Speed versus coverage trade off in targeted interventions during an outbreak

From more testing to smart testing: data-guided SARS-CoV-2 testing choices, the Netherlands, May to September 2020

Background

SARS-CoV-2 RT-PCR assays are more sensitive than rapid antigen detection assays (RDT) and can detect viral RNA even after an individual is no longer infectious. RDT can reduce the time to test and the results might better correlate with infectiousness.

Aim

We assessed the ability of five RDT to identify infectious COVID-19 cases and systematically recorded the turnaround time of RT-PCR testing.

Methods

Sensitivity of RDT was determined using a serially diluted SARS-CoV-2 stock with known viral RNA concentration. The probability of detecting infectious virus at a given viral load was calculated using logistic regression of viral RNA concentration and matched culture results of 78 specimens from randomly selected non-hospitalised cases. The probability of each RDT to detect infectious cases was calculated as the sum of the projected probabilities for viral isolation success for every viral RNA load found at the time of diagnosis in 1,739 confirmed non-hospitalised COVID-19 cases.

Results

The distribution of quantification cycle values and estimated RNA loads for patients reporting to drive-through testing was skewed to high RNA loads. With the most sensitive RDT (Abbott and SD Biosensor), 97.30% (range: 88.65–99.77) of infectious individuals would be detected. This decreased to 92.73% (range: 60.30–99.77) for Coris BioConcept and GenBody, and 75.53% (range: 17.55–99.77) for RapiGEN. Only 32.9% of RT-PCR results were available on the same day as specimen collection.

Conclusion

The most sensitive RDT detected infectious COVID-19 cases with high sensitivity and may considerably improve containment through more rapid isolation and contact tracing.

Limit of detection in different matrices of 19 commercially available rapid antigen tests for the detection of SARS-CoV-2

In the context of the coronavirus disease 2019 (COVID-19) pandemic there has been an increase of the use of antigen-detection rapid diagnostic tests (Ag-RDT). The performance of Ag-RDT vary greatly between manufacturers and evaluating their analytical limit of detection (LOD) has become high priority. Here we describe a manufacturer-independent evaluation of the LOD of 19 marketed Ag-RDT using live SARS-CoV-2 spiked in different matrices: direct culture supernatant, a dry swab, and a swab in Amies. Additionally, the LOD using dry swab was investigated after 7 days' storage at - 80 °C of the SARS-CoV-2 serial dilutions. An LOD of ≈ 5.0 × 102 pfu/ml (1.0 × 106 genome copies/ml) in culture media is defined as acceptable by the World Health Organization. Fourteen of 19 Ag-RDTs (ActiveXpress, Espline, Excalibur, Innova, Joysbio, Mologic, NowCheck, Orient, PanBio, RespiStrip, Roche, Standard-F, Standard-Q and Sure-Status) exceeded this performance criteria using direct culture supernatant applied to the Ag-RDT. Six Ag-RDT were not compatible with Amies media and a decreased sensitivity of 2 to 20-fold was observed for eleven tests on the stored dilutions at - 80 °C for 7 days. Here, we provide analytical sensitivity data to guide appropriate test and sample type selection for use and for future Ag-RDT evaluations.

Accuracy of the Mologic COVID-19 rapid antigen test: a prospective multi-centre analytical and clinical evaluation

Background: The coronavirus disease 2019 (COVID-19) pandemic has highlighted the reliance on antigen detection rapid diagnostic tests (Ag-RDTs). Their evaluation at point of use is a priority. Methods: Here, we report a multi-centre evaluation of the analytical sensitivity, specificity, and clinical accuracy of the Mologic COVID-19 Ag-RDT by comparing to reverse transcriptase polymerase chain reaction (RT-qPCR) results from individuals with and without COVID-19 symptoms. Participants had attended hospitals in Merseyside, hospital and ambulance services in Yorkshire, and drive-through testing facilities in Northumberland, UK. Results: The limit of detection of the Mologic COVID-19 Ag-RDT was 5.0 x 102 pfu/ml in swab matrix with no cross-reactivity and interference for any other pathogens tested. A total of 347 participants were enrolled from 26th of November 2020 to 15th of February 2021 with 39.2% (CI 34.0-44.6) testing RT-qPCR positive for SARS-CoV-2. The overall sensitivity and specificity of the Mologic Ag-RDT compared to the reference SARS-CoV-2 RT-qPCR were 85.0% (95% CI 78.3-90.2) and 97.8% (95.0-99.3), respectively. Sensitivity was stratified by RT-qPCR cycle threshold (Ct) and 98.4% (91.3-100) of samples with a Ct less than 20 and 93.2% (86.5-97.2) of samples with a Ct less than 25 were detected using the Ag-RDT. Clinical accuracy was stratified by sampling strategy, swab type and clinical presentation. Mologic COVID-19 Ag-RDT demonstrated highest sensitivity with nose/throat swabs compared with throat or nose swabs alone; however, the differences were not statistically significant. Conclusions: Overall, the Mologic test had high diagnostic accuracy across multiple different settings, different demographics, and on self-collected swab specimens. These findings suggest the Mologic rapid antigen test may be deployed effectively across a range of use settings.

Clinical Evaluation of Roche SD Biosensor Rapid Antigen Test for SARS-CoV-2 in Municipal Health Service Testing Site, the Netherlands

Rapid detection of infection is essential for stopping the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Roche SD Biosensor rapid antigen test for SARS-CoV-2 was evaluated in a nonhospitalized symptomatic population. We rapid-tested a sample onsite and compared results with those from reverse transcription PCR and virus culture. We analyzed date of onset and symptoms using data from a clinical questionnaire. Overall test sensitivity was 84.9% (95% CI 79.1–89.4) and specificity was 99.5% (95% CI 98.7–99.8). Sensitivity increased to 95.8% (95% CI 90.5–98.2) for persons who sought care within 7 days of symptom onset. Test band intensity and time to result correlated strongly with viral load; thus, strong positive results could be read before the recommended time. Approximately 98% of all viable specimens with cycle threshold <30 were detected. Rapid antigen tests can detect symptomatic SARS-CoV-2 infections in the early phase of disease, thereby identifying the most infectious persons.

Preparing for Emerging Zoonotic Viruses

The risk of emergence and spread of novel human pathogens originating from an animal reservoir has increased in the past decades. However, the unpredictable nature of disease emergence makes surveillance and preparedness challenging. Knowledge of general risk factors for emergence and spread, combined with local level data is needed to develop a risk-based methodology for early detection. This involves the implementation of the One Health approach, integrating human, animal and environmental health sectors, as well as social sciences, bioinformatics and more. Recent technical advances, such as metagenomic sequencing, will aid the rapid detection of novel pathogens on the human-animal interface.

Impact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study

Background

In countries with declining numbers of confirmed cases of COVID-19, lockdown measures are gradually being lifted. However, even if most physical distancing measures are continued, other public health measures will be needed to control the epidemic. Contact tracing via conventional methods or mobile app technology is central to control strategies during de-escalation of physical distancing. We aimed to identify key factors for a contact tracing strategy to be successful.

Methods

We evaluated the impact of timeliness and completeness in various steps of a contact tracing strategy using a stochastic mathematical model with explicit time delays between time of infection and symptom onset, and between symptom onset, diagnosis by testing, and isolation (testing delay). The model also includes tracing of close contacts (eg, household members) and casual contacts, followed by testing regardless of symptoms and isolation if testing positive, with different tracing delays and coverages. We computed effective reproduction numbers of a contact tracing strategy (R_CTS) for a population with physical distancing measures and various scenarios for isolation of index cases and tracing and quarantine of their contacts.

Findings

For the most optimistic scenario (testing and tracing delays of 0 days and tracing coverage of 100%), and assuming that around 40% of transmissions occur before symptom onset, the model predicts that the estimated effective reproduction number of 1·2 (with physical distancing only) will be reduced to 0·8 (95% CI 0·7–0·9) by adding contact tracing. The model also shows that a similar reduction can be achieved when testing and tracing coverage is reduced to 80% (R_CTS 0·8, 95% CI 0·7–1·0). A testing delay of more than 1 day requires the tracing delay to be at most 1 day or tracing coverage to be at least 80% to keep R_CTS below 1. With a testing delay of 3 days or longer, even the most efficient strategy cannot reach R_CTS values below 1. The effect of minimising tracing delay (eg, with app-based technology) declines with decreasing coverage of app use, but app-based tracing alone remains more effective than conventional tracing alone even with 20% coverage, reducing the reproduction number by 17·6% compared with 2·5%. The proportion of onward transmissions per index case that can be prevented depends on testing and tracing delays, and given a 0-day tracing delay, ranges from up to 79·9% with a 0-day testing delay to 41·8% with a 3-day testing delay and 4·9% with a 7-day testing delay.

Interpretation

In our model, minimising testing delay had the largest impact on reducing onward transmissions. Optimising testing and tracing coverage and minimising tracing delays, for instance with app-based technology, further enhanced contact tracing effectiveness, with the potential to prevent up to 80% of all transmissions. Access to testing should therefore be optimised, and mobile app technology might reduce delays in the contact tracing process and optimise contact tracing coverage.

Funding

ZonMw, Fundação para a Ciência e a Tecnologia, and EU Horizon 2020 RECOVER.