Background: Reliable point-of-care (POC) diagnostics not requiring laboratory infrastructure could be a game changer in the COVID-19 pandemic, particularly in the Global South. We assessed performance, limit of detection (LOD) and ease-of-use of three antigen-detecting, rapid POC diagnostics (Ag-RDT) for SARS-CoV-2. Methods: This prospective, multi-centre diagnostic accuracy study, recruited participants suspected to have SARS-CoV2 in Germany and UK. Paired nasopharyngeal swabs (NP) or NP and/or oropharyngeal swabs (OP) were collected from participants (one for clinical real-time reverse transcription polymerase chain reaction (RT-PCR) and one for Ag-RDT testing). Performance of each of three Ag-RDTs was compared to RT-PCR overall, and according to predefined subcategories e.g. cycle threshold (CT)-value, days from symptom onset, etc. In addition, limited verification of analytical limit-of-detection (LOD) was determined. To understand the usability of each Ag-RDT a System Usability Scale (SUS) questionnaire and ease-of-use assessment were performed. Results: Between April 17th and August 25th, 2020, 2417 participants were enrolled, with 70 (3.0%) testing positive by RT-PCR. The best-performing test (SD Biosensor, Inc. STANDARD Q) was 76.6% [95% Confidence Interval (CI) 62.8-86.4] sensitive and 99.3% [CI 98.6-99.6] specific. A sub-analysis showed all samples with RT-PCR CT-values <25 were detectable by STANDARD Q. The test was considered easy-to-use (SUS 86/100) and suitable for POC. Bioeasy and Coris showed specificity of 93.1% [CI 91.0%-94.8%] and 95.8% [CI 93.4%-97.4%], respectively, not meeting the predefined target of ≥98%. Conclusion: There is large variability in performance of Ag-RDT tests with one test showing promise. Given the usability at POC, these tests are likely to have impact despite imperfect sensitivity; however further research and modelling are needed.

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Background: Two antigen-detecting rapid diagnostic tests (Ag-RDTs) are now approved through the WHO Emergency Use Listing procedure and can be performed at the point-of-care. However, both tests use nasopharyngeal (NP) swab samples. NP swab samples must be collected by trained healthcare personnel with protective equipment and are frequently perceived as uncomfortable by patients. Methods: This was a manufacturer-independent, prospective diagnostic accuracy study with comparison of a supervised, self-collected anterior nasal (AN) swab sample with a professional-collected NP swab sample, using a WHO-listed SARS-CoV-2 Ag-RDT, STANDARD Q COVID-19 Ag Test (SD Biosensor), which is also being distributed by Roche. The reference standard was RT-PCR from an oro-/nasopharyngeal swab sample. Percent positive and negative agreement as well as sensitivity and specificity were calculated. Results: Among the 289 participants, 39 (13.5%) tested positive for SARS-CoV-2 by RT-PCR. The positive percent agreement of the two different sampling techniques for the Ag-RDT was 90.6% (CI 75.8-96.8). The negative percent agreement was 99.2% (CI 97.2-99.8). The Ag-RDT with AN sampling showed a sensitivity of 74.4% (29/39 PCR positives detected; CI 58.9-85.4) and specificity of 99.2% (CI 97.1-99.8) compared to RT-PCR. The sensitivity with NP sampling was 79.5% (31/39 PCR positives detected; CI 64.5-89.2) and specificity was 99.6% (CI 97.8-100). In patients with high viral load (>7.0 log10 RNA SARS-CoV2/swab), the sensitivity of the Ag-RDT with AN sampling was 96% and 100% with NP sampling. Conclusion: Supervised self-sampling from the anterior nose is a reliable alternative to professional nasopharyngeal sampling using a WHO-listed SARS-CoV-2 Ag-RDT. Considering the ease-of-use of Ag-RDTs, self-sampling and potentially patient self-testing at home may be a future use case.

Background Antigen-detecting rapid diagnostic tests (Ag-RDTs) for SARS-CoV-2 are important diagnostic tools. We assessed clinical performance and ease-of-use of seven Ag-RDTs in a prospective, manufacturer-independent, multi-centre cross-sectional diagnostic accuracy study to inform global decision makers. Methods Unvaccinated participants suspected of a first SARS-CoV-2 infection were recruited at six sites (Germany, Brazil). Ag-RDTs were evaluated sequentially, with collection of paired swabs for routine reverse transcription polymerase chain reaction (RT-PCR) testing and Ag-RDT testing. Performance was compared to RT-PCR overall and in sub-group analyses (viral load, symptoms, symptoms duration). To understandusability a System Usability Scale (SUS) questionnaire and ease-of-use (EoU) assessment were performed. Findings 7471 participants were included in the analysis. Sensitivities across Ag-RDTs ranged from 70·4%-90·1%, specificities were above 97·2% for all Ag-RDTs but one (93·1%).Ag-RDTs, Mologic, Bionote, Standard Q, showed diagnostic accuracy in line with WHO targets (> 80% sensitivity, > 97% specificity). All tests showed high sensitivity in the first three days after symptom onset (≥87·1%) and in individuals with viral loads≥ 6 log 10 SARS-CoV2 RNA copies/mL (≥ 88·7%). Usability varied, with Rapigen, Bionote and Standard Q reaching very good scores; 90, 88 and 84/100, respectively. Interpretation Variability in test performance is partially explained by variable viral loads in population evaluated over the course of the pandemic. All Ag-RDTs reach high sensitivity early in the disease and in individuals with high viral loads, supporting their role in identifying transmission relevant infections. For easy-to-use tests, performance shown will likely be maintained in routine implementation. Funding Ministry of Science, Research and Arts, State of Baden-Wuerttemberg, Germany, internal funds from Heidelberg University Hospital, University Hospital Charité − Universitätsmedizin Berlin, UK Department of International Development, WHO, Unitaid.

Objectives In this cluster-randomised controlled study (CoV-Surv Study), four different “active” SARS-CoV-2 testing strategies for general population surveillance are evaluated for their effectiveness in determining and predicting the prevalence of SARS-CoV-2 infections in a given population. In addition, the costs and cost-effectiveness of the four surveillance strategies will be assessed. Further, this trial is supplemented by a qualitative component to determine the acceptability of each strategy. Findings will inform the choice of the most effective, acceptable and affordable strategy for SARS-CoV-2 surveillance, with the most effective and cost-effective strategy becoming part of the local public health department’s current routine health surveillance activities. Investigating its everyday performance will allow us to examine the strategy’s applicability to real time prevalence prediction and the usefulness of the resulting information for local policy makers to implement countermeasures that effectively prevent future nationwide lockdowns. The authors would like to emphasize the importance and relevance of this study and its expected findings in the context of population-based disease surveillance, especially in respect to the current SARS-CoV-2 pandemic. In Germany, but also in many other countries, COVID-19 surveillance has so far largely relied on passive surveillance strategies that identify individuals with clinical symptoms, monitor those cases who then tested positive for the virus, followed by tracing of individuals in close contact to those positive cases. To achieve higher effectiveness in population surveillance and to reliably predict the course of an outbreak, screening and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic. To better control and manage the SARS-CoV-2 pandemic, current strategies therefore need to be complemented by an active surveillance of the wider population, i.e. routinely conducted testing and monitoring activities to identify and isolate infected individuals regardless of their clinical symptoms. Such active surveillance strategies will enable more effective prevention of the spread of the virus as they can generate more precise population-based parameters during a pandemic. This essential information will be required in order to determine the best strategic and targeted short-term countermeasures to limit infection spread locally. Trial design This trial implements a cluster-randomised, two-factorial controlled, prospective, interventional, single-blinded design with four study arms, each representing a different SARS-CoV-2 testing and surveillance strategy. Participants Eligible are individuals age 7 years or older living in Germany’s Rhein-Neckar Region who consent to provide a saliva sample (all four arms) after completion of a brief questionnaire (two arms only). For the qualitative component, different samples of study participants and non-participants (i.e. eligible for study, but refuse to participate) will be identified for additional interviews. For these interviews, only individuals age 18 years or older are eligible. Intervention and comparator Of the four surveillance strategies to be assessed and compared, Strategy A1 is considered the gold standard for prevalence estimation and used to determine bias in other arms. To determine the cost-effectiveness, each strategy is compared to status quo, defined as the currently practiced passive surveillance approach. Strategy A1: Individuals (one per household) receive information and study material by mail with instructions on how to produce a saliva sample and how to return the sample by mail. Once received by the laboratory, the sample is tested for SARS-CoV-2 using Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP). Strategy A2: Individuals (one per household) receive information and study material by mail with instructions on how to produce their own as well as saliva samples from each household member and how to return these samples by mail. Once received by the laboratory, the samples are tested for SARS-CoV-2 using RT-LAMP. Strategy B1: Individuals (one per household) receive information by mail on how to complete a brief pre-screening questionnaire which asks about COVID-19 related clinical symptoms and risk exposures. Only individuals whose pre-screening score crosses a defined threshold, will then receive additional study material by mail with instructions on how to produce a saliva sample and how to return the sample by mail. Once received by the laboratory, the saliva sample is tested for SARS-CoV-2 using RT-LAMP. Strategy B2: Individuals (one per household) receive information by mail on how to complete a brief pre-screening questionnaire which asks about COVID-19 related clinical symptoms. Only individuals whose pre-screening score crosses a defined threshold, will then receive additional study material by mail with instructions how to produce their own as well as saliva samples from each household member and how to return these samples by mail. Once received by the laboratory, the samples are tested for SARS-CoV-2 using RT-LAMP. In each strategy, RT-LAMP positive samples are additionally analyzed with qPCR in order to minimize the number of false positives. Main outcomes The identification of the one best strategy will be determined by a set of parameters. Primary outcomes include costs per correctly screened person, costs per positive case, positive detection rate, and precision of positive detection rate. Secondary outcomes include participation rate, costs per asymptomatic case, prevalence estimates, number of asymptomatic cases per study arm, ratio of symptomatic to asymptomatic cases per study arm, participant satisfaction. Additional study components (not part of the trial) include cost effectiveness of each of the four surveillance strategies compared to passive monitoring (i.e. status quo), development of a prognostic model to predict hospital utilization caused by SARS-CoV-2, time from test shipment to test application and time from test shipment to test result, and perception and preferences of the persons to be tested with regard to test strategies. Randomisation Samples are drawn in three batches of three continuous weeks. Randomisation follows a two-stage process. First, a total of 220 sampling points have been allocated to the three different batches. To obtain an integer solution, the Cox-algorithm for controlled rounding has been used. Afterwards, sample points have been drawn separately per batch, following a probability proportional to size (PPS) random sample. Second, for each cluster the same number of residential addresses is randomly sampled from the municipal registries (self-weighted sample of individuals). The 28,125 addresses drawn per municipality are then randomly allocated to the four study arms A1, A2, B1, and B2 in the ratio 5 to 2.5 to 14 to 7 based on the expected response rates in each arm and the sensitivity and specificity of the pre-screening tool as applied in strategy B1 and B2. Based on the assumptions, this allocation should yield 2500 saliva samples in each strategy. Although a municipality can be sampled by multiple batches and the overall number of addresses per municipality might vary, the number of addresses contacted in each arm is kept constant. Blinding (masking) The design is single-blinded, meaning the staff conducting the SARS-CoV-2 tests are unaware of the study arm assignment of each single participant and test sample. Sample sizes Total sample size for the trial is 10,000 saliva samples equally allocated to the four study arms (i.e. 2,500 participants per arm). For the qualitative component, up to 60 in-depth interviews will be conducted with about 30 study participants (up to 15 in each arm A and B) and 30 participation refusers (up to 15 in each arm A and B) purposefully selected from the quantitative study sample to represent a variety of gender and ages to explore experiences with admission or rejection of study participation. Up to 25 asymptomatic SARS-CoV-2 positive study participants will be purposefully selected to explore the way in which asymptomatic men and women diagnosed with SARS-CoV-2 give meaning to their diagnosis and to the dialectic between feeling concurrently healthy and yet also being at risk for transmitting COVID-19. In addition, 100 randomly selected study participants will be included to explore participants’ perspective on testing processes and implementation. Trial Status Final protocol version is “Surveillance_Studienprotokoll_03Nov2020_v1_2” from November 3, 2020. Recruitment started November 18, 2020 and is expected to end by or before December 31, 2020. Trial registration The trial is currently being registered with the German Clinical Trials Register (Deutsches Register Klinischer Studien), DRKS00023271 (https://www.drks.de/drks_web/navigate.do?navigationId=trial. HTML&TRIAL_ID=DRKS00023271). Retrospectively registered 30 November 2020. Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Background To achieve higher effectiveness in population-based SARS-CoV-2 surveillance and to reliably predict the course of an outbreak, screening, and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic. Methods This trial implements a two-factorial, randomized, controlled, multi-arm, prospective, interventional, single-blinded design with cluster sampling and four study arms, each representing a different SARS-CoV-2 testing and surveillance strategy based on individuals’ self-collection of saliva samples which are then sent to and analyzed by a laboratory. The targeted sample size for the trial is 10,000 saliva samples equally allocated to the four study arms (2500 participants per arm). Strategies differ with respect to tested population groups (individuals vs. all household members) and testing approach (without vs. with pre-screening survey). The trial is complemented by an economic evaluation and qualitative assessment of user experiences. Primary outcomes include costs per completely screened person, costs per positive case, positive detection rate, and precision of positive detection rate. Discussion Systems for active surveillance of the general population will gain more importance in the context of pandemics and related disease prevention efforts. The pandemic parameters derived from such active surveillance with routine population monitoring therefore not only enable a prospective assessment of the short-term course of a pandemic, but also a more targeted and thus more effective use of local and short-term countermeasures. Trial registration ClinicalTrials.gov DRKS00023271. Registered November 30, 2020, with the German Clinical Trials Register (Deutsches Register Klinischer Studien)

Since the first identified case of COVID-19 in Wuhan, China, the disease has developed into a pandemic, imposing a major challenge for health authorities and hospitals worldwide. Mathematical transmission models can help hospitals to anticipate and prepare for an upcoming wave of patients by forecasting the time and severity of infections. Taking the city of Heidelberg as an example, we predict the ongoing spread of the disease for the next months including hospital and ventilator capacity and consider the possible impact of currently imposed countermeasures.

Background Most data on COVID-19 was collected in hospitalized cases. Much less is known about the spectrum of disease in entire populations. In this study, we examine a representative cohort of primarily symptomatic cases in an administrative district in Southern Germany. Methods We contacted all confirmed SARS-CoV-2 cases in the administrative district. Consenting participants answered a retrospective survey either via a telephone, electronically or via mail. Clinical and sociodemographic features were compared between hospitalized and non-hospitalized patients. Additionally, we assessed potential risk factors for hospitalization and time to hospitalization in a series of regression models. Results We included 897 participants in our study, 69% out of 1,305 total cases in the district with a mean age of 47 years (range 2–97), 51% of which were female and 47% had a pre-existing illness. The percentage of asymptomatic, mild, moderate (leading to hospital admission) and critical illness (requiring mechanical ventilation) was 54 patients (6%), 713 (79%), 97 (11%) and 16 (2%), respectively. Seventeen patients (2%) died. The most prevalent symptoms were fatigue (65%), cough (62%) and dysgeusia (60%). The risk factors for hospitalization included older age (OR 1.05 per year increase; 95% CI 1.04–1.07) preexisting lung conditions (OR 3.09; 95% CI 1.62–5.88). Female sex was a protective factor (OR 0.51; 95% CI 0.33–0.77). Conclusion This representative analysis of primarily symptomatic COVID-19 cases confirms age, male sex and preexisting lung conditions but not cardiovascular disease as risk factors for severe illness. Almost 80% of infection take a mild course, whereas 13% of patients suffer moderate to severe illness. Trial registration German Clinical Trials Register, DRKS00022926. URL: https://www.drks.de/drks_web/setLocale_EN.do