ag-RDT, respectively, in most analyses. Interpreting the results was considered (very) easy for both self-tests. InterpretationThe Hangzhou AllTest self-performed saliva Ag-RDT is not reliable for SARS-CoV-2 infection detection overall nor in the studied subgroups. The SD Biosensor self-performed nasal Ag-RDT had high sensitivity in individuals with symptoms and in those without a prior SARS-CoV-2 infection. The overall accuracy in individuals with symptoms was comparable to that found in previous studies with professional sampling for this Ag-RDT. The extremely low sensitivity of the nasal Ag-RDT in asymptomatic individuals and in individuals who had had a prior SARS-CoV-2 infection is an important finding and warrants further investigation. FundingDutch Ministry of Health, Welfare, and Sport.
RESUMO
BackgroundIn autumn 2020, many countries, including the Netherlands, are experiencing a second wave of the COVID-19 pandemic. Health policymakers are struggling with choosing the right mix of measures to keep the COVID-19 case numbers under control, but still allow a minimum of social and economic activity. The priority to keep schools open is high, but the role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We used a transmission model to estimate the impact of school contacts on transmission of SARS-CoV-2 and to assess the effects of school-based measures, including school closure, on controlling the pandemic at different time points during the pandemic. Methods and FindingsThe age-structured model was fitted to age-specific seroprevalence and hospital admission data from the Netherlands during spring 2020. Compared to adults older than 60 years, the estimated susceptibility was 23% (95%CrI 20--28%) for children aged 0 to 20 years and 61% (95%CrI 50%--72%) for the age group of 20 to 60 years. The time points considered in the analyses were (i) August 2020 when the effective reproduction number (Re) was estimated to be 1.31 (95%CrI 1.15--2.07), schools just opened after the summer holidays and measures were reinforced with the aim to reduce Re to a value below 1, and (ii) November 2020 when measures had reduced Re to 1.00 (95%CrI 0.94--1.33). In this period schools remained open. Our model predicts that keeping schools closed after the summer holidays, in the absence of other measures, would have reduced Re by 10% (from 1.31 to 1.18 (95%CrI 1.04--1.83)) and thus would not have prevented the second wave in autumn 2020. Reducing non-school-based contacts in August 2020 to the level observed during the first wave of the pandemic would have reduced Re to 0.83 (95%CrI 0.75--1.10). Yet, this reduction was not achieved and the observed Re in November was 1.00. Our model predicts that closing schools in November 2020 could reduce Re from the observed value of 1.00 to 0.84 (95%CrI 0.81--0.90), with unchanged non-school based contacts. Reductions in Re due to closing schools in November 2020 were 8% for 10 to 20 years old children, 5% for 5 to 10 years old children and negligible for 0 to 5 years old children. ConclusionsThe impact of measures reducing school-based contacts, including school closure, depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce Re with non-school-based measures are exhausted or undesired and Re is still close to 1, the additional benefit of school-based measures may be considerable, particularly among the older school children.
