Review of analytical performance of COVID-19 detection methods

Monitoring Coronavirus Disease 2019: A Review of Available Diagnostic Tools

Coronavirus disease 2019 (COVID-19) pneumonia is caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has rapidly become a global public health concern. As the new type of betacoronavirus, SARS-CoV-2 can spread across species and between populations and has a greater risk of transmission than other coronaviruses. To control the spread of SARS-CoV-2, it is vital to have a rapid and effective means of diagnosing asymptomatic SARS-CoV-2-positive individuals and patients with COVID-19, an early isolation protocol for infected individuals, and effective treatments for patients with COVID-19 pneumonia. In this review, we will summarize the novel diagnostic tools that are currently available for coronavirus, including imaging examinations and laboratory medicine by next-generation sequencing (NGS), real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) analysis, immunoassay for COVID-19, cytokine and T cell immunoassays, biochemistry and microbiology laboratory parameters in the blood of the patients with COVID-19, and a field-effect transistor-based biosensor of COVID-19. Specifically, we will discuss the effective detection rate and assay time for the rRT-PCR analysis of SARS-CoV-2 and the sensitivity and specificity of different antibody detection methods, such as colloidal gold and ELISA using specimen sources obtained from the respiratory tract, peripheral serum or plasma, and other bodily fluids. Such diagnostics will help scientists and clinicians develop appropriate strategies to combat COVID-19.

Challenges of SERS technology as a non-nucleic acid or -antigen detection method for SARS-CoV-2 virus and its variants

The COVID-19 pandemic has caused a significant burden since December 2019 that has negatively impacted the global economy owing to the fact that the SARS-CoV-2 virus is fast-transmitting and highly contagious. Efforts have been taken to minimize the impact through strict screening measures in country borders in order to isolate potential virus carriers. Effective fast-screening methods are thus needed to identify infected individuals. The standard diagnostic methods for screening SARS-CoV-2 virus have always been to perform nucleic acid-based and serological tests. However, with each having drawbacks on producing false results at very early or later stage after symptoms onset, supplementary techniques are needed to back up these tests. Surface-enhanced Raman spectroscopy (SERS) as a detection technique has continuously advanced throughout the years in terms of sensitivity and capability to detect ultralow concentration of analytes ranging from single molecule to pathogens, to present as a highly potential alternative to known sensing methods. SERS technology as a candidate for an alternative and supplementary diagnostic method for the viral envelope of SARS-CoV-2 virus is presented, comparing its pros and cons to the standard methods and what other aspects it could offer that the other methods are not capable of. Factors that contribute to the detection effectivity of SERS is also discussed to show the advantages and limitations of this technique. Despite its promising capabilities, challenges like sources of SARS-CoV-2 virus and its variations, reliable SERS spectra, mass production of SERS-active substrates, and compliance to regulations for wide-scale testing scenario are highlighted.

Challenges of SERS technology as a non-nucleic acid or -antigen detection method for SARS-CoV-2 virus and its variants

The COVID-19 pandemic has caused a significant burden since December 2019 that has negatively impacted the global economy owing to the fact that the SARS-CoV-2 virus is fast-transmitting and highly contagious. Efforts have been taken to minimize the impact through strict screening measures in country borders in order to isolate potential virus carriers. Effective fast-screening methods are thus needed to identify infected individuals. The standard diagnostic methods for screening SARS-CoV-2 virus have always been to perform nucleic acid-based and serological tests. However, with each having drawbacks on producing false results at very early or later stage after symptoms onset, supplementary techniques are needed to back up these tests. Surface-enhanced Raman spectroscopy (SERS) as a detection technique has continuously advanced throughout the years in terms of sensitivity and capability to detect ultralow concentration of analytes ranging from single molecule to pathogens, to present as a highly potential alternative to known sensing methods. SERS technology as a candidate for an alternative and supplementary diagnostic method for the viral envelope of SARS-CoV-2 virus is presented, comparing its pros and cons to the standard methods and what other aspects it could offer that the other methods are not capable of. Factors that contribute to the detection effectivity of SERS is also discussed to show the advantages and limitations of this technique. Despite its promising capabilities, challenges like sources of SARS-CoV-2 virus and its variations, reliable SERS spectra, mass production of SERS-active substrates, and compliance to regulations for wide-scale testing scenario are highlighted.

Voltammetric-based immunosensor for the detection of SARS-CoV-2 nucleocapsid antigen

Since the COVID-19 disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) was declared a pandemic, it has spread rapidly, causing one of the most serious outbreaks in the last century. Reliable and rapid diagnostic tests for COVID-19 are crucial to control and manage the outbreak. Here, a label-free square wave voltammetry-based biosensing platform for the detection of SARS-CoV-2 in nasopharyngeal samples is reported. The sensor was constructed on screen-printed carbon electrodes coated with gold nanoparticles. The electrodes were functionalized using 11-mercaptoundecanoic acid (MUA) which was used for the immobilization of an antibody against SARS-CoV-2 nucleocapsid protein (N protein). The binding of the immunosensor with the N protein caused a change in the electrochemical signal. The detection was realised by measuring the change in reduction peak current of a redox couple using square wave voltammetry at 0.04 V versus Ag ref. electrode on the immunosensor upon binding with the N protein. The electrochemical immunosensor showed high sensitivity with a linear range from 1.0 pg.mL⁻¹ to 100 ng.mL⁻¹ and a limit of detection of 0.4 pg.mL⁻¹ for the N protein in PBS buffer pH 7.4. Moreover, the immunosensor did not exhibit significant response with other viruses such as HCoV, MERS-CoV, Flu A and Flu B, indicating the high selectivity of the sensor for SARS-CoV-2. However, cross reactivity of the biosensor with SARS-CoV is indicated, which gives ability of the sensor to detect both SARS-CoV and SARS-CoV-2. The biosensor was successfully applied to detect the SARS-CoV-2 virus in clinical samples showing good correlation between the biosensor response and the RT-PCR cycle threshold values. We believe that the capability of miniaturization, low-cost and fast response of the proposed label-free electrochemical immunosensor will facilitate the point-of-care diagnosis of COVID 19 and help prevent further spread of infection.

Pool testing on random and natural clusters of individuals: Optimisation of SARS-CoV-2 surveillance in the presence of low viral load samples

Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. During the first emergency phase of the epidemic, RT-qPCR on nasopharyngeal (NP) swabs, which is the most reliable technique to detect ongoing infections, exhibited limitations due to availability of reagents and budget constraints. This stressed the need to develop screening procedures that require fewer resources and are suitable to be extended to larger portions of the population. RT-qPCR on pooled samples from individual NP swabs seems to be a promising technique to improve surveillance. We performed preliminary experimental analyses aimed to investigate the performance of pool testing on samples with low viral load and we evaluated through Monte Carlo (MC) simulations alternative screening protocols based on sample pooling, tailored to contexts characterized by different infection prevalence. We focused on the role of pool size and the opportunity to develop strategies that take advantage of natural clustering structures in the population, e.g. families, school classes, hospital rooms. Despite the use of a limited number of specimens, our results suggest that, while high viral load samples seem to be detectable even in a pool with 29 negative samples, positive specimens with low viral load may be masked by the negative samples, unless smaller pools are used. The results of MC simulations confirm that pool testing is useful in contexts where the infection prevalence is low. The gain of pool testing in saving resources can be very high, and can be optimized by selecting appropriate group sizes. Exploiting natural groups makes the definition of larger pools convenient and potentially overcomes the issue of low viral load samples by increasing the probability of identifying more than one positive in the same pool.

Portable Sensing Devices for Detection of COVID-19: A Review

The coronavirus pandemic is the most challenging incident that people have faced in recent years. Despite the time-consuming and expensive conventional methods, point-of-care diagnostics have a crucial role in deterrence, timely detection, and intensive care of the disease's progress. Hence, this detrimental health emergency persuaded researchers to accelerate the development of highly-scalable diagnostic devices to control the propagation of the virus even in the least developed countries. The strategies exploited for detecting COVID-19 stem from the already designed systems for studying other maladies, particularly viral infections. The present report reviews not only the novel advances in portable diagnostic devices for recognizing COVID-19, but also the previously existing biosensors for detecting other viruses. It discusses their adaptability for identifying surface proteins, whole viruses, viral genomes, host antibodies, and other biomarkers in biological samples. The prominence of different types of biosensors such as electrochemical, optical, and electrical for detecting low viral loads have been underlined. Thus, it is anticipated that this review will assist scientists who have embarked on a competition to come up with more efficient and marketable in-situ test kits for identifying the infection even in its incubation time without sample pretreatment. Finally, a conclusion is provided to highlight the importance of such an approach for monitoring people to combat the spread of such contagious diseases.

Development of multiplex real-time RT-PCR assay for the detection of SARS-CoV-2

The outbreak of the new human coronavirus SARS-CoV-2 (also known as 2019-nCoV) continues to increase globally. The real-time reverse transcription polymerase chain reaction (rRT-PCR) is the most used technique in virus detection. However, possible false-negative and false-positive results produce misleading consequences, making it necessary to improve existing methods. Here, we developed a multiplex rRT-PCR diagnostic method, which targets two viral genes (RdRP and E) and one human gene (RP) simultaneously. The reaction was tested by using pseudoviral RNA and human target mRNA sequences as a template. Also, the protocol was validated by using 14 clinical SARS-CoV-2 positive samples. The results are in good agreement with the CDC authorized Cepheid`s Xpert® Xpress SARS-CoV-2 diagnostic system (100%). Unlike single gene targeting strategies, the current method provides the amplification of two viral regions in the same PCR reaction. Therefore, an accurate SARS-CoV-2 diagnostic assay was provided, which allows testing of 91 samples in 96-well plates in per run. Thanks to this strategy, fast, reliable, and easy-to-use rRT-PCR method is obtained to diagnose SARS-CoV-2.

Time variation in the probability of failing to detect a case of polymerase chain reaction testing for SARS-CoV-2 as estimated from a viral dynamics model

Viral tests including polymerase chain reaction (PCR) tests are recommended to diagnose COVID-19 infection during the acute phase of infection. A test should have high sensitivity; however, the sensitivity of the PCR test is highly influenced by viral load, which changes over time. Because it is difficult to collect data before the onset of symptoms, the current literature on the sensitivity of the PCR test before symptom onset is limited. In this study, we used a viral dynamics model to track the probability of failing to detect a case of PCR testing over time, including the presymptomatic period. The model was parametrized by using longitudinal viral load data collected from 30 hospitalized patients. The probability of failing to detect a case decreased toward symptom onset, and the lowest probability was observed 2 days after symptom onset and increased afterwards. The probability on the day of symptom onset was 1.0% (95% CI: 0.5 to 1.9) and that 2 days before symptom onset was 60.2% (95% CI: 57.1 to 63.2). Our study suggests that the diagnosis of COVID-19 by PCR testing should be done carefully, especially when the test is performed before or way after symptom onset. Further study is needed of patient groups with potentially different viral dynamics, such as asymptomatic cases.

Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives

Artificial intelligence (AI) is being used to aid in various aspects of the COVID-19 crisis, including epidemiology, molecular research and drug development, medical diagnosis and treatment, and socioeconomics. The association of AI and COVID-19 can accelerate to rapidly diagnose positive patients. To learn the dynamics of a pandemic with relevance to AI, we search the literature using the different academic databases (PubMed, PubMed Central, Scopus, Google Scholar) and preprint servers (bioRxiv, medRxiv, arXiv). In the present review, we address the clinical applications of machine learning and deep learning, including clinical characteristics, electronic medical records, medical images (CT, X-ray, ultrasound images, etc.) in the COVID-19 diagnosis. The current challenges and future perspectives provided in this review can be used to direct an ideal deployment of AI technology in a pandemic.

Nanobiotechnology as a platform for the diagnosis of COVID-19: a review

A sensitive method for diagnosing coronavirus disease 2019 (COVID-19) is highly required to fight the current and future global health threats due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2). However, most of the current methods exhibited high false‐negative rates, resulting in patient misdiagnosis and impeding early treatment. Nanoparticles show promising performance and great potential to serve as a platform for diagnosing viral infection in a short time and with high sensitivity. This review highlighted the potential of nanoparticles as platforms for the diagnosis of COVID-19. Nanoparticles such as gold nanoparticles, magnetic nanoparticles, and graphene (G) were applied to detect SARS-CoV 2. They have been used for molecular-based diagnosis methods and serological methods. Nanoparticles improved specificity and shorten the time required for the diagnosis. They may be implemented into small devices that facilitate the self-diagnosis at home or in places such as airports and shops. Nanoparticles-based methods can be used for the analysis of virus-contaminated samples from a patient, surface, and air. The advantages and challenges were discussed to introduce useful information for designing a sensitive, fast, and low-cost diagnostic method. This review aims to present a helpful survey for the lesson learned from handling this outbreak to prepare ourself for future  pandemic.

Clinical decision support tool for diagnosis of COVID-19 in hospitals

Background

The coronavirus infectious disease 19 (COVID-19) pandemic has resulted in significant morbidities, severe acute respiratory failures and subsequently emergency departments’ (EDs) overcrowding in a context of insufficient laboratory testing capacities. The development of decision support tools for real-time clinical diagnosis of COVID-19 is of prime importance to assist patients’ triage and allocate resources for patients at risk.

Methods and principal findings

From March 2 to June 15, 2020, clinical patterns of COVID-19 suspected patients at admission to the EDs of Liège University Hospital, consisting in the recording of eleven symptoms (i.e. dyspnoea, chest pain, rhinorrhoea, sore throat, dry cough, wet cough, diarrhoea, headache, myalgia, fever and anosmia) plus age and gender, were investigated during the first COVID-19 pandemic wave. Indeed, 573 SARS-CoV-2 cases confirmed by qRT-PCR before mid-June 2020, and 1579 suspected cases that were subsequently determined to be qRT-PCR negative for the detection of SARS-CoV-2 were enrolled in this study. Using multivariate binary logistic regression, two most relevant symptoms of COVID-19 were identified in addition of the age of the patient, i.e. fever (odds ratio [OR] = 3.66; 95% CI: 2.97–4.50), dry cough (OR = 1.71; 95% CI: 1.39–2.12), and patients older than 56.5 y (OR = 2.07; 95% CI: 1.67–2.58). Two additional symptoms (chest pain and sore throat) appeared significantly less associated to the confirmed COVID-19 cases with the same OR = 0.73 (95% CI: 0.56–0.94). An overall pondered (by OR) score (OPS) was calculated using all significant predictors. A receiver operating characteristic (ROC) curve was generated and the area under the ROC curve was 0.71 (95% CI: 0.68–0.73) rendering the use of the OPS to discriminate COVID-19 confirmed and unconfirmed patients. The main predictors were confirmed using both sensitivity analysis and classification tree analysis. Interestingly, a significant negative correlation was observed between the OPS and the cycle threshold (Ct values) of the qRT-PCR.

Conclusion and main significance

The proposed approach allows for the use of an interactive and adaptive clinical decision support tool. Using the clinical algorithm developed, a web-based user-interface was created to help nurses and clinicians from EDs with the triage of patients during the second COVID-19 wave.

COVID-19 into Chemical Science Perspective: Chemical Preventive Measures and Drug Development

COVID-19 facts and literature are discussed into chemical science intuition highlighting the direct role of chemistry to the ongoing global pandemic by covering structural identification of the virus, chemical preventive measures and development of drugs. We reviewed the four most promising repurposed drugs which are presently being investigated in mass clinical trials on COVID-19 infected persons and synthetic routes of these drugs with their recent advancement. Chemical preventive measures such as soap water, hand sanitizer and disinfectant are the only available options in the arsenal to fight against COVID-19, till an effective medicine or vaccine will be made available. As such the present review will focus on the mode of action of the major chemical preventives.

SARS-CoV-2 RNA Detection with Duplex-Specific Nuclease Signal Amplification

The emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a zoonotic pathogen, has led to the outbreak of coronavirus disease 2019 (COVID-19) pandemic and brought serious threats to public health worldwide. The gold standard method for SARS-CoV-2 detection requires both reverse transcription (RT) of the virus RNA to cDNA and then polymerase chain reaction (PCR) for the cDNA amplification, which involves multiple enzymes, multiple reactions and a complicated assay optimization process. Here, we developed a duplex-specific nuclease (DSN)-based signal amplification method for SARS-CoV-2 detection directly from the virus RNA utilizing two specific DNA probes. These specific DNA probes can hybridize to the target RNA at different locations in the nucleocapsid protein gene (N gene) of SARS-CoV-2 to form a DNA/RNA heteroduplex. DSN cleaves the DNA probe to release fluorescence, while leaving the RNA strand intact to be bound to another available probe molecule for further cleavage and fluorescent signal amplification. The optimized DSN amount, incubation temperature and incubation time were investigated in this work. Proof-of-principle SARS-CoV-2 detection was demonstrated with a detection sensitivity of 500 pM virus RNA. This simple, rapid, and direct RNA detection method is expected to provide a complementary method for the detection of viruses mutated at the PCR primer-binding regions for a more precise detection.

Evaluation of two fluorescence immunoassays for the rapid detection of SARS-CoV-2 antigen-new tool to detect infective COVID-19 patients

Background

Real-Time Reverse-Transcription Polymerase Chain Reaction (RT-PCR) is currently the only recommended diagnostic method for SARS-CoV-2. However, rapid immunoassays for SARS-CoV-2 antigen could significantly reduce the COVID-19 burden currently weighing on laboratories around the world.

Methods

We evaluated the performance of two rapid fluorescence immunoassays (FIAs), SOFIA SARS Antigen FIA (Quidel Corporation, San Diego, CA, USA) and STANDARD F COVID-19 Ag FIA (SD Biosensor Inc., Gyeonggi-do, Republic of Korea), which use an automated reader. The study used 64 RT-PCR characterized clinical samples (32 positive; 32 negative), which consisted of nasopharyngeal swabs in universal transport medium.

Results

Of the 32 positive specimens, all from patients within 5 days of symptom onset, the Quidel and SD Biosensor assays detected 30 (93.8%) and 29 (90.6%) samples, respectively. Among the 27 samples with high viral loads (Ct ≤ 25), the two tests had a sensitivity of 100%. Specificity was 96.9% for both kits.

Conclusion

The high performance of the evaluated FIAs indicates a potential use as rapid and PCR-independent tools for COVID-19 diagnosis in early stages of infection. The excellent sensitivity to detect cases with viral loads above ~10⁶ copies/mL (Ct values ≤ 25), the estimated threshold of contagiousness, suggests that the assays might serve to rapidly identify infective individuals.

Impact of SARS-CoV-2 pandemic among health care workers in a secondary teaching hospital in Spain

BACKGROUND

The COVID-19 pandemic has posed a huge challenge to healthcare systems and their personnel worldwide. The study of the impact of SARS-CoV-2 infection among healthcare workers (HCW), through prevalence studies, will let us know viral expansion, individuals at most risk and the most exposed areas in healthcare organizations. The aim of this study is to gauge the impact of SARS-CoV-2 pandemic in our hospital workforce and identify groups and areas at increased risk.

METHODS AND FINDINGS

This is a cross-sectional and incidence study carried out on healthcare workers based on molecular and serological diagnosis of SARS-CoV-2 infection. Of the 3013 HCW invited to participate, 2439 (80.9%) were recruited, including 674 (22.4%) who had previously consulted at the Occupational Health Service (OHS) for confirmed exposure and/or presenting symptoms suggestive of COVID-19. A total of 411 (16.9%) and 264 (10.8%) healthcare workers were SARS-CoV-2 IgG and rRT-PCR positive, respectively. The cumulative prevalence considering all studies (IgG positive HCW and/or rRT-PCR positive detection) was 485 (19.9%). SARS-CoV-2 IgG-positive patients in whom the virus was not detected were 221 (9.1%); up to 151 of them (68.3%) did not report any compatible symptoms nor consult at the OHS for this reason. Men became more infected than women (25% vs 18.5%, p = 0.0009), including when data were also classified by age. COVID-19 cumulative prevalence among the HCW assigned to medical departments was higher (25.2%) than others, as well as among medical staff (25.4%) compared with other professional categories (p<0.01).

CONCLUSIONS

The global impact of the COVID-19 pandemic on HCW of our centre has been 19.9%. Doctors and medical services personnel have had the highest prevalence of SARS-CoV-2 infection, but many of them have not presented compatible symptoms. This emphasizes the performance of continuous surveillance methods of the most exposed health personnel and not only based on the appearance of symptoms.

New insights into application of nanoparticles in the diagnosis and screening of novel coronavirus (SARS-CoV-2)

Novel coronavirus disease 2019 (COVID-19) is by far the worst pandemic disease in the current millennium. The first human-to-human transmission was observed in December 2019 in China and is caused by the highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has infected millions of people within months across the globe. SARS-CoV-2 is a spike protein enveloped virus with particle-like characteristics and a diameter of 60-140 nm. Real-time PCR, reverse transcriptase PCR, isothermal PCR, immunological-based detection technique and nano-based diagnostic system have been explained for the identification and differentiation of different types of virus including SARS-COV-2. Synthetic nanoparticles can closely mimic the virus and interact strongly with its virulent proteins due to their morphological similarities. Some of the antiviral nanomaterials are also discussed, for example zinc oxide nanoparticle is an antiviral agent with a tetrapod morphology that mimics the cell surface by interacting with the viral capsid. It suppressed the viral proteins upon UV radiation due to reaction caused by photocatalysis. Hence, nanoparticle-based strategies for tackling viruses have immense potential. The second part of the review points to the latest in vitro and in vivo procedures for screening viral particles and the usage of nanoparticles in diagnostic and therapeutics. This would be beneficial for early detection and assists for the safe and effective therapeutic management of COVID-19.

Pregnancy and Childbirth in the COVID-19 Era-The Course of Disease and Maternal-Fetal Transmission

From the beginning of the Coronavirus Disease 2019 (COVID-19) pandemic, special attention has been paid to pregnant women and to monitoring comorbidities, such as gestational diabetes and hypertension, which could increase their risk of disease and death. The purpose of this review is to synthesize the available knowledge on the course of COVID-19 in pregnant women as well as the risk of maternal-fetal transmission. The study indicated that the course of COVID-19 is worse in pregnant women who are more often admitted to intensive care units or who require mechanical ventilation than nonpregnant women with COVID-19. Some symptoms, such as dyspnea and cough, were similar to those observed in nonpregnant women, but fever, headache, muscle aches, chills, and diarrhea were less frequent. A study revealed that premature delivery and cesarean section were more common in pregnant women diagnosed with COVID-19. In addition, recent studies confirm the possibility of intrauterine maternal-fetal transmission by positive genetic tests and the presence of IgM in newborns just after delivery; at the moment, the probability of transmission through mother's milk is inconclusive. Considering all the above, a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is an important factor that threatens the health and life of both the mother and the fetus, but further studies are still needed.