Estimating the potential need and impact of SARS-CoV-2 test-and-treat programs with oral antivirals in low-and-middle-income countries (preprint)

Oral antivirals can potentially reduce the burden of COVID-19. However, low SARS-CoV-2 clinical testing rates in many low- and middle-income countries (LMICs) (mean <10 tests/100,000 people/day, July 2022) makes the development of effective test- and-treat programs challenging. Here, we used an agent-based model to investigate how testing rates and strategies could affect development of test- and-treat programs in three representative LMICs. We find that at <10 tests/100,000 people/day, test- and-treat programs are unlikely to have any impact on the public health burden of COVID-19. At low effective transmission rates ( R t ≤ 1.2), increasing to 100 tests/100,000 people/day and allowing uncapped distribution of antivirals to LMICs (estimate = 26,000,000-90,000,000 courses/year for all LMICs), could avert up to 65% of severe cases, particularly in countries with older populations. For higher R t , significant reductions in severe cases are only possible by substantially increasing testing rates or restricting clinical testing to those with higher risk of severe disease.

Low testing rates limit the ability of genomic surveillance programs to monitor SARS-CoV-2 variants: a mathematical modelling study (preprint)

Background Genomic surveillance is essential for monitoring the emergence and spread of SARS-CoV-2 variants. SARS-CoV-2 diagnostic testing is the starting point for SARS-CoV-2 genomic sequencing. However, testing rates in many low- and middle-income countries (LMICs) are low (mean = 27 tests/100,000 people/day) and global testing rates are falling in the post-crisis phase of the pandemic, leading to spatiotemporal biases in sample collection. Various public health agencies and academic groups have produced recommendations on sample sizes and sequencing strategies for effective genomic surveillance. However, these recommendations assume very high volumes of diagnostic testing that are currently well beyond reach in most LMICs. Methods To investigate how testing rates, sequencing strategies and the degree of spatiotemporal bias in sample collection impact variant detection and monitoring outcomes, we used an individual-based model to simulate COVID-19 epidemics in a prototypical LMIC. Within the model, we simulated a range of testing rates, accounted for likely testing demand and applied various genomic surveillance strategies, including sentinel surveillance. Findings Diagnostic testing rates play a substantially larger role in monitoring the prevalence and emergence of new variants than the proportion of samples sequenced. To enable timely detection and monitoring of emerging variants, programs should achieve average testing rates of at least 100 tests/100,000 people/day and sequence 5-10% of test-positive specimens, which may be accomplished through sentinel or other routine surveillance systems. Under realistic assumptions, this averages to ~10 samples for sequencing/1,000,000 people/week. Interpretation For countries where testing capacities are low and sample collection is spatiotemporally biased, surveillance programs should prioritize investments in wider access to diagnostic testing to enable more representative sampling, ahead of simply increasing quantities of sequenced samples. Funding European Research Council, the Rockefeller Foundation, and the Governments of Germany, Canada, UK, Australia, Norway, Saudi Arabia, Kuwait, Netherlands and Portugal.

Accuracy of rapid point-of-care antigen-based diagnostics for SARS-CoV-2: an updated systematic review and meta-analysis with meta regression analyzing influencing factors (preprint)

BackgroundComprehensive information about the accuracy of antigen rapid diagnostic tests (Ag-RDTs) for SARS-CoV-2 is essential to guide public health decision makers in choosing the best tests and testing policies. In August 2021, we published a systematic review and meta-analysis about the accuracy of Ag-RDTs. We now update this work and analyze the factors influencing test sensitivity in further detail. Methods and findingsWe registered the review on PROSPERO (registration number: CRD42020225140). We systematically searched multiple databases (PubMed, Web of Science Core Collection, medRvix, bioRvix, and FIND) for publications evaluating the accuracy of Ag-RDTs for SARS-CoV-2 until August 31, 2021. Descriptive analyses of all studies were performed, and when more than 4 studies were available, a random-effects meta-analysis was used to estimate pooled sensitivity and specificity with reverse transcription polymerase chain reaction (RT-PCR) testing as a reference. To evaluate factors influencing test sensitivity, we performed 3 different analyses using multivariate mixed-effects meta-regression models. We included 194 studies with 221,878 Ag-RDTs performed. Overall, the pooled estimates of Ag-RDT sensitivity and specificity were 72.0% (95% confidence interval [CI] 69.8 to 74.2) and 98.9% (95% CI 98.6 to 99.1), respectively. When manufacturer instructions were followed, sensitivity increased to 76.4% (95%CI 73.8 to 78.8). Sensitivity was markedly better on samples with lower RT-PCR cycle threshold (Ct) values (sensitivity of 97.9% [95% CI 96.9 to 98.9] and 90.6% [95% CI 88.3 to 93.0] for Ct-values <20 and <25, compared to 54.4% [95% CI 47.3 to 61.5] and 18.7% [95% CI 13.9 to 23.4] for Ct-values [≥]25 and [≥]30) and was estimated to increase by 2.9 percentage points (95% CI 1.7 to 4.0) for every unit decrease in mean Ct-value when adjusting for testing procedure and patients symptom status. Concordantly, we found the mean Ct-value to be lower for true positive (22.2 [95% CI 21.5 to 22.8]) compared to false negative (30.4 [95% CI 29.7 to 31.1]) results. Testing in the first week from symptom onset resulted in substantially higher sensitivity (81.9% [95% CI 77.7 to 85.5]) compared to testing after 1 week (51.8%, 95% CI 41.5 to 61.9). Similarly, sensitivity was higher in symptomatic (76.2% [95% CI 73.3 to 78.9]) compared to asymptomatic (56.8% [95% CI 50.9 to 62.4]) persons. However, both effects were mainly driven by the Ct-value of the sample. With regards to sample type, highest sensitivity was found for nasopharyngeal (NP) and combined NP/oropharyngeal samples (70.8% [95% CI 68.3 to 73.2]), as well as in anterior nasal/mid-turbinate samples (77.3% [95% CI 73.0 to 81.0]). ConclusionAg-RDTs detect most of the individuals infected with SARS-CoV-2, and almost all when high viral loads are present (>90%). With viral load, as estimated by Ct-value, being the most influential factor on their sensitivity, they are especially useful to detect persons with high viral load who are most likely to transmit the virus. To further quantify the effects of other factors influencing test sensitivity, standardization of clinical accuracy studies and access to patient level Ct-values and duration of symptoms are needed.

SARS-CoV-2 Testing Strategies for Outbreak Mitigation in Vaccinated Populations (preprint)

Although COVID-19 vaccines are globally available, waning immunity and emerging vaccine-evasive variants of concern have hindered the international response as COVID-19 cases continue to rise. Mitigating COVID-19 requires testing to identify and isolate infectious individuals. We developed a stochastic compartmentalized model to simulate SARS-CoV-2 spread in the United States and India using Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) assays, rapid antigen tests, and vaccinations. We detail the optimal testing frequency and coverage in the US and India to mitigate an emerging outbreak even in a vaccinated population: overall, maximizing frequency is more important, but high coverage remains necessary when there is sustained transmission. We show that a resource-limited vaccination strategy still requires high-frequency testing and is 16.50% more effective in India than the United States. Tailoring testing strategies to transmission settings can help effectively reduce cases more than if a uniform approach is employed without regard to differences in location.

Use cases for COVID-19 screening and surveillance with rapid antigen-detecting tests: a systematic review (preprint)

Introduction: Testing is critical to controlling the COVID-19 pandemic. Antigen-detecting rapid diagnostic tests (Ag-RDTs) that can be used at the point of care have the potential to increase access to COVID 19 testing, particularly in settings with limited laboratory capacity. This systematic review synthesized literature on specific use cases and performance of Ag RDTs for detecting SARS-CoV-2, for the first comprehensive assessment of Ag RDT use in real-world settings. Methods: We searched three databases (PubMed, EMBASE and medRxiv) up to 12 April 2021 for publications on Ag-RDT use for large-scale screening,irrespective of symptoms, and surveillance of COVID-19, excluding studies of only presumptive COVID-19 patients. We tabulated data on the study setting, populations, type of test, diagnostic performance and operational findings. We assessed risk of bias using QUADAS-2 and an adapted tool for prevalence studies. Results: From 4313 citations, 39 studies conducted in asymptomatic and symptomatic adults were included. Study sample sizes varied from 40 to >5 million. Of 39 studies, 37 (94.9%) investigated lateral flow Ag-RDTs and two (5.1%) investigated multiplex sandwich chemiluminescent enzyme immunoassay Ag-RDTs. Six categories of testing (screening/surveillance) initiatives were identified: mass screening (n=13), targeted screening (n=11), healthcare entry testing (n=6), at-home testing (n=4), surveillance (n=4) and prevalence survey (n=1). Across studies, Ag-RDT sensitivity varied from 40% to 100%. Ag-RDTs were noted as convenient, easy-to-use and low cost, with a rapid turnaround time and high user acceptability. Risk of bias was generally low or unclear across the studies. Conclusion: This systematic review demonstrates the use of Ag-RDTs across a wide range of real-world settings for screening and surveillance of COVID-19 in both symptomatic and asymptomatic individuals. Ag-RDTs were overall found to be easy-to-use, low cost and rapid tools, when consideration is given to their implementation and interpretation. The review was funded by FIND, the global alliance for diagnostics.

Optimal use of COVID19 Ag-RDT screening at border crossings to prevent community transmission: a modeling analysis (preprint)

Background Countries around the world have implemented restrictions on mobility, especially cross-border travel to reduce or prevent SARS-CoV-2 community transmission. Rapid antigen testing (Ag-RDT), with on-site administration and rapid turnaround time may provide a valuable screening measure to ease cross-border travel while minimizing risk of local transmission. To maximize impact, we developed an optimal Ag-RDT screening algorithm for cross-border entry. Methods Using a previously developed mathematical model, we determined the daily number of imported COVID-19 cases that would generate no more than a relative 1% increase in cases over one month for different effective reproductive numbers (Rt) of the recipient country. We then developed an algorithm- for differing levels of Rt, arrivals per day, mode of travel, and SARS-CoV-2 prevalence amongst travelers- to determine the minimum proportion of people that would need Ag-RDT testing at border crossings to ensure no greater than the relative 1% community spread increase. Findings When daily international arrivals and/or COVID-19 prevalence amongst arrivals increases, the proportion of arrivals required to test using Ag-RDT increases. At very high numbers of international arrivals/COVID-19 prevalence, Ag-RDT testing is not sufficient to prevent increased community spread, especially for lower levels of Rt. In these cases, Ag-RDT screening would need to be supplemented with other measures to prevent an increase in community transmission. Interpretation An efficient Ag-RDT algorithm for SARS-CoV-2 testing depends strongly on Rt, volume of travel, proportion of land and air arrivals, test sensitivity, and COVID-19 prevalence among travelers. Funding USAID, Government of the Netherlands

Quantifying Rapid Antigen Diagnostic Resource Requirements for SARS-CoV-2: A Cost-Effectiveness Analysis of Testing Strategies for Five Countries in Sub-Saharan Africa (preprint)

Background: Molecular testing (PCR) is the recommended method for the diagnosis of coronavirus disease 19 (COVID-19). In low-resource settings (LRS), the availability and public health impact of these tests is constrained. Despite lower sensitivity, antigen detection rapid diagnostic tests (Ag-RDTs) could provide improved access at lower costs and quicker turnaround-time (TAT). We evaluated the optimal use of Ag-RDTs to increase testing access within TAT and reduce the cost and the number of cases missed in LRS.  Methods: We modeled estimated COVID-19 testing demand coverage based on current PCR capacity in three different epidemic phases across five African countries. We then modelled five additional testing strategies that utilized a combination of PCR and Ag-RDT.  For each strategy, epidemic phase and country, we estimated the total number of correct test results expected within a 48hr-TAT, the number of positive cases missed, corresponding costs ($12/PCR, $6/Ag-RDT), and the incremental cost-effectiveness ratios.  Findings: Across all countries and phase of epidemic, there was insufficient PCR capacity to meet the calculated required testing demand. The strategy limited to current PCR capacity was not considered cost-effective. Saturating testing demand with Ag-RDT was considered robustly cost-effective in every epidemic phase ($5-$7/additional person with a correct test result within 48hr-TAT and $50-$1000/additional case missed averted)  Interpretation: Inclusion of Ag-RDT in testing strategies is cost-effective and critical in increasing timely testing access in countries with low PCR capacity.  Funding: Supported by the Government of the Netherlands in the context of the ACT-Accelerator and USAID. Declaration of Interest: None to declare.

The accuracy of novel antigen rapid diagnostics for SARS-CoV-2: a living systematic review and meta-analysis (preprint)

ABSTRACT Background SARS-CoV-2 antigen rapid diagnostic tests (Ag-RDTs) are increasingly being integrated in testing strategies around the world. Studies of the Ag-RDTs have shown variable performance. In this systematic review and meta-analysis, we assessed the clinical accuracy (sensitivity and specificity) of commercially available Ag-RDTs. Methods and Results We registered the review on PROSPERO (Registration number: CRD42020225140). We systematically searched multiple databases (PubMed, Web of Science Core Collection, medRvix and bioRvix, FIND) for publications evaluating the accuracy of Ag-RDTs for SARS-CoV-2 up until April 30 th , 2021. Descriptive analyses of all studies were performed and when more than four studies were available, a random-effects meta-analysis was used to estimate pooled sensitivity and specificity in comparison to reverse transcriptase polymerase chain reaction testing. We assessed heterogeneity by subgroup analyses, and rated study quality and risk of bias using the QUADAS 2 assessment tool. From a total of 14,254 articles, we included 133 analytical and clinical studies resulting in 214 clinical accuracy data sets with 112,323 samples. Across all meta-analyzed samples, the pooled Ag-RDT sensitivity was 71.2% (95% confidence interval [CI] 68.2 to 74.0) and increased to 76.3% (CI 73.1 to 79.2) if analysis was restricted to studies that followed the Ag-RDT manufacturers’ instructions. The LumiraDx showed the highest sensitivity with 88.2% (CI 59.0 to 97.5). Of instrument-free Ag-RDTs, Standard Q nasal performed best with 80.2% sensitivity (CI 70.3 to 87.4). Across all Ag-RDTs sensitivity was markedly better on samples with lower Ct-values, i.e., <20 (96.5%, CI 92.6 to 98.4) and <25 (95.8%, CI 92.3 to 97.8), in comparison to those with Ct ≥25 (50.7%, CI 35.6 to 65.8) and ≥30 (20.9%, CI 12.5 to 32.8). Testing in the first week from symptom onset resulted in substantially higher sensitivity (83.8%, CI 76.3 to 89.2) compared to testing after one week (61.5%, CI 52.2 to 70.0). The best Ag-RDT sensitivity was found with anterior nasal sampling (75.5%, CI 70.4 to 79.9) in comparison to other sample types (e.g., nasopharyngeal 71.6%, CI 68.1 to 74.9) although CIs were overlapping. Concerns of bias were raised across all data sets, and financial support from the manufacturer was reported in 24.1% of data sets. Our analysis was limited by the included studies’ heterogeneity in design and reporting, making it difficult to draw conclusions from. Conclusion In this study we found that Ag-RDTs detect the vast majority of cases within the first week of symptom onset and those with high viral load. Thus, they can have high utility for diagnostic purposes in the early phase of disease, making them a valuable tool to fight the spread of SARS-CoV-2. Standardization in conduct and reporting of clinical accuracy studies would improve comparability and use of data. AUTHOR SUMMARY Why was this study done? – Antigen rapid diagnostic tests (Ag-RDTs) are considered an important diagnostic tool to fight the spread of SARS-CoV-2 – An increasing number of Ag-RDTs is offered on the market, and a constantly growing body of literature evaluating their performance is available – To inform decision makers about the best test to choose, an up to date summary of their performance is needed What did the researchers do and find? – On a weekly basis, we search multiple data bases for evaluations of Ag-RDTs detecting SARS-CoV-2 and post the results on www.diagnosticsglobalhealth.org – Based on the search results up until April 30 th , 2021, we conducted a systematic review and meta-analysis, including a total of 133 clinical and analytical accuracy studies – Across all meta-analyzed studies, when Ag-RDTs were performed according to manufacturers’ recommendations, they showed a sensitivity of 76.3% (CI 73.1 to 79.2), with the LumiraDx (sensitivity 88.2%, CI 59.0 to 97.5) and of the instrument-free Ag-RDT Standard Q (74.9% sensitivity, CI 69.3 to 79.7) performing best. – Across all Ag-RDTs, sensitivity increased to 95.8% (CI 92.3 to 97.8) when restricting the analysis to samples with high viral loads (i.e., a Ct-value <25) and to 83.8% (CI 76.3 to 89.2) when tests were performed on patients within the first week after symptom onset What do these findings mean? – Ag-RDTs detect the vast majority of cases within the first week of symptom onset and those with high viral load. Thus, they can have high utility for diagnostic purposes in the early phase of disease – Out of all assessed tests, the Lumira Dx showed the highest accuracy. The Standard Q wasthe best performing test when only considering those that don’t require an instrument – A standardization of reporting methods for clinical accuracy studies would enhance future test-comparisons