Viral dynamics and duration of PCR positivity of the SARS-CoV-2 Omicron variant

Background. The Omicron SARS-CoV-2 variant is responsible for a major wave of COVID-19, with record case counts reflecting high transmissibility and escape from prior immunity. Defining the time course of Omicron viral proliferation and clearance is crucial to inform isolation protocols aiming to minimize disease spread. Methods. We obtained longitudinal, quantitative RT-qPCR test results using combined anterior nares and oropharyngeal samples (n = 10,324) collected between July 5th, 2021 and January 10th, 2022 from the National Basketball Association's (NBA) occupational health program. We quantified the fraction of tests with PCR cycle threshold (Ct) values <30, chosen as a proxy for potential infectivity and antigen test positivity, on each day after first detection of suspected and confirmed Omicron infections, stratified by individuals detected under frequent testing protocols and those detected due to symptom onset or concern for contact with an infected individual. We quantified the duration of viral proliferation, clearance rate, and peak viral concentration for individuals with acute Omicron and Delta variant SARS-CoV-2 infections. Results. A total of 97 infections were confirmed or suspected to be from the Omicron variant and 107 from the Delta variant. Of 27 Omicron-infected individuals testing positive ≤1 day after a previous negative or inconclusive test, 52.0% (13/25) were PCR positive with Ct values <30 at day 5, 25.0% (6/24) at day 6, and 13.0% (3/23) on day 7 post detection. Of 70 Omicron-infected individuals detected ≥2 days after a previous negative or inconclusive test, 39.1% (25/64) were PCR positive with Ct values <30 at day 5, 33.3% (21/63) at day 6, and 22.2% (14/63) on day 7 post detection. Overall, Omicron infections featured a mean duration of 9.87 days (95% CI 8.83-10.9) relative to 10.9 days (95% CI 9.41-12.4) for Delta infections. The peak viral RNA based on Ct values was lower for Omicron infections than for Delta infections (Ct 23.3, 95% CI 22.4-24.3 for Omicron; Ct 20.5, 95% CI 19.2-21.8 for Delta) and the clearance phase was shorter for Omicron infections (5.35 days, 95% CI 4.78-6.00 for Omicron; 6.23 days, 95% CI 5.43-7.17 for Delta), though the rate of clearance was similar (3.13 Ct/day, 95% CI 2.75-3.54 for Omicron; 3.15 Ct/day, 95% CI 2.69-3.64 for Delta). Conclusions. While Omicron infections feature lower peak viral RNA and a shorter clearance phase than Delta infections on average, it is unclear to what extent these differences are attributable to more immunity in this largely vaccinated population or intrinsic characteristics of the Omicron variant. Further, these results suggest that Omicron's infectiousness may not be explained by higher viral load measured in the nose and mouth by RT-PCR. The substantial fraction of individuals with Ct values <30 at days 5 of infection, particularly in those detected due to symptom onset or concern for contact with an infected individual, underscores the heterogeneity of the infectious period, with implications for isolation policies.

Pooled testing efficiency increases with test frequency

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around x. However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

A Retrospective Outbreak Investigation of a COVID-19 Case Cluster in a Berlin Kindergarten, November 2020

While SARS-CoV-2 infection activity in German kindergartens during the first year of the pandemic appeared to be overall low, outbreaks did occur. We retrospectively investigated an outbreak in November and December 2020 in a Berlin kindergarten participating in the Berlin Corona School and Kindergarten Study (BECOSS). Interviews were conducted with affected families regarding symptomatology, contact persons and possible sources of infection, as well as relevant information on the conditions on-site and infection prevention measures. A chronology of the outbreak was elaborated, and based on data on contacts and symptoms, we mapped the most likely chains of infection. Overall, 24 individuals, including ten educators, seven children, and seven household members, were infected with SARS-CoV-2 in a four-week time interval. Courses of infection ranged from asymptomatic to severe, with children less affected by symptoms. Viral spread within the facility seemed to occur mainly through kindergarten staff, while children primarily transmitted infections within their families. Interviewees reported that hygiene measures were not always adhered to inside the facility. To prevent outbreaks in kindergartens, especially in the light of current and newly emerging viral variants of concern, strict compliance to hygiene rules, staff vaccinations against SARS-CoV-2, and immediate reaction to suspected cases by quarantining and frequent testing seem reasonable measures.

Effect of Frequent Testing on Students’ Test Anxiety at University Level

This study was designed to find out the effect of frequent Testing on students’ test anxiety scores in research method course at university level. The study was expected to predict the worry and emotional factor scores of test anxiety on frequent testing. A quasi-experimental pre-test post-test control group design was used in this study. Two intact groups were selected from department of science education, University of the Punjab, Lahore. The researcher has adopted the test anxiety Inventory by Spielberger (1980) to find out the students’ test anxiety. The reliability was analyzed through the pilot testing of the instrument. The interventional group was manipulated by frequent testing. The control group was assessed by conventional method. Both groups were compared on test anxiety scores. After analyzing the data, it was observed that both groups experience the same test anxiety in regard to worry and emotional factor. Frequent testing did not effect the test anxiety of students in research method course. Stakeholders and evaluators will benefit from the information gathered on how to lessen test anxiety in order to improve the teaching-learning process in classroom. To strengthen the teaching and learning process in classrooms, it is necessary to increase confidence in prospective teachers.

COVID-19 testing systems and their effectiveness in small, semi-isolated groups for sports events

In this study, we quantitatively assessed the effectiveness of systems for COVID-19 testing in small groups of sport teams that are semi-isolated from the general population by countermeasures against infection. Two types of group were assumed, and the dynamics of infection within each group was modeled by using a compartment model of infectious disease. One group (Group A) comprised domestic professional sports teams that play many games over a season while remaining within a relatively small region. Polymerase chain reaction (PCR) tests were routinely conducted once every 2 weeks, and the number of infected individuals that could not be removed after identification by testing or checking for symptoms was defined as the risk. The other group (Group B) comprised teams that travel across borders for mass-gathering events like the Olympic and Paralympic Games. The teams were isolated for 2 weeks at their destination; frequent testing and checking for symptoms was conducted, and any infected individuals were removed. The number of infected individuals participating in games after the isolation period was defined as the risk. In Group A, the number of infected individuals detected by routinely conducted PCR testing was lower than the number of infected individuals detected by checking for symptoms, indicating that routine testing every 2 weeks was not very effective. In Group B, daily PCR testing was the most effective, followed by daily antigen testing. Dual testing, in which individuals with a positive antigen test were given an additional PCR test, was the least effective with an effect equal to PCR testing every other day. These results indicate that repeated testing does not necessarily increase the detection of infected individuals.

A Value-of-Information Framework for Personalizing the Timing of Surveillance Testing

Background Patient surveillance using repeated biomarker measurements presents an opportunity to detect and treat disease progression early. Frequent surveillance testing using biomarkers is recommended and routinely conducted in several diseases, including cancer and diabetes. However, frequent testing involves tradeoffs. Although surveillance tests provide information about current disease status, the complications and costs of frequent tests may not be justified for patients who are at low risk of progression. Predictions based on patients’ earlier biomarker values may be used to inform decision making; however, predictions are uncertain, leading to decision uncertainty. Methods We propose the Personalized Risk-Adaptive Surveillance (PRAISE) framework, a novel method for embedding predictions into a value-of-information (VOI) framework to account for the cost of uncertainty over time and determine the time point at which collection of biomarker data would be most valuable. The proposed sequential decision-making framework is innovative in that it leverages the patient’s longitudinal history, considers individual benefits and harms, and allows for dynamic tailoring of surveillance intervals by considering the uncertainty in current information and estimating the probability that new information may change treatment decisions, as well as the impact of this change on patient outcomes. Results When applied to data from cystic fibrosis patients, PRAISE lowers costs by allowing some patients to skip a visit, compared to an “always test” strategy. It does so without compromising expected survival, by recommending less frequent testing among those who are unlikely to be treated at the skipped time point. Conclusions A VOI-based approach to patient monitoring is feasible and could be applied to several diseases to develop more cost-effective and personalized strategies for ongoing patient care. Highlights In many patient-monitoring settings, the complications and costs of frequent tests are not justified for patients who are at low risk of disease progression. Predictions based on patient history may be used to individualize the timing of patient visits based on evolving risk. We propose Personalized Risk-Adaptive Surveillance (PRAISE), a novel method for personalizing the timing of surveillance testing, where prediction modeling projects the disease trajectory and a value-of-information (VOI)–based pragmatic decision-theoretic framework quantifies patient- and time-specific benefit-harm tradeoffs. A VOI-based approach to patient monitoring could be applied to several diseases to develop more personalized and cost-effective strategies for ongoing patient care.

Modeling the influence of vaccine administration on COVID-19 testing strategies

Vaccination is considered the best strategy for limiting and eliminating the COVID-19 pandemic. The success of this strategy relies on the rate of vaccine deployment and acceptance across the globe. As these efforts are being conducted, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is continuously mutating, which leads to the emergence of variants with increased transmissibility, virulence, and lower response the vaccines. One important question is whether surveillance testing is still needed in order to limit SARS-CoV-2 transmission in an increasingly vaccinated population. In this study, we developed a multi-scale mathematical model of SARS-CoV-2 transmission in a vaccinated population and used it to predict the role of testing in an outbreak with alpha and delta variants. We found that, when the alpha variant is dominant, testing is effective when vaccination levels are low to moderate and its impact is diminished when vaccination levels are high. When the delta variant is dominant, widespread vaccination is necessary in order to prevent significant outbreaks. When only moderate vaccination can be achieved, frequent testing can significantly reduce the cumulative size of delta variant outbreak, with the impact of testing having maximum effects when focused on the non-vaccinated population.

Concordance between PCR-based extraction-free saliva and nasopharyngeal swabs for SARS-CoV-2 testing

Introduction: Saliva represents a less invasive alternative to nasopharyngeal swab (NPS) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection. SalivaDirect is a nucleic acid extraction-free method for detecting SARS-CoV2 in saliva specimens. Studies evaluating the concordance of gold standard NPS and newly developed SalivaDirect protocols are limited. The aim of our study was to assess SalivaDirect as an alternative method for COVID-19 testing. Methods: Matching NPS and saliva samples were analysed from a cohort of symptomatic (n=127) and asymptomatic (n=181) participants recruited from hospital and university settings, respectively. RNA was extracted from NPS while saliva samples were subjected to the SalivaDirect protocol before RT-qPCR analysis. The presence of SARS-Cov-2 was assessed using RdRp and N1 gene targets in NPS and saliva, respectively. Results: Overall we observed 94.3% sensitivity (95% CI 87.2-97.5%), and 95.9% specificity (95% CI 92.4-97.8%) in saliva when compared to matching NPS samples. Analysis of concordance demonstrated 95.5% accuracy overall for the saliva test relative to NPS, and a very high level of agreement (κ coefficient = 0.889, 95% CI 0.833–0.946) between the two sets of specimens. Fourteen of 308 samples were discordant, all from symptomatic patients. Ct values were >30 in 13/14 and >35 in 6/14 samples. No significant difference was found in the Ct values of matching NPS and saliva sample (p=0.860). A highly significant correlation (r = 0.475, p<0.0001) was also found between the Ct values of the concordant positive saliva and NPS specimens. Conclusions: Use of saliva processed according to the SalivaDirect protocol represents a valid method to detect SARS-CoV-2. Accurate and less invasive saliva screening is an attractive alternative to current testing methods based on NPS and would afford greater capacity to test asymptomatic populations especially in the context of frequent testing.

WHotLAMP: A simple, inexpensive, and sensitive molecular test for the detection of SARS-CoV-2 in saliva

Despite the development of effective vaccines against SARS-CoV-2, epidemiological control of the virus is still challenging due to slow vaccine rollouts, incomplete vaccine protection to current and emerging variants, and unwillingness to get vaccinated. Therefore, frequent testing of individuals to identify early SARS-CoV-2 infections, contact-tracing and isolation strategies remain crucial to mitigate viral spread. Here, we describe WHotLAMP, a rapid molecular test to detect SARS-CoV-2 in saliva. WHotLAMP is simple to use, highly sensitive (~4 viral particles per microliter of saliva) and specific, as well as inexpensive, making it ideal for frequent screening. Moreover, WHotLAMP does not require toxic chemicals or specialized equipment and thus can be performed in point-of-care settings, and may also be adapted for resource-limited environments or home use. While applied here to SARS-CoV-2, WHotLAMP can be modified to detect other pathogens, making it adaptable for other diagnostic assays, including for use in future outbreaks.

Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing

The rapid identification and isolation of infected individuals remains a key strategy for controlling the spread of SARS-CoV-2. Frequent testing of populations to detect infection early in asymptomatic or presymptomatic individuals can be a powerful tool for intercepting transmission, especially when the viral prevalence is low. However, RT-PCR testing—the gold standard of SARS-CoV-2 diagnosis—is expensive, making regular testing of every individual unfeasible. Sample pooling is one approach to lowering costs. By combining samples and testing them in groups the number of tests required is reduced, substantially lowering costs. Here we report on the implementation of pooling strategies using 3-d and 4-d hypercubes to test a professional sports team in South Africa. We have shown that infected samples can be reliably detected in groups of 27 and 81, with minimal loss of assay sensitivity for samples with individual Ct values of up to 32. We report on the automation of sample pooling, using a liquid-handling robot and an automated web interface to identify positive samples. We conclude that hypercube pooling allows for the reliable RT-PCR detection of SARS-CoV-2 infection, at significantly lower costs than lateral flow antigen (LFA) tests.