Molecular diagnostic technologies for COVID-19: Limitations and challenges

A Rapid Label-Free Disposable Electrochemical Salivary Point-of-Care Sensor for SARS-CoV-2 Detection and Quantification

The coronavirus disease 2019 (COVID-19) pandemic has created an urgent need for accurate early diagnosis and monitoring. A label-free rapid electrochemical point-of-care (POC) biosensor for SARS-CoV-2 detection in human saliva is reported here to help address the shortcomings of traditional nucleic acid amplification methods and give a quantitative assessment of the viral load to track infection status anywhere, using disposable electrochemical sensor chips. A new chemical construct of gold nanoparticles (GNp) and thionine (Th) are immobilized on carboxylic acid functionalized carbon nanotubes (SWCNT-COOH) for high-performance biosensing. The sensor uses saliva with a one-step pretreatment and simple testing procedure as an analytical medium due to the user-friendly and non-invasive nature of its procurement from patients. The sensor has a response time of 5 min with a limit of detection (LOD) reaching 200 and 500 pM for the freely suspended spike (S) protein in phosphate buffer saline (PBS) and human saliva, respectively. The sensor's performance was also proven for detecting a COVID-19 pseudovirus in an electrolyte solution with a LOD of 10⁶ copies/mL. The results demonstrate that the optimized POC sensor developed in this work is a promising device for the label-free electrochemical biosensing detection of SARS-CoV-2 and different species of viruses.

Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen-antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.

Novel reverse transcription-multiple inner primer loop-mediated isothermal amplification (RT-MIPLAMP) for visual and sensitive detection of SARS-CoV-2

Since the end of 2019, outbreaks of COVID-19 pandemics have continued in different areas worldwide, which exacerbates the need for rapid, sensitive and simple methods for diagnosis. Currently, COVID-19 diagnosis mainly relies on reverse transcription-polymerase chain reaction (RT-PCR), which requires sophisticated instruments. Reverse transcription-loop mediated isothermal amplification (RT-LAMP), due to its isothermal nature and high specificity, can be used as an alternative. In this paper, a novel visual reverse transcription-multiple inner primer loop-mediated isothermal amplification (RT-MIPLAMP) method is established based on RT-LAMP by adding a pair of inner primers. The RT-MIPLAMP method has a higher sensitivity and shorter reaction time compared with conventional RT-LAMP. By using RT-MIPLAMP, as low as 6 × 10³ copies per mL in vitro transcribed (IVT) N gene can be detected within 55 min. Meanwhile, as low as 6 × 10⁴ copies per mL IVT N gene is detectable with conventional RT-LAMP within 80 min. The feasibility of visual RT-MIPLAMP is also validated by detecting the N gene spiked into one healthy volunteer's saliva and the full-length RNA in pseudoviruses, indicating the great potential of visual RT-MIPLAMP for SARS-CoV-2 identification.

Wastewater surveillance allows early detection of SARS-CoV-2 omicron in North Rhine-Westphalia, Germany

Wastewater-based epidemiology (WBE) has demonstrated its importance to support SARS-CoV-2 epidemiology complementing individual testing strategies. Due to their immune-evasive potential and the resulting significance for public health, close monitoring of SARS-CoV-2 variants of concern (VoC) is required to evaluate the regulation of early local countermeasures. In this study, we demonstrate a rapid workflow for wastewater-based early detection and monitoring of the newly emerging SARS-CoV-2 VoCs Omicron in the end of 2021 at the municipal wastewater treatment plant (WWTP) Emschermuendung (KLEM) in the Federal State of North-Rhine-Westphalia (NRW, Germany). Initially, available primers detecting Omicron-related mutations were rapidly validated in a central laboratory. Subsequently, RT-qPCR analysis of purified SARS-CoV-2 RNA was performed in a decentral PCR laboratory in close proximity to KLEM. This decentralized approach enabled the early detection of K417N present in Omicron in samples collected on 8th December 2021 and the detection of further mutations (N501Y, Δ69/70) in subsequent biweekly sampling campaigns. The presence of Omicron in wastewater was confirmed by next generation sequencing (NGS) in a central laboratory with samples obtained on 14th December 2021. Moreover, the relative increase of the mutant fraction of Omicron was quantitatively monitored over time by dPCR in a central PCR laboratory starting on 12th December 2021 confirming Omicron as the dominant variant by the end of 2021. In conclusions, WBE plays a crucial role in surveillance of SARS-CoV-2 variants and is suitable as an early warning system to identify variant emergence. In particular, the successive workflow using RT-qPCR, RT-dPCR and NGS demonstrates the strength of WBE as a versatile tool to monitor variant spreading.

Infección natural por SARS-CoV-2 en gatos y perros domésticos de personas con diagnóstico de COVID-19 en el Valle de Aburrá, Antioquia

Introducción. El síndrome respiratorio agudo grave causado por el nuevo coronavirus SARSCoV-2 es causa de la emergencia sanitaria por la pandemia de COVID-19. Si bien el humano es el el principal huésped vulnerable, en estudios experimentales y reportes de infección natural, se han encontrado casos de zoonosis inversa de SARS-CoV-2 en animales.Objetivo. Evaluar la infección natural por SARS-CoV-2 en gatos y perros de propietarios con diagnóstico de COVID-19 en el Valle de Aburrá, Antioquia, Colombia.Materiales y métodos. La circulación del SARS-CoV-2 se evaluó por RT-qPCR y RT-PCR en muestras de frotis nasofaríngeos y orofaríngeos de gatos y perros cuyos propietarios se encontraban dentro del periodo de los 14 días de aislamiento. Los casos positivos se verificaron amplificando fragmentos de los genes RdRp, N y E; se secuenció el gen RdRp y se analizó filogenéticamente.Resultados. De 80 animales evaluados, seis gatos y tres perros fueron casos confirmados de infección natural por SARS-CoV-2. Los animales no presentaron signos clínicos y sus propietarios, que padecían la infección, reportaron únicamente signos leves de la enfermedad sin complicaciones clínicas. En el análisis de una de las secuencias, se encontró un polimorfismo de un solo nucleótido (SNP) con un cambio en la posición 647, con sustitución del aminoácido serina (S) por una isoleucina (I). Los casos se presentaron en los municipios de Caldas, Medellín y Envigado.Conclusiones. Se infiere que la infección natural en los gatos y perros se asocia al contacto directo con un paciente con COVID-19. No obstante, no es posible determinar la virulencia del virus en este huésped, ni su capacidad de transmisión  zoonótica o entre especie.

Development and Clinical Validation of RT-LAMP-Based Lateral-Flow Devices and Electrochemical Sensor for Detecting Multigene Targets in SARS-CoV-2

Consistently emerging variants and the life-threatening consequences of SARS-CoV-2 have prompted worldwide concern about human health, necessitating rapid and accurate point-of-care diagnostics to limit the spread of COVID-19. Still, However, the availability of such diagnostics for COVID-19 remains a major rate-limiting factor in containing the outbreaks. Apart from the conventional reverse transcription polymerase chain reaction, loop-mediated isothermal amplification-based (LAMP) assays have emerged as rapid and efficient systems to detect COVID-19. The present study aims to develop RT-LAMP-based assay system for detecting multiple targets in N, ORF1ab, E, and S genes of the SARS-CoV-2 genome, where the end-products were quantified using spectrophotometry, paper-based lateral-flow devices, and electrochemical sensors. The spectrophotometric method shows a LOD of 10 agµL−1 for N, ORF1ab, E genes and 100 agµL−1 for S gene in SARS-CoV-2. The developed lateral-flow devices showed an LOD of 10 agµL−1 for all four gene targets in SARS-CoV-2. An electrochemical sensor developed for N-gene showed an LOD and E-strip sensitivity of log 1.79 ± 0.427 pgµL−1 and log 0.067 µA/pg µL−1/mm2, respectively. The developed assay systems were validated with the clinical samples from COVID-19 outbreaks in 2020 and 2021. This multigene target approach can effectively detect emerging COVID-19 variants using combination of various analytical techniques at testing facilities and in point-of-care settings.

Indirect Virus Transmission via Fomites Can Counteract Lock-Down Effectiveness

The spread of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has raised major health policy questions. Direct transmission via respiratory droplets seems to be the dominant route of its transmission. However, indirect transmission via shared contact of contaminated objects may also occur. The contribution of each transmission route to epidemic spread might change during lock-down scenarios. Here, we simulate viral spread of an abstract epidemic considering both routes of transmission by use of a stochastic, agent-based SEIR model. We show that efficient contact tracing (CT) at a high level of incidence can stabilize daily cases independently of the transmission route long before effects of herd immunity become relevant. CT efficacy depends on the fraction of cases that do not show symptoms. Combining CT with lock-down scenarios that reduce agent mobility lowers the incidence for exclusive direct transmission scenarios and can even eradicate the epidemic. However, even for small fractions of indirect transmission, such lockdowns can impede CT efficacy and increase case numbers. These counterproductive effects can be reduced by applying measures that favor distancing over reduced mobility. In summary, we show that the efficacy of lock-downs depends on the transmission route. Our results point to the particular importance of hygiene measures during mobility lock-downs.

Point-of-care CRISPR/Cas biosensing technology: A promising tool for preventing the possible COVID-19 resurgence caused by contaminated cold-chain food and packaging

The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused great public health concern and has been a global threat due to its high transmissibility and morbidity. Although the SARS-CoV-2 transmission mainly relies on the person-to-person route through the respiratory droplets, the possible transmission through the contaminated cold-chain food and packaging to humans has raised widespread concerns. This review discussed the possibility of SARS-CoV-2 transmission via the contaminated cold-chain food and packaging by tracing the occurrence, the survival of SARS-CoV-2 in the contaminated cold-chain food and packaging, as well as the transmission and outbreaks related to the contaminated cold-chain food and packaging. Rapid, accurate, and reliable diagnostics of SARS-CoV-2 is of great importance for preventing and controlling the COVID-19 resurgence. Therefore, we summarized the recent advances on the emerging clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system-based biosensing technology that is promising and powerful for preventing the possible COVID-19 resurgence caused by the contaminated cold-chain food and packaging during the COVID-19 pandemic, including CRISPR/Cas system-based biosensors and their integration with portable devices (e.g., smartphone, lateral flow assays, microfluidic chips, and nanopores). Impressively, this review not only provided an insight on the possibility of SARS-CoV-2 transmission through the food supply chain, but also proposed the future opportunities and challenges on the development of CRISPR/Cas system-based detection methods for the diagnosis of SARS-CoV-2.

Rapid and quantitative detection of respiratory viruses using surface-enhanced Raman spectroscopy and machine learning

Rapid and sensitive pathogen detection is important for prevention and control of disease. Here, we report a label-free diagnostic platform that combines surface-enhanced Raman scattering (SERS) and machine learning for the rapid and accurate detection of thirteen respiratory virus species including SARS-CoV-2, common human coronaviruses, influenza viruses, and others. Virus detection and measurement have been performed using highly sensitive SiO₂ coated silver nanorod array substrates, allowing for detection and identification of their characteristic SERS peaks. Using appropriate spectral processing procedures and machine learning algorithms (MLAs) including support vector machine (SVM), k-nearest neighbor, and random forest, the virus species as well as strains and variants have been differentiated and classified and a differentiation accuracy of >99% has been obtained. Utilizing SVM-based regression, quantitative calibration curves have been constructed to accurately estimate the unknown virus concentrations in buffer and saliva. This study shows that using a combination of SERS, MLA, and regression, it is possible to classify and quantify the virus in saliva, which could aid medical diagnosis and therapeutic intervention.

A pandemic guided by the SARS-CoV-2 PCR test: What should the clinician know?

Amidst an ever-evolving pandemic, the demand for timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) continues to increase. Critically, managing and containing the spread of the disease requires expedient testing of infected individuals. Presently, the gold standard for the diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains the polymerase chain reaction (PCR) test. Potential vulnerabilities of this testing methodology can range from preanalytical variables to laboratory-related analytical factors and, ultimately, to the interpretation of results.

Simplifying the complex: accessible microfluidic solutions for contemporary processes within in vitro diagnostics

In vitro diagnostics (IVDs) form the cornerstone of modern medicine. They are routinely employed throughout the entire treatment pathway, from initial diagnosis through to prognosis, treatment planning, and post-treatment surveillance. Given the proven links between high quality diagnostic testing and overall health, ensuring broad access to IVDs has long been a focus of both researchers and medical professionals. Unfortunately, the current diagnostic paradigm relies heavily on centralized laboratories, complex and expensive equipment, and highly trained personnel. It is commonly assumed that this level of complexity is required to achieve the performance necessary for sensitive and specific disease diagnosis, and that making something affordable and accessible entails significant compromises in test performance. However, recent work in the field of microfluidics is challenging this notion. By exploiting the unique features of microfluidic systems, researchers have been able to create progressively simple devices that can perform increasingly complex diagnostic assays. This review details how microfluidic technologies are disrupting the status quo, and facilitating the development of simple, affordable, and accessible integrated IVDs. Importantly, we discuss the advantages and limitations of various approaches, and highlight the remaining challenges within the field.

Early Detection of SARS-CoV-2 Omicron BA.4 and BA.5 in German Wastewater

Wastewater-based SARS-CoV-2 epidemiology (WBE) has been established as an important tool to support individual testing strategies. The Omicron sub-variants BA.4/BA.5 have spread globally, displacing the preceding variants. Due to the severe transmissibility and immune escape potential of BA.4/BA.5, early monitoring was required to assess and implement countermeasures in time. In this study, we monitored the prevalence of SARS-CoV-2 BA.4/BA.5 at six municipal wastewater treatment plants (WWTPs) in the Federal State of North Rhine-Westphalia (NRW, Germany) in May and June 2022. Initially, L452R-specific primers/probes originally designed for SARS-CoV-2 Delta detection were validated using inactivated authentic viruses and evaluated for their suitability for detecting BA.4/BA.5. Subsequently, the assay was used for RT-qPCR analysis of RNA purified from wastewater obtained twice a week at six WWTPs. The occurrence of L452R carrying RNA was detected in early May 2022, and the presence of BA.4/BA.5 was confirmed by variant-specific single nucleotide polymorphism PCR (SNP-PCR) targeting E484A/F486V and NGS sequencing. Finally, the mutant fractions were quantitatively monitored by digital PCR, confirming BA.4/BA.5 as the majority variant by 5 June 2022. In conclusion, the successive workflow using RT-qPCR, variant-specific SNP-PCR, and RT-dPCR demonstrates the strength of WBE as a versatile tool to rapidly monitor variants spreading independently of individual test capacities.

Update on the limited sensitivity of computed tomography relative to RT-PCR for COVID-19: a systematic review

Purpose

The global and ongoing COVID-19 outbreak has compelled the need for timely and reliable methods of detection for SARS-CoV-2 infection. Although reverse transcription-polymerase chain reaction (RT-PCR) has been widely accepted as a reference standard for COVID-19 diagnosis, several early studies have suggested the superior sensitivity of computed tomography (CT) in identifying SARS-CoV-2 infection. In a previous systematic review, we stratified studies based on risk for bias to evaluate the true sensitivity of CT for detecting SARS-CoV-2 infection. This study revisits our prior analysis, incorporating more current data to assess the sensitivity of CT for COVID-19.

Material and methods

The PubMed and Google Scholar databases were searched for relevant articles published between 1 January 2020, and 25 April 2021. Exclusion criteria included lack of specification regarding whether the study cohort was adult or paediatric, whether patients were symptomatic or asymptomatic, and not identifying the source of RT-PCR specimens. Ultimately, 62 studies were included for systematic review and were subsequently stratified by risk for bias using the QUADAS-2 quality assessment tool. Sensitivity data were extracted for random effects meta-analyses.

Results

The average sensitivity for COVID-19 reported by the high-risk-of-bias studies was 68% [CI: 58, 80; range: 38-96%] for RT-PCR and 91% [CI: 87, 96; range: 47-100%] for CT. The average sensitivity reported by the low-risk-of-bias studies was 84% [CI: 0.75, 0.94; range: 70-97%] for RT-PCR and 78% [CI: 71, 0.86; range: 44-92%] for CT.

Conclusions

On average, the high-risk-of bias studies underestimated the sensitivity of RT-PCR and overestimated the sensitivity of CT for COVID-19. Given the incorporation of recently published low-risk-of-bias articles, the sensitivities according to low-risk-of-bias studies for both RT-PCR and CT were higher than previously reported.

Fluorescence spectrophotometry for COVID-19 determination in clinical swab samples

Considering the limitations of the assays currently available for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its emerging variants, a simple and rapid method using fluorescence spectrophotometry was developed to detect coronavirus disease 2019 (COVID-19). Forty clinical swab samples were collected from the nasopharyngeal and oropharyngeal cavities of COVID-19-positive and -negative. Each sample was divided into two parts. The first part of the samples was analyzed using reverse transcription-polymerase chain reaction (RT-qPCR) as the control method to identify COVID-19-positive and -negative samples. The second part of the samples was analyzed using fluorescence spectrophotometry. Fluorescence measurements were performed at excitation and emission wavelengths ranging from 200 to 800 nm. Twenty COVID-19-positive samples and twenty COVID-19-negative samples were detected based on RT-qPCR results. The fluorescence spectrum data indicated that the COVID-19-positive and -negative samples had significantly different characteristics. All positive samples could be distinguished from negative samples by fluorescence spectrophotometry. Principal component analysis showed that COVID-19-positive samples were clustered separately from COVID-19-negative samples. The specificity and accuracy of this experiment reached 100%. Limit of detection (LOD) obtained 42.20 copies/ml (Ct value of 33.65 cycles) for E gene and 63.60 copies/ml (Ct value of 31.36 cycles) for ORF1ab gene. This identification process only required 4 min. Thus, this technique offers an efficient and accurate method to identify an individual with active SARS-CoV-2 infection and can be easily adapted for the early investigation of COVID-19, in general.

CXGNet: A tri-phase chest X-ray image classification for COVID-19 diagnosis using deep CNN with enhanced grey-wolf optimizer

The coronavirus disease 2019 (COVID-19) epidemic had a significant impact on daily life in many nations and global public health. COVID's quick spread has become one of the biggest disruptive calamities in the world. In the fight against COVID-19, it's critical to keep a close eye on the initial stage of infection in patients. Furthermore, early COVID-19 discovery by precise diagnosis, especially in patients with no evident symptoms, may reduce the patient's death rate and can stop the spread of COVID-19. When compared to CT images, chest X-ray (CXR) images are now widely employed for COVID-19 diagnosis since CXR images contain more robust features of the lung. Furthermore, radiologists can easily diagnose CXR images because of its operating speed and low cost, and it is promising for emergency situations and therapy. This work proposes a tri-stage CXR image based COVID-19 classification model using deep learning convolutional neural networks (DLCNN) with an optimal feature selection technique named as enhanced grey-wolf optimizer with genetic algorithm (EGWO-GA), which is denoted as CXGNet. The proposed CXGNet is implemented as multiple classes, such as 4-class, 3-class, and 2-class models based on the diseases. Extensive simulation outcome discloses the superiority of the proposed CXGNet model with enhanced classification accuracy of 94.00% for the 4-class model, 97.05% of accuracy for the 3-class model, and 100% accuracy for the 2-class model as compared to conventional methods.

The CRISPR-Cas system as a tool for diagnosing and treating infectious diseases

Emerging and relapsing infectious diseases pose a huge health threat to human health and a new challenge to global public health. Rapid, sensitive and simple diagnostic tools are keys to successful management of infectious patients and containment of disease transmission. In recent years, international research on Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-related proteins (Cas) has revolutionized our understanding of biology. The CRISPR-Cas system has the advantages of high specificity, high sensitivity, simple, rapid, low cost, and has begun to be used for molecular diagnosis and treatment of infectious diseases. In this paper, we described the biological principles, application fields and prospects of CRISPR-Cas system in the molecular diagnosis and treatment of infectious diseases, and compared it with existing molecular diagnosis methods, the advantages and disadvantages were summarized.

SARS-CoV-2 serological assay and viral testing: a report of professional football setting

PURPOSE OF THE STUDY

PCR is the current standard test for the diagnosis of SARS-CoV-2 infection. However, due to its limitations, serological testing is considered an alternative method for detecting SARS-CoV-2 exposure. In this study, we measured the level of SARS-CoV-2 IgM and IgG antibodies of male professional football players and compared the results with the standard PCR test to investigate the association between the two tests.

STUDY DESIGN

Participants were male professional football players and team officials. Nasopharyngeal swabs and peripheral blood samples were collected for the PCR and serological tests, respectively. Also, previous records of COVID-19 testing and symptoms were gathered. Those with previous positive PCR tests who tested negative for the second time were considered to be recovered patients.

RESULTS

Of the 1243 subjects, 222 (17.9%) were seropositive, while 29 (2.3%) tested positive for the SARS-CoV-2 PCR test. Sixty percent of symptomatic cases with a negative PCR were found to be seropositive. The mean level of IgM was significantly higher in PCR-positive and symptomatic subjects, whereas the recovered cases showed significantly higher levels of IgG.

CONCLUSION

Our study revealed an inconsistency of results between the two tests; therefore, although application of serological assays alone seems insufficient in diagnosing COVID-19 disease, the findings are beneficial in the comprehension and the management of the disease.

Transfer Learning for Automated COVID-19 B-Line Classification in Lung Ultrasound

Lung ultrasound (LUS) as a diagnostic tool is gaining support for its role in the diagnosis and management of COVID-19 and a number of other lung pathologies. B-lines are a predominant feature in COVID-19, however LUS requires a skilled clinician to interpret findings. To facilitate the interpretation, our main objective was to develop automated methods to classify B-lines as pathologic vs. normal. We developed transfer learning models based on ResNet networks to classify B-lines as pathologic (at least 3 B-lines per lung field) vs. normal using COVID-19 LUS data. Assessment of B-line severity on a 0-4 multi-class scale was also explored. For binary B-line classification, at the frame-level, all ResNet models pretrained with ImageNet yielded higher performance than the baseline nonpretrained ResNet-18. Pretrained ResNet-18 has the best Equal Error Rate (EER) of 9.1% vs the baseline of 11.9%. At the clip-level, all pretrained network models resulted in better Cohen's kappa agreement (linear-weighted) and clip score accuracy, with the pretrained ResNet-18 having the best Cohen's kappa of 0.815 [95% CI: 0.804-0.826], and ResNet-101 the best clip scoring accuracy of 93.6%. Similar results were shown for multi-class scoring, where pretrained network models outperformed the baseline model. A class activation map is also presented to guide clinicians in interpreting LUS findings. Future work aims to further improve the multi-class assessment for severity of B-lines with a more diverse LUS dataset.

Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has been characterized by the emergence of sets of mutations impacting the virus characteristics, such as transmissibility and antigenicity, presumably in response to the changing immune profile of the human population. The presence of mutations in the SARS-CoV-2 virus can potentially impact therapeutic and diagnostic test performances. We design and develop here a unique set of DNA probes i.e., antisense oligonucleotides (ASOs) which can interact with genetic sequences of the virus irrespective of its ongoing mutations. The probes, developed herein, target a specific segment of the nucleocapsid phosphoprotein (N) gene of SARS-CoV-2 with high binding efficiency which do not mutate among the known variants. Further probing into the interaction profile of the ASOs reveals that the ASO-RNA hybridization remains unaltered even for a hypothetical single point mutation at the target RNA site and diminished only in case of the hypothetical double or triple point mutations. The mechanism of interaction among the ASOs and SARS-CoV-2 RNA is then explored with a combination of surface-enhanced Raman scattering (SERS) and machine learning techniques. It has been observed that the technique, described herein, could efficiently discriminate between clinically positive and negative samples with ∼100% sensitivity and ∼90% specificity up to 63 copies/mL of SARS-CoV-2 RNA concentration. Thus, this study establishes N gene targeted ASOs as the fundamental machinery to efficiently detect all the current SARS-CoV-2 variants regardless of their mutations.

A Regional Pooling Intervention in a High-Throughput COVID-19 Diagnostic Laboratory to Enhance Throughput, Save Resources and Time Over a Period of 6 Months

An effective and rapid diagnosis has great importance in tackling the ongoing COVID-19 pandemic through isolation of the infected individuals to curb the transmission and initiation of specialized treatment for the disease. It has been proven that enhanced testing capacities contribute to efficiently curbing SARS-CoV-2 transmission during the initial phases of the outbreaks. RT-qPCR is considered a gold standard for the diagnosis of COVID-19. However, in resource-limited countries expenses for molecular diagnosis limits the diagnostic capacities. Here, we present interventions of two pooling strategies as 5 sample pooling (P-5) and 10 sample pooling (P-10) in a high-throughput COVID-19 diagnostic laboratory to enhance throughput and save resources and time over a period of 6 months. The diagnostic capacity was scaled-up 2.15-folds in P-5 and 1.8-fold in P-10, reagents (toward RNA extraction and RT-qPCR) were preserved at 75.24% in P-5 and 86.21% in P-10, and time saved was 6,290.93 h in P-5 and 3147.3 h in P-10.

A Review on SARS-CoV-2 Genome in the Aquatic Environment of Africa: Prevalence, Persistence and the Future Prospects

The COVID-19 pandemic (Coronavirus disease 2019) remains problematic in all its manifestations on the global stage where countless events of human-to-human exposure have led to fatal cases; thus, the aftermath being an unprecedented public health concern, with inaccessible health care and the instability of economies and financial institutions. These pose massive obstacles that can insatiably devour existing human resources causing negative impacts, especially in developing countries. Tracking the origin, dissemination and mutating strains of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) on population-wide scales is a somewhat overwhelming task, with the urgent need to map the dissemination and magnitude of SARS-CoV-2 in near real-time. This review paper focuses on the poor sanitation of some waterbodies and wastewater management policies in low-income African countries, highlighting how these contribute to the COVID-19 pandemic on the continent. Since the outbreak of the novel coronavirus pandemic, there has been an upsurge in scientific literature and studies concerning SARS-CoV-2 with different opinions and findings. The current paper highlights the challenges and also summarizes the environmental aspects related to the monitoring and fate of the SARS-CoV-2 genomes in the aquatic milieu of Sub-Saharan Africa.

Performance differences among commercially available antigen rapid tests for COVID-19 in Brazil

A rapid and accurate diagnosis is a crucial strategy for containing the coronavirus disease (COVID-19) pandemic. Considering the obstacles to upscaling the use of RT–qPCR, rapid tests based on antigen detection (Ag-RDT) have become an alternative to enhance mass testing, reducing the time for a prompt diagnosis and virus spreading. However, the performances of several commercially available Ag-RDTs have not yet been evaluated in several countries. Here, we evaluate the performance of eight Ag-RDTs available in Brazil to diagnose COVID-19. Patients admitted to tertiary hospitals with moderate or mild COVID-19 symptoms and presenting risk factors for severe disease were included. The tests were performed using a masked protocol, strictly following the manufacturer’s recommendations and were compared with RT–qPCR. The overall sensitivity of the tests ranged from 9.8 to 81.1%, and specificity greater than 83% was observed for all the evaluated tests. Overall, slight or fair agreement was observed between Ag-RDTs and RT–PCR, except for the Ag-RDT COVID-19 (Acro Biotech), in which moderate agreement was observed. Lower sensitivity of Ag-RDTs was observed for patients with cycle threshold > 25, indicating that the sensitivity was directly affected by viral load, whereas the effect of the disease duration was unclear. Despite the lower sensitivity of Ag-RDTs compared with RT–qPCR, its easy fulfillment and promptness still justify its use, even at hospital admission. However, the main advantage of Ag-RDTs seems to be the possibility of increasing access to the diagnosis of COVID-19 in patients with a high viral load, allowing immediate clinical management and reduction of infectivity and community transmission.

Molecular modifications, biological activities, and applications of chitosan and derivatives: A recent update

Polysaccharides arouse great interest due to their structure and unique properties, such as biocompatibility, biodegradability, and absence of toxicity. Polysaccharides from marine sources are particularly useful due to the wide variety of applications and biological activities. Chitosan, a deacetylated derivative of chitin, is an example of an interesting bioactive marine-derived polysaccharide. Moreover, a wide variety of chemical modifications and conjugation of chitosan with other bioactive molecules are responsible for improvements in physicochemical properties and biological activities, expanding the range of applications. An overview of the synthetic approaches for preparing chitosan, chitosan derivatives, and conjugates is described and discussed. A recent update of the biological activities and applications in different research fields, mainly focused on the last 5 years, is presented, highlighting current trends.

Risk factors for intensive care unit need in patients with COVID-19: An analysis of 368 cases

Objective: Covid-19 is a global epidemic that predominantly affects the respiratory system, in which about 20% of patients are severe and about 10-15% of mild cases become severe. The clinical and laboratory findings in the course of the disease are mild in the first week and may become more severe in the following days, also the possibility false negativity of the tomography in the first 24-48 hours, making it difficult to select patients in triage. Being able to detect cases that may have a serious course in the Covid-19 pandemic will help health systems to function without interruption. In our study, we tried to identify cases that may need intensive care in triage. Methods: Medical records and radiological findings of 368 patients with laboratory-confirmed Severe-Acute-Respiratory-Syndrome Coronavirus-2 infection who were hospitalized between March and June 2020 were reviewed. The patients were analyzed by dividing into two groups; group 1; critically ill patients with severe pneumonia who need intensive care during treatment. Approximately 8% of all patients are in this group. Group 2; non-critical patients who do not need intensive care followed in the clinic. Results: It was determined that the mean age of the patients in Group 1, the rate of being over 50 years old and the male gender ratio were higher than Group 2. Conclusion: Although there are low oxygen saturation, tachypnea and comorbid diseases in critically ill patients in triage, advanced age and male gender were found to be the most important risk factors for intensive care need.

Advancements in Testing Strategies for COVID-19

The SARS-CoV-2 coronavirus, also known as the disease-causing agent for COVID-19, is a virulent pathogen that may infect people and certain animals. The global spread of COVID-19 and its emerging variation necessitates the development of rapid, reliable, simple, and low-cost diagnostic tools. Many methodologies and devices have been developed for the highly sensitive, selective, cost-effective, and rapid diagnosis of COVID-19. This review organizes the diagnosis platforms into four groups: imaging, molecular-based detection, serological testing, and biosensors. Each platform's principle, advancement, utilization, and challenges for monitoring SARS-CoV-2 are discussed in detail. In addition, an overview of the impact of variants on detection, commercially available kits, and readout signal analysis has been presented. This review will expand our understanding of developing advanced diagnostic approaches to evolve into susceptible, precise, and reproducible technologies to combat any future outbreak.

SARS-CoV-2 Detection Methods

A fast and highly specific detection of COVID-19 infections is essential in managing the virus dissemination networks. The most relevant technologies developed for SARS-CoV-2 detection, along with their advantages and limitations, will be presented and fully explored. Additionally, some of the newest and emerging COVID-19 diagnosis tools, such as biosensing platforms, will also be introduced. Considering the extreme relevance that all these technologies assume in pandemic control, it is of the utmost relevance to have an intrinsic knowledge of the parameters that need to be taken into consideration before choosing the most adequate test for a particular situation. Moreover, the new variants of the virus and their potential impact on the detection method’s effectiveness will be discussed. In order to better manage the pandemic, it is essential to maintain continuous research into the SARS-CoV-2 genome and updated genomic surveillance at the global level. This will allow for timely detection of new mutations and viral variants, which may affect the performance of COVID-19 detection tests.

Advanced Molecular and Immunological Diagnostic Methods to Detect SARS-CoV-2 Infection

COVID-19 emerged in late 2019 in China and quickly spread across the globe, causing over 521 million cases of infection and 6.26 million deaths to date. After 2 years, numerous advances have been made. First of all, the preventive vaccine, which has been implemented in record time, is effective in more than 95% of cases. Additionally, in the diagnostic field, there are numerous molecular and antigenic diagnostic kits that are equipped with high sensitivity and specificity. Real Time-PCR-based assays for the detection of viral RNA are currently considered the gold-standard method for SARS-CoV-2 diagnosis and can be used efficiently on pooled nasopharyngeal, or oropharyngeal samples for widespread screening. Moreover, additional, and more advanced molecular methods such as droplet-digital PCR (ddPCR), clustered regularly interspaced short palindromic repeats (CRISPR) and next-generation sequencing (NGS), are currently under development to detect the SARS-CoV-2 RNA. However, as the number of subjects infected with SARS-CoV-2 continuously increases globally, health care systems are being placed under increased stress. Thus, the clinical laboratory plays an important role, helping to select especially asymptomatic individuals who are actively carrying the live replicating virus, with fast and non-invasive molecular technologies. Recent diagnostic strategies, other than molecular methods, have been adopted to either detect viral antigens, i.e., antigen-based immunoassays, or human anti-SARS-CoV-2 antibodies, i.e., antibody-based immunoassays, in nasal or oropharyngeal swabs, as well as in blood or saliva samples. However, the role of mucosal sIgAs, which are essential in the control of viruses entering the body through mucosal surfaces, remains to be elucidated, and in particular the role of the immune response in counteracting SARS-CoV-2 infection, primarily at the site(s) of virus entry that appears to be promising.

An all-in-one point-of-care testing device for multiplexed detection of respiratory infections

The impact of the COVID-19 pandemic has reinforced the need for rapid, cost-effective, and reliable point-of-care testing (POCT) devices for massive population screening. The co-circulation of SARS-CoV-2 with several seasonal respiratory viruses highlights the need for multiplexed biosensing approaches. Herein, we present a fast and robust all-in-one POCT device for parallel viral antigen and serological analysis. The biosensing approach consists of a functionalized polycarbonate disc-shaped surface with microfluidic structures, where specific bioreagents are immobilized in microarray format, and a portable optoelectronic analyzer. The biosensor quantifies the concentration of viral antigens and specific immunoglobulins G and M for SARS-CoV-2, influenza A/B, adenovirus, and respiratory syncytial virus, using 30 μL of a sample. The semi-automated analysis of 6 samples is performed in 30 min. Validation studies performed with 135 serum samples and 147 nasopharyngeal specimens reveal high diagnostic sensitivity (98–100%) and specificity (84–98%), achieving an excellent agreement (κ = 0.937) with commercial immunoassays, which complies with the World Health Organization criteria for POC COVID-19 diagnostic tests. The versatility of the POCT device paves the way for the detection of other pathogens and analytes in the incoming post-pandemic world, integrating specific bioreagents against different variants of concerns and interests.

Performance evaluation of STANDARD Q COVID-19 Ag home test for the diagnosis of COVID-19 during early symptom onset

BACKGROUND

Surveillance and control of SARS-CoV-2 outbreak through gold standard detection, that is, real-time polymerase chain reaction (RT-PCR), become a great obstacle, especially in overwhelming outbreaks. In this study, we aimed to analyze the performance of rapid antigen home test (RAHT) as an alternative detection method compared with RT-PCR.

METHODS

In total, 79 COVID-19-positive and 217 COVID-19-negative patients confirmed by RT-PCR were enrolled in this study. A duration from symptom onset to COVID-19 confirmation of <5 days was considered a recruiting criterion for COVID-19-positive cases. A nasal cavity specimen was collected for the RAHT, and a nasopharyngeal swab specimen was collected for RT-PCR.

RESULTS

Sensitivity of the STANDARD Q COVID-19 Ag Home Test (SD Biosensor, Korea), compared with RT-PCR, was 94.94% (75/79) (95% [confidence interval] CI, 87.54%-98.60%), and specificity was 100%. Sensitivity was significantly higher in symptomatic patients (98.00%) than in asymptomatic (89.66%) patients (p-value = 0.03). There was no difference in sensitivity according to the duration of symptom onset to confirmation (100% for 0-2 days and 96.97% for 3-5 days, respectively) (p-value = 1.00). The RAHT detected all 51 COVID-19 patients whose Ct values were ≤25 (100%), whereas sensitivity was 73.33% (11/15) among patients with Ct values >25 (p-value = 0.01).

CONCLUSION

The RAHT showed an excellent sensitivity for COVID-19-confirmed cases, especially for those with symptoms. There was a decrease in sensitivity when the Ct value is over 25, indicating that RAHT screening may be useful during the early phase of symptom onset, when the viral numbers are higher and it is more transmissible.

COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients

BACKGROUND

We aimed to analyze the prognostic power of CT-based radiomics models using data of 14,339 COVID-19 patients.

METHODS

Whole lung segmentations were performed automatically using a deep learning-based model to extract 107 intensity and texture radiomics features. We used four feature selection algorithms and seven classifiers. We evaluated the models using ten different splitting and cross-validation strategies, including non-harmonized and ComBat-harmonized datasets. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were reported.

RESULTS

In the test dataset (4,301) consisting of CT and/or RT-PCR positive cases, AUC, sensitivity, and specificity of 0.83 ± 0.01 (CI95%: 0.81-0.85), 0.81, and 0.72, respectively, were obtained by ANOVA feature selector + Random Forest (RF) classifier. Similar results were achieved in RT-PCR-only positive test sets (3,644). In ComBat harmonized dataset, Relief feature selector + RF classifier resulted in the highest performance of AUC, reaching 0.83 ± 0.01 (CI95%: 0.81-0.85), with a sensitivity and specificity of 0.77 and 0.74, respectively. ComBat harmonization did not depict statistically significant improvement compared to a non-harmonized dataset. In leave-one-center-out, the combination of ANOVA feature selector and RF classifier resulted in the highest performance.

CONCLUSION

Lung CT radiomics features can be used for robust prognostic modeling of COVID-19. The predictive power of the proposed CT radiomics model is more reliable when using a large multicentric heterogeneous dataset, and may be used prospectively in clinical setting to manage COVID-19 patients.

Molecular and antigen tests, and sample types for diagnosis of COVID-19: a review

Laboratory tests seeking to improve detection of COVID-19 have been widely developed by laboratories and commercial companies. This review provides an overview of molecular and antigen tests, presents the sensitivity and specificity for 329 assays that have received US FDA Emergency Use Authorization and evaluates six sample collection methods – nasal, nasopharyngeal, oropharyngeal swabs, saliva, blood and stool. Molecular testing is preferred for diagnosis of COVID-19, but negative results do not always rule out the presence of infection, especially when clinical suspicion is high. Sensitivity and specificity ranged from 88.1 to 100% and 88 to 100%, respectively. Antigen tests may be more easy to use and rapid. However, they have reported a wide range of detection sensitivities from 16.7 to 85%, which may potentially yield many false-negative results.

Respiratory etiological surveillance among quarantined patients with suspected lower respiratory tract infection at a medical center in southern Taiwan during COVID-19 pandemic

Background

A comprehensive study of respiratory pathogens was conducted in an area with a low prevalence of COVID-19 among the adults quarantined at a tertiary hospital.

Methods

From March to May 2020, 201 patients suspected lower respiratory tract infection (LRTI) were surveyed for etiologies by multiplex polymerase chain reaction (PCR: FilmArray TM Respiratory Panel) test combination with cultural method, viral antigen detection and serologic surveys.

Results

Total 201 patients tested with FilmArray TM Respiratory Panel were enrolled, of which 68.2% had sputum bacterial culture, 86.1% had pneumococcus and Legionella urine antigen test. Their median age was 72.0 year-old with multiple comorbidities, and 11.4% were nursing home residents. Bacteria accounted for 59.7% of identified pathogens. Atypical pathogens were identified in 31.3% of total pathogens, of which viruses accounted for 23.9%. In comparison to patients with bacterial infection, patients with atypical pathogens were younger (median= 77.2 vs 67.1, years, P = 0.017) and had shorter length of hospital (8.0 vs 4.5, days, P = 0.007).

Conclusions

Patients with LRTI caused by atypical pathogens was indistinguishable from those with bacterial pathogens by clinical manifestations or biomarkers. Multiplex PCR providing rapid diagnosis of atypical pathogens enhance patient care and decision making when rate of sputum culture sampling was low in quarantine ward during pandemic.

Use of Nanomaterials for Diagnosis and Treatment: The Advancement of Next-Generation Antiviral Therapy

Globally, viral illness propagation is the leading cause of morbidity and death, causing wreaking havoc on socioeconomic development and health care systems. The rise of infected individuals has outpaced the existing critical care facilities. Early and sophisticated methods are desperately required in this respect to halt the spread of the infection. Therefore, early detection of infectious agents and an early treatment approach may help minimize viral outbreaks. Conventional point-of-care diagnostic techniques such as computed tomography scan, quantitative real time polymerase chain reaction (qRT-PCR), X-ray, and immunoassay are still deemed valuable. However, the labor demanding, low sensitivity, and complex infrastructure needed for these methods preclude their use in distant areas. Nanotechnology has emerged as a potentially transformative technology due to its promise as an effective theranostic platform for diagnosing and treating viral infection, circumventing the limits of traditional techniques. Their unique physical and chemical characteristics make nanoparticles (NPs) advantageous for drug delivery platforms due to their size, encapsulation efficiency, improved bioavailability, effectiveness, immunogenicity, and antiviral response. This study discusses the recent research on nanotechnology-based treatments designed to combat new viruses.

Nanomaterials-assisted metabolic analysis toward in vitro diagnostics

In vitro diagnostics (IVD) has played an indispensable role in healthcare system by providing necessary information to indicate disease condition and guide therapeutic decision. Metabolic analysis can be the primary choice to facilitate the IVD since it characterizes the downstream metabolites and offers real-time feedback of the human body. Nanomaterials with well-designed composition and nanostructure have been developed for the construction of high-performance detection platforms toward metabolic analysis. Herein, we summarize the recent progress of nanomaterials-assisted metabolic analysis and the related applications in IVD. We first introduce the important role that nanomaterials play in metabolic analysis when coupled with different detection platforms, including electrochemical sensors, optical spectrometry, and mass spectrometry. We further highlight the nanomaterials-assisted metabolic analysis toward IVD applications, from the perspectives of both the targeted biomarker quantitation and untargeted fingerprint extraction. This review provides fundamental insights into the function of nanomaterials in metabolic analysis, thus facilitating the design of next-generation diagnostic devices in clinical practice.

Remote Floating-Gate Field-Effect Transistor with 2-Dimensional Reduced Graphene Oxide Sensing Layer for Reliable Detection of SARS-CoV-2 Spike Proteins

Despite intensive research of nanomaterials-based field-effect transistors (FETs) as a rapid diagnostic tool, it remains to be seen for FET sensors to be used for clinical applications due to a lack of stability, reliability, reproducibility, and scalability for mass production. Herein, we propose a remote floating-gate (RFG) FET configuration to eliminate device-to-device variations of two-dimensional reduced graphene oxide (rGO) sensing surfaces and most of the instability at the solution interface. Also, critical mechanistic factors behind the electrochemical instability of rGO such as severe drift and hysteresis were identified through extensive studies on rGO-solution interfaces varied by rGO thickness, coverage, and reduction temperature. rGO surfaces in our RFGFET structure displayed a Nernstian response of 54 mV/pH (from pH 2 to 11) with a 90% yield (9 samples out of total 10), coefficient of variation (CV) < 3%, and a low drift rate of 2%, all of which were calculated from the absolute measurement values. As proof-of-concept, we demonstrated highly reliable, reproducible, and label-free detection of spike proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a saliva-relevant media with concentrations ranging from 500 fg/mL to 5 μg/mL, with an R² value of 0.984 and CV < 3%, and a guaranteed limit of detection at a few pg/mL. Taken together, this new platform may have an immense effect on positioning FET bioelectronics in a clinical setting for detecting SARS-CoV-2.

Evaluation of Performance of Detection of Immunoglobulin G and Immunoglobulin M Antibody Against Spike Protein of SARS-CoV-2 by a Rapid Kit in a Real-Life Hospital Setting

Background

Antibody testing is often used for serosurveillance of coronavirus disease 2019 (COVID-19). Enzyme-linked immunosorbent assay and chemiluminescence-based antibody tests are quite sensitive and specific for such serological testing. Rapid antibody tests against different antigens are developed and effectively used for this purpose. However, their diagnostic efficiency, especially in real-life hospital setting, needs to be evaluated. Thus, the present study was conducted in a dedicated COVID-19 hospital in New Delhi, India, to evaluate the diagnostic efficacy of a rapid antibody kit against the receptor-binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Methods

Sixty COVID-19 confirmed cases by reverse transcriptase–polymerase chain reaction (RT-PCR) were recruited and categorized as early, intermediate, and late cases based on the days passed after their first RT-PCR–positive test report, with 20 subjects in each category. Twenty samples from pre-COVID era and 20 RT-PCR–negative collected during the study period were taken as controls. immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies against the RBD of the spike (S) protein of SARS-CoV-2 virus were detected by rapid antibody test and compared with the total antibody against the nucleocapsid (N) antigen of SARS-CoV-2 by electrochemiluminescence-based immunoassay (ECLIA).

Results

The detection of IgM against the RBD of the spike protein by rapid kit was less sensitive and less specific for the diagnosis of SARS-CoV-2 infection. However, diagnostic efficacy of IgG by rapid kit was highly sensitive and specific when compared with the total antibody against N antigen measured by ECLIA.

Conclusion

It can be concluded that detection of IgM against the RBD of S protein by rapid kit is less effective, but IgG detection can be used as an effective diagnostic tool for SARS-CoV-2 infection in real-life hospital setting.

Design, optimization, and application of multiplex rRT-PCR in the detection of respiratory viruses

Viral respiratory infections are common and serious diseases. Because there is no effective treatment method or vaccine for respiratory tract infection, early diagnosis is vital to identify the pathogen so as to determine the infectivity of the patient and to quickly take measures to curb the spread of the virus, if warranted, to avoid serious public health problems. Real-time reverse transcriptase PCR (rRT-PCR), which has high sensitivity and specificity, is the best approach for early diagnosis. Among rRT-PCR methods, multiplex rRT-PCR can resolve issues arising from various types of viruses, high mutation frequency, coinfection, and low concentrations of virus. However, the design, optimization, and validation of multiplex rRT-PCR are more complicated than singleplex rRT-PCR, and comprehensive research on multiplex rRT-PCR methodology is lacking. This review summarizes recent progress in multiplex rRT-PCR methodology, outlines the principles of design, optimization and validation, and describes a scheme to help diagnostic companies to design and optimize their multiplex rRT-PCR detection panel and to assist laboratory staff to solve problems in their daily work. In addition, the analytical validity, clinical validity and clinical utility of multiplex rRT-PCR in viral respiratory tract infection diagnosis are assessed to provide theoretical guidance and useful information for physicians to understand the test results.

Detection of SARS-CoV-2 by Canine Olfaction: A Pilot Study

Background

As the number of coronavirus disease 2019 (COVID-19) cases continue to surge worldwide and new variants emerge, additional accurate, rapid, and noninvasive screening methods to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed. The number of COVID-19 cases reported globally is >455 million, and deaths have surpassed 6 million. Current diagnostic methods are expensive, invasive, and produce delayed results. While COVID-19 vaccinations are proven to help slow the spread of infection and prevent serious illness, they are not equitably available worldwide. Almost 40% of the world’s population remains unvaccinated. Evidence suggests that SARS-CoV-2 virus–associated volatile organic compounds found in the breath, urine, and sweat of infected individuals can be detected by canine olfaction. Medical detection dogs may be a feasible, accurate, and affordable SARS-CoV-2 screening method.

Methods

In this double-blinded, case–control, validation study, we obtained sweat samples from inpatients and outpatients tested for SARS-CoV-2 by a polymerase chain reaction test. Medical detection dogs were trained to distinguish SARS-CoV-2-positive samples from SARS-CoV-2-negative samples using reward-based reinforcement.

Results

Samples were obtained from 584 individuals (6–97 years of age; 24% positive SARS-CoV-2 samples and 76% negative SARS-CoV-2 samples). In the testing phase, all dogs performed with high accuracy in detecting SARS-CoV-2. The overall diagnostic sensitivity was 98%, and specificity was 92%. In a follow-up phase, 1 dog screened 153 patients for SARS-CoV-2 in a hospital setting with 96% diagnostic sensitivity and 100% specificity.

Conclusions

Canine olfaction is an accurate and feasible method for diagnosis of SARS-CoV-2, including asymptomatic and presymptomatic infected individuals.

Validation and performance of a multiplex serology assay to quantify antibody responses following SARS-CoV-2 infection or vaccination

Objectives

Robust, quantitative serology assays are required to accurately measure antibody levels following vaccination and natural infection. We present validation of a quantitative, multiplex, SARS‐CoV‐2, electrochemiluminescent (ECL) serology assay; show correlation with two established SARS‐CoV‐2 immunoassays; and present calibration results for two SARS‐CoV‐2 reference standards.

Methods

Precision, dilutional linearity, ruggedness, analytical sensitivity and specificity were evaluated. Clinical sensitivity and specificity were assessed using serum from prepandemic and SARS‐CoV‐2 polymerase chain reaction (PCR)‐positive patient samples. Assay concordance to the established Roche Elecsys® Anti‐SARS‐CoV‐2 immunoassay and a live‐virus microneutralisation (MN) assay was evaluated.

Results

Standard curves demonstrated the assay can quantify SARS‐CoV‐2 antibody levels over a broad range. Assay precision (10.2−15.1% variability), dilutional linearity (≤ 1.16‐fold bias per 10‐fold increase in dilution), ruggedness (0.89−1.18 overall fold difference), relative accuracy (107−118%) and robust selectivity (102−104%) were demonstrated. Analytical sensitivity was 7, 13 and 7 arbitrary units mL⁻¹ for SARS‐CoV‐2 spike (S), receptor‐binding domain (RBD) and nucleocapsid (N) antigens, respectively. For all antigens, analytical specificity was > 90% and clinical specificity was 99.0%. Clinical sensitivities for S, RBD and N antigens were 100%, 98.8% and 84.9%, respectively. Comparison with the Elecsys® immunoassay showed ≥ 87.7% agreement and linear correlation (Pearson r of 0.85, P < 0.0001) relative to the MN assay. Conversion factors for the WHO International Standard and Meso Scale Discovery® Reference Standard are presented.

Conclusions

The multiplex SARS‐CoV‐2 ECL serology assay is suitable for efficient, reproducible measurement of antibodies to SARS‐CoV‐2 antigens in human sera, supporting its use in clinical trials and sero‐epidemiology studies.

An encodable multiplex microsphere-phase amplification sensing platform detects SARS-CoV-2 mutations

SARS-CoV-2 variants of concern (VOCs) contain several single-nucleotide variants (SNVs) at key sites in the receptor-binding region (RBD) that enhance infectivity and transmission, as well as cause immune escape, resulting in an aggravation of the coronavirus disease 2019 (COVID-19) pandemic. Emerging VOCs have sparked the need for a diagnostic method capable of simultaneously monitoring these SNVs. To date, no highly sensitive, efficient clinical tool exists to monitor SNVs simultaneously. Here, an encodable multiplex microsphere-phase amplification (MMPA) sensing platform that combines primer-coded microsphere technology with dual fluorescence decoding strategy to detect SARS-CoV-2 RNA and simultaneously identify 10 key SNVs in the RBD. MMPA limits the amplification refractory mutation system PCR (ARMS-PCR) reaction for specific target sequence to the surface of a microsphere with specific fluorescence coding. This effectively solves the problem of non-specific amplification among primers and probes in multiplex PCR. For signal detection, specific fluorescence codes inside microspheres are used to determine the corresponding relationship between the microspheres and the SNV sites, while the report probes hybridized with PCR products are used to detect the microsphere amplification intensity. The MMPA platform offers a lower SARS-CoV-2 RNA detection limit of 28 copies/reaction, the ability to detect a respiratory pathogen panel without cross-reactivity, and a SNV analysis accuracy level comparable to that of sequencing. Moreover, this super-multiple parallel SNVs detection method enables a timely updating of the panel of detected SNVs that accompanies changing VOCs, and presents a clinical availability that traditional sequencing methods do not.

Clinical Performance of the cobas Liat SARS-CoV-2 & Influenza A/B Assay in Nasal Samples

Background and Objective

Point-of-care type molecular diagnostic tests have been used for detecting SARS-CoV-2, although their clinical utility with nasal samples has yet to be established. This study evaluated the clinical performance of the cobas Liat SARS-CoV-2 & Influenza A/B (Liat) assay in nasal samples.

Methods

Nasal and nasopharyngeal samples were collected and were tested using the Liat, the cobas 6800 system and the cobas SARS-CoV-2 & Influenza A/B (cobas), and a method developed by National Institute of Infectious Diseases, Japan (NIID).

Results

A total of 814 nasal samples were collected. The Liat assay was positive for SARS-CoV-2 in 113 (13.9%). The total, positive, and negative concordance rate between the Liat and cobas/NIID assays were 99.3%/98.4%, 99.1%/100%, and 99.3%/98.2%, respectively. Five samples were positive only using the Liat assay. Their Ct values ranged from 31.9 to 37.2. The Ct values of the Liat assay were significantly lower (p < 0.001) but were correlated (p < 0.001) with those of other molecular assays. In the participants who tested positive for SARS-CoV-2 on the Liat assay using nasopharyngeal samples, 88.2% of their nasal samples also tested positive using the Liat assay.

Conclusion

The Liat assay showed high concordance with other molecular assays in nasal samples. Some discordance occurred in samples with Ct values > 30 on the Liat assay.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40291-022-00580-8.

Ultrasensitive assay for saliva-based SARS-CoV-2 antigen detection

OBJECTIVES

Widespread SARS-CoV-2 testing is invaluable for identifying asymptomatic/pre-symptomatic individuals. There remains a technological gap for highly reliable, easy, and quick SARS-CoV-2 diagnostic tests suitable for frequent mass testing. Compared to nasopharyngeal (NP) swab-based tests, saliva-based methods are attractive due to easier and safer sampling. Current saliva-based SARS-CoV-2 rapid antigen tests (RATs) are hindered by limited analytical sensitivity. Here, we report one of the first ultrasensitive, saliva-based SARS-CoV-2 antigen assays with an analytical sensitivity of <0.32 pg/mL, corresponding to four viral RNA copies/µL, which is comparable to that of PCR-based tests.

METHODS

Using the novel electrochemiluminescence (ECL)-based immunoassay, we measured the SARS-CoV-2 nucleocapsid (N) antigen concentration in 105 salivas, obtained from non-COVID-19 and COVID-19 patients. We then verified the results with a second, independent cohort of 689 patients (3.8% SARS-CoV-2 positivity rate). We also compared our method with a widely used point-of-care rapid test.

RESULTS

In the first cohort, at 100% specificity, the sensitivity was 92%. Our assay correctly identified samples with viral loads up to 35 CT cycles by saliva-based PCR. Paired NP swab-based PCR results were obtained for 86 cases. Our assay showed high concordance with saliva-based and NP swab-based PCR in samples with negative (<0.32 pg/mL) and strongly positive (>2 pg/mL) N antigen concentrations. In the second cohort, at 100% specificity, sensitivity was also 92%. Our assay is about 700-fold more sensitive than the Abbott Panbio Rapid Test.

CONCLUSIONS

We demonstrated the ultrasensitivity and specificity assay and its concordance with PCR. This novel assay is especially valuable when compliance to frequent swabbing may be problematic.

Diagnostic Accuracy of Rapid Antigen Tests for COVID-19 Detection: A Systematic Review With Meta-analysis

Introduction

Reverse transcription-polymerase chain reaction (RT-PCR) to detect SARS-CoV-2 is time-consuming and sometimes not feasible in developing nations. Rapid antigen test (RAT) could decrease the load of diagnosis. However, the efficacy of RAT is yet to be investigated comprehensively. Thus, the current systematic review and meta-analysis were conducted to evaluate the diagnostic accuracy of RAT against RT-PCR methods as the reference standard.

Methods

We searched the MEDLINE/Pubmed and Embase databases for the relevant records. The QUADAS-2 tool was used to assess the quality of the studies. Diagnostic accuracy measures [i.e., sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratios (PLR), negative likelihood ratios (NLR), and the area under the curve (AUC)] were pooled with a random-effects model. All statistical analyses were performed with Meta-DiSc (Version 1.4, Cochrane Colloquium, Barcelona, Spain).

Results

After reviewing retrieved records, we identified 60 studies that met the inclusion criteria. The pooled sensitivity and specificity of the rapid antigen tests against the reference test (the real-time PCR) were 69% (95% CI: 68–70) and 99% (95% CI: 99–99). The PLR, NLR, DOR and the AUC estimates were found to be 72 (95% CI: 44–119), 0.30 (95% CI: 0.26–0.36), 316 (95% CI: 167–590) and 97%, respectively.

Conclusion

The present study indicated that using RAT kits is primarily recommended for the early detection of patients suspected of having COVID-19, particularly in countries with limited resources and laboratory equipment. However, the negative RAT samples may need to be confirmed using molecular tests, mainly when the symptoms of COVID-19 are present.

SaliVISION: a rapid saliva-based COVID-19 screening and diagnostic test with high sensitivity and specificity

The Coronavirus disease 2019 (COVID-19) pandemic-caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)– has posed a global threat and presented with it a multitude of economic and public-health challenges. Establishing a reliable means of readily available, rapid diagnostic testing is of paramount importance in halting the spread of COVID-19, as governments continue to ease lockdown restrictions. The current standard for laboratory testing utilizes reverse transcription quantitative polymerase chain reaction (RT-qPCR); however, this method presents clear limitations in requiring a longer run-time as well as reduced on-site testing capability. Therefore, we investigated the feasibility of a reverse transcription looped-mediated isothermal amplification (RT-LAMP)-based model of rapid COVID-19 diagnostic testing which allows for less invasive sample collection, named SaliVISION. This novel, two-step, RT-LAMP assay utilizes a customized multiplex primer set specifically targeting SARS-CoV-2 and a visual report system that is ready to interpret within 40 min from the start of sample processing and does not require a BSL-2 level testing environment or special laboratory equipment. When compared to the SalivaDirect and Thermo Fisher Scientific TaqPath RT-qPCR testing platforms, the respective sensitivities of the SaliVISION assay are 94.29% and 98.28% while assay specificity was 100% when compared to either testing platform. Our data illustrate a robust, rapid diagnostic assay in our novel RT-LAMP test design, with potential for greater testing throughput than is currently available through laboratory testing and increased on-site testing capability.

A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19

The novel coronavirus, renamed SARS-CoV-2 and most commonly referred to as COVID-19, has infected nearly 44.83 million people in 224 countries and has been designated SARS-CoV-2. In this study, we used ‘web of Science’, ‘Scopus’ and ‘goggle scholar’ with the keywords of “SARS-CoV-2 detection” or “coronavirus 2019 detection” or “COVID 2019 detection” or “COVID 19 detection” “corona virus techniques for detection of COVID-19”, “audio techniques for detection of COVID-19”, “speech techniques for detection of COVID-19”, for period of 2019–2021. Some COVID-19 instances have an impact on speech production, which suggests that researchers should look for signs of disease detection in speech utilising audio and speech recognition signals from humans to better understand the condition. It is presented in this review that an overview of human audio signals is presented using an AI (Artificial Intelligence) model to diagnose, spread awareness, and monitor COVID-19, employing bio and non-obtrusive signals that communicated human speech and non-speech audio information is presented. Development of accurate and rapid screening techniques that permit testing at a reasonable cost is critical in the current COVID-19 pandemic crisis, according to the World Health Organization. In this context, certain existing investigations have shown potential in the detection of COVID 19 diagnostic signals from relevant auditory noises, which is a promising development. According to authors, it is not a single “perfect” COVID-19 test that is required, but rather a combination of rapid and affordable tests, non-clinic pre-screening tools, and tools from a variety of supply chains and technologies that will allow us to safely return to our normal lives while we await the completion of the hassle free COVID-19 vaccination process for all ages. This review was able to gather information on biomedical signal processing in the detection of speech, coughing sounds, and breathing signals for the purpose of diagnosing and screening the COVID-19 virus.

•

This is a comprehensive review of published work for the detection of COVID-19.

•

Previously conducted studies on audio, voice, cough sound, breathing and signal processing methods in order to address COVID-19-related health conditions.

•

Analyzing and diagnosing COVID-19 using audio, speech and Signal Processing.

•

Diagnosing and Screening of COVID-19 are studied using Machine Learning, Artificial Intelligence and Deep Learning.

•

An overall these Signal Processing, Machine Learning, Artificial Intelligence and Deep Learning techniques were seen to have satisfactory results for the detection of COVID-19.

Epidemiological profile and performance of triage decision-making process of COVID-19 suspected cases in southern Tunisia

Introduction

During an epidemic, screening processes can play a crucial role in limiting the spread of the infection. The aim of this study was to describe the epidemiological profile of COVID-19 suspected cases and to evaluate the performance of the triage process in predicting COVID-19 in Southern Tunisia.

Methods

It was a prospective study including all patients consulting to the Hedi Chaker University Hospital departments from March to June 2020. A clinical triage score (CTS) was used to assess the risk of the infection and to refer patients to the appropriate part of the facility accordingly.

Results

Overall, 862 patients were enrolled, among whom 505 patients (58.6%) were classified as suspected cases (CTS ≥4). Of these, 46.9% (n = 237) were of mild form. Samples were collected from 215 patients (24.9%), among whom five were COVID-19 positive, representing a positive rate of 2.3%. The in-hospital cumulative incidence rate of COVID-19 was 580/100000 patients. The total daily incidence decreased significantly during the study period (p < 0.001, chi-square for linear trend = 25.6). At a cut-off of four, the CTS had a sensitivity of 40%, a specificity of 32.4%, and negative and positive predictive values of 95.8% and 1.4%, respectively.

Discussion

Although the triage process based on the CTS was not as performant as the RT-PCR, it was crucial to interrupt virus spread among hospitalized patients in “COVID-19-free departments”.

Detection and classification of SARS-CoV-2 using high-resolution melting analysis

Coronavirus disease 2019 (COVID‐19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has recently posed a significant threat to global public health. The objective of this study was to develop and evaluate a rapid, expandable and sequencing‐free high‐resolution melting (HRM) approach for the direct detection and classification of SARS‐CoV‐2. Thirty‐one common pathogens that can cause respiratory tract infections were used to evaluate the specificity of the method. Synthetic RNA with serial dilutions was utilized to determine the sensitivity of the method. Finally, the clinical performance of the method was assessed using 290 clinical samples. The one‐step multiplex HRM could accurately identify SARS‐CoV‐2 and differentiate mutations in each marker site within approximately 2 h. For each target, the limit of detection was lower than 10 copies/reaction, and no cross‐reactivity was observed among organisms within the specificity testing panel. The method showed good uniformity for SARS‐CoV‐2 detection with a consistency of 100%. Regarding the clade classification performance, the results showed good concordance compared with sequencing, with the rate of agreement being 95.1% (78/82). The one‐step multiplex HRM method is a rapid method for SARS‐CoV‐2 detection and classification.

A method comparison study of the high throughput automated HISCL® SARS-CoV-2 antigen assay using nasopharyngeal swab samples from symptomatic and asymptomatic subjects against conventional RT-PCR

Our study aim was to evaluate the performance of the automated Sysmex HISCL® severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) antigen assay against reverse‐transcription polymerase chain reaction (RT‐PCR). We tested 277 remnant frozen nasopharyngeal swab samples, stored in universal transport medium (UTM), yielding a sensitivity of 94.9% against historical RT‐PCR results with cycle threshold (C_t) < 30, and a sensitivity of 76.7% for C_t < 35, and specificity of 100% (all C_t values) confirming compatibility of UTM‐diluted samples with the assay system. Thereafter, we prospectively collected 141 nasopharyngeal swab samples in UTM from healthcare workers and 1369 paired swabs (400 UTM; 969 dry) from individuals at a public health testing center, with the first swab (UTM) reserved for RT‐PCR, yielding a positivity rate of 4.6%. HISCL assay performance using UTM swabs was superior to dry swabs, with a sensitivity of 100% (95% confidence interval [CI] 71.5%–100%) at C_t < 30 versus 92.3% (95%CI 81.5%–97.9%), and a specificity of 99.3% (95% CI 98.1–99.89) against 83.3% (95%CI 80.7%–85.6%). We conclude that this antigen assay is suitable for high throughput facilities where the primary indication for testing is to rule out infection with low RT‐PCR C_t values (proxy for high viral loads) to curb viral spread.