Rapid and Flexible RT-qPCR Surveillance Platforms To Detect SARS-CoV-2 Mutations.

Multiple mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) increase transmission, disease severity, and immune evasion and facilitate zoonotic or anthropozoonotic infections. Four such mutations, ΔH69/V70, L452R, E484K, and N501Y, occurred in the SARS-CoV-2 spike glycoprotein in combinations that allow the simultaneous detection of VOCs. Here, we present two flexible reverse transcription-quantitative PCR (RT-qPCR) platforms for small- and large-scale screening (also known as variant PCR) to detect these mutations and schemes for adapting the platforms to future mutations. The large-scale RT-qPCR platform was validated by pairwise matching of RT-qPCR results with whole-genome sequencing (WGS) consensus genomes, showing high specificity and sensitivity. Both platforms are valuable examples of complementing WGS to support the rapid detection of VOCs. Our mutational signature approach served as an important intervention measure for the Danish public health system to detect and delay the emergence of new VOCs. IMPORTANCE Denmark weathered the SARS-CoV-2 crisis with relatively low rates of infection and death. Intensive testing strategies with the aim of detecting SARS-CoV-2 in symptomatic and nonsymptomatic individuals were available by establishing a national test system called TestCenter Denmark. This testing regime included the detection of SARS-CoV-2 signature mutations, with referral to the national health system, thereby delaying outbreaks of variants of concern. Our study describes the design of the large-scale RT-qPCR platform established at TestCenter Denmark in conjunction with whole-genome sequencing to report mutations of concern to the national health system. Validation of the large-scale RT-qPCR platform using paired WGS consensus genomes showed high sensitivity and specificity. For smaller laboratories with limited infrastructure, we developed a flexible small-scale RT-qPCR platform to detect three signature mutations in a single run. The RT-qPCR platforms are important tools to support the control of the SARS-CoV-2 endemic in Denmark.

A Large-Scale Screening Responding Sporadic Epidemic of COVID-19 in China by an Integrated Health-Care System.

Introduction: In the post-pandemic period of COVID-19, the majority of cities in China try to balance the normalization of epidemic prevention and social-economic development. However, the appearance of asymptomatic infected patients poses threats to public health, which might be infectious without clinical symptoms and only be detected by testing approaches. Methods: Along with the appearance of one symptomatic case, a regional large-scale screening program was carried out in Shenzhen City charged by a regionally integrated healthcare system. After describing the screening program, a retrospective cross-sectional study for the screening outcome and efficacy was conducted. Discussion: According to the screening results, the asymptomatic case was infectious and their close contacts should be quarantined cautiously as the close contacts of symptomatic cases. Besides, after integrating medical resources in Luohu district of Shenzhen, the medical capability of Luohu district improved greatly which could be demonstrated in inspection and organization abilities in this screening program. Conclusion: The large-scale screening contributed to preventing epidemic transmission. In the post-pandemic period, regular surveillance of asymptomatic cases and rapid response capability for emergent screening program are both crucial for the prevention and control of COVID-19 epidemic. The integrated healthcare system coordinating regional medical institutions and optimizing regional medical recourse has advantages to address public health emergencies.

Real-world Evaluation of a Sample Pooling Strategy for Large-Scale Rapid COVID-19 Testing.

BACKGROUND: The worldwide outbreak of COVID-19 has become a public health crisis of unprecedented proportions. The fast spread of emerging variants increases the needs of rapid diagnostic and screening testing. Sample pooling efficiently expands the testing capacity under limited resources. OBJECTIVES: We evaluated the performance of sample pooling on the Point-of-Care (POC) Liat® and cobas® 6800 systems and provided real-world experiences for implementing these systems in large-scale screenings. METHODS: Positive nasopharyngeal (NP) specimens with Ct values < 25, 25∼30 or > 30 were tested individually and in pools to optimize the POC Liat® and cobas® 6800 systems, which were then implemented in community screenings. RESULTS: The 5-sample pooling strategy did not affect the positive detection rates on Liat® or cobas® 6800 in samples with Ct values <25 or 25∼30. However, in samples with low viral loads (Ct values >30), five-sample pooling has a higher positive detection rate on POC Liat® (20/20; 100%), compared to cobas® 6800 (9/20; 45%). Five-sample pooled on POC Liat® and two-sample pooled on cobas® 6800 appear to be appropriate for SARS-CoV-2 detection. By implementing the pooling strategies in two large-scale community screenings, 7,606 NP specimens was tested within 36 h; the average turn-around time was 4.8 h for cobas® 6800 and 1.3 h for POC Liat®. Eight positive specimens (0.11%; 8/7,606) were identified, with Ct values ranging from 18.85 to 37.68. CONCLUSION: The performance of sample pooling on POC Liat® was demonstrated to be an effective, accurate, and economical approach for large-scale community screenings for COVID-19.

Kloman Metre: An EMD-Based Tool for Triaging Diseases Leading to Lung Infections Including COVID-19

The digital revolution can help developing countries to overcome the problem of limited healthcare infrastructure in developing nations such as India. The COVID-19 pandemic has shown the urgency of integration of digital technologies into healthcare infrastructure. In order to solve the issue of lack of trained healthcare professionals at public health centres (PHCs), researchers are trying to build tools which can help to tag pulmonary ailment within a fraction of second. Such tagging will help the medical community to utilize their time more efficiently. In this work, we have tried to assess the “lung health” of patients suffering from a variety of pulmonary diseases including COVID-19, tuberculosis and pneumonia by applying Earth Mover’s Distance algorithm to the X-ray images of the patients. The lung X-ray images of patients suffering from pneumonia, TB and COVID-19 and healthy persons are pooled together from various datasets. Our preliminary data based upon 100 random images depicting each type of lung disease such as COVID-19, tuberculosis and pneumonia revealed that patients suffering from tuberculosis have the highest severity as per the values obtained from the EMD scale. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.