Insight into the practical performance of RT-PCR testing for SARS-CoV-2 using serological data: a cohort study

Adjusting Incidence Estimates with Laboratory Test Performances: A Pragmatic Maximum Likelihood Estimation-Based Approach

Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings.

Digital microfluidics methods for nucleic acid detection: A mini review

Many serious infectious diseases have occurred throughout human history. Rapid and accurate detection as well as the isolation of infected individuals, through nucleic acid testing, are effective means of containing the spread of these viruses. However, traditional nucleic acid testing methods rely on complex machines and specialized personnel, making it difficult to achieve large-scale, high-throughput, and rapid detection. In recent years, digital microfluidics has emerged as a promising technology that integrates various fields, including electrokinetics, acoustics, optics, magnetism, and mechanics. By leveraging the advantages of these different technologies, digital microfluidic chips offer several benefits, such as high detection throughput, integration of multiple functions, low reagent consumption, and portability. This rapid and efficient testing is crucial in the timely detection and isolation of infected individuals to prevent the virus spread. Another advantage is the low reagent consumption of digital microfluidic chips. Compared to traditional methods, these chips require smaller volumes of reagents, resulting in cost savings and reduced waste. Furthermore, digital microfluidic chips are portable and can be easily integrated into point-of-care testing devices. This enables testing to be conducted in remote or resource-limited areas, where access to complex laboratory equipment may be limited. Onsite testing reduces the time and cost associated with sample transportation. In conclusion, bioassay technologies based on digital microfluidic principles have the potential to significantly improve infectious disease detection and control. By enabling rapid, high-throughput, and portable testing, these technologies enhance our ability to contain the spread of infectious diseases and effectively manage public health outbreaks.

Deep learning network selection and optimized information fusion for enhanced COVID‐19 detection

This study proposes a wrapper‐based technique to improve the classification performance of chest infection (including COVID‐19) detection using X‐rays. Deep features were extracted using pretrained deep learning models. Ten optimization techniques, including poor and rich optimization, path finder algorithm, Henry gas solubility optimization, Harris hawks optimization, atom search optimization, manta‐ray foraging optimization, equilibrium optimizer, slime mold algorithm, generalized normal distribution optimization, and marine predator algorithm, were used to determine the optimal features using a support vector machine. Moreover, a network selection technique was used to select the deep learning models. An online chest infection detection X‐ray scan dataset was used to validate the proposed approach. The results suggest that the proposed wrapper‐based automatic deep learning network selection and feature optimization framework has a high classification rate of 97.7%. The comparative analysis further validates the credibility of the framework in COVID‐19 and other chest infection classifications, suggesting that the proposed approach can help doctors in clinical practice.

Detection of patients with COVID-19 by the emergency medical services in Lombardy through an operator-based interview and machine learning models

BACKGROUND

The regional emergency medical service (EMS) in Lombardy (Italy) developed clinical algorithms based on operator-based interviews to detect patients with COVID-19 and refer them to the most appropriate hospitals. Machine learning (ML)-based models using additional clinical and geospatial epidemiological data may improve the identification of infected patients and guide EMS in detecting COVID-19 cases before confirmation with SARS-CoV-2 reverse transcriptase PCR (rtPCR).

METHODS

This was an observational, retrospective cohort study using data from October 2020 to July 2021 (training set) and October 2021 to December 2021 (validation set) from patients who underwent a SARS-CoV-2 rtPCR test within 7 days of an EMS call. The performance of an operator-based interview using close contact history and signs/symptoms of COVID-19 was assessed in the training set for its ability to determine which patients had an rtPCR in the 7 days before or after the call. The interview accuracy was compared with four supervised ML models to predict positivity for SARS-CoV-2 within 7 days using readily available prehospital data retrieved from both training and validation sets.

RESULTS

The training set includes 264 976 patients, median age 74 (IQR 55-84). Test characteristics for the detection of COVID-19-positive patients of the operator-based interview were: sensitivity 85.5%, specificity 58.7%, positive predictive value (PPV) 37.5% and negative predictive value (NPV) 93.3%. Contact history, fever and cough showed the highest association with SARS-CoV-2 infection. In the validation set (103 336 patients, median age 73 (IQR 50-84)), the best-performing ML model had an AUC of 0.85 (95% CI 0.84 to 0.86), sensitivity 91.4% (95 CI% 0.91 to 0.92), specificity 44.2% (95% CI 0.44 to 0.45) and accuracy 85% (95% CI 0.84 to 0.85). PPV and NPV were 13.3% (95% CI 0.13 to 0.14) and 98.2% (95% CI 0.98 to 0.98), respectively. Contact history, fever, call geographical distribution and cough were the most important variables in determining the outcome.

CONCLUSION

ML-based models might help EMS identify patients with SARS-CoV-2 infection, and in guiding EMS allocation of hospital resources based on prespecified criteria.

Assessing potential insights of an imperfect testing strategy: Parameter estimation and practical identifiability using early COVID-19 data in India

A deterministic model with testing of infected individuals has been proposed to investigate the potential consequences of the impact of testing strategy. The model exhibits global dynamics concerning the disease-free and a unique endemic equilibrium depending on the basic reproduction number when the recruitment of infected individuals is zero; otherwise, the model does not have a disease-free equilibrium, and disease never dies out in the community. Model parameters have been estimated using the maximum likelihood method with respect to the data of early COVID-19 outbreak in India. The practical identifiability analysis shows that the model parameters are estimated uniquely. The consequences of the testing rate for the weekly new cases of early COVID-19 data in India tell that if the testing rate is increased by 20% and 30% from its baseline value, the weekly new cases at the peak are decreased by 37.63% and 52.90%; and it also delayed the peak time by four and fourteen weeks, respectively. Similar findings are obtained for the testing efficacy that if it is increased by 12.67% from its baseline value, the weekly new cases at the peak are decreased by 59.05% and delayed the peak by 15 weeks. Therefore, a higher testing rate and efficacy reduce the disease burden by tumbling the new cases, representing a real scenario. It is also obtained that the testing rate and efficacy reduce the epidemic's severity by increasing the final size of the susceptible population. The testing rate is found more significant if testing efficacy is high. Global sensitivity analysis using partial rank correlation coefficients (PRCCs) and Latin hypercube sampling (LHS) determine the key parameters that must be targeted to worsen/contain the epidemic.

Prevalence of Post-Coronavirus Disease Condition 12 Weeks After Omicron Infection Compared With Negative Controls and Association With Vaccination Status

BACKGROUND

Post-coronovirus disease (COVID) symptoms can persist several months after severe acute respiratory syndrome coronavirus 2 infection. Little is known, however, about the prevalence of post-COVID condition following infections from Omicron variants and how this varies according to vaccination status. This study evaluates the prevalence of symptoms and functional impairment 12 weeks after an infection by Omicron variants (BA.1 and BA.2) compared with negative controls tested during the same period.

METHODS

Outpatient individuals who tested positive or negative for COVID-19 infection between December 2021 and February 2022 at the Geneva University Hospitals were followed 12 weeks after their test date.

RESULTS

Overall, 11.7% of Omicron cases had symptoms 12 weeks after the infection compared with 10.4% of individuals who tested negative during the same period (P < .001), and symptoms were much less common in vaccinated versus nonvaccinated individuals with Omicron infection (9.7% vs 18.1%; P < .001). There were no significant differences in functional impairment at 12 weeks between Omicron cases and negative controls, even after adjusting for multiple potential confounders.

CONCLUSIONS

The differential prevalence of post-COVID symptoms and functional impairment attributed to Omicron BA.1 and BA.2 infection is low when compared with negative controls. Vaccination is associated with lower prevalence of post-COVID symptoms.

Magnetic biosensors for identification of SARS-CoV-2, Influenza, HIV, and Ebola viruses: a review

Infectious diseases such as novel coronavirus (SARS-CoV-2), Influenza, HIV, Ebola, etc kill many people around the world every year (SARS-CoV-2 in 2019, Ebola in 2013, HIV in 1980, Influenza in 1918). For example, SARS-CoV-2 has plagued higher than 317 000 000 people around the world from December 2019 to January 13, 2022. Some infectious diseases do not yet have not a proper vaccine, drug, therapeutic, and/or detection method, which makes rapid identification and definitive treatments the main challenges. Different device techniques have been used to detect infectious diseases. However, in recent years, magnetic materials have emerged as active sensors/biosensors for detecting viral, bacterial, and plasmids agents. In this review, the recent applications of magnetic materials in biosensors for infectious viruses detection have been discussed. Also, this work addresses the future trends and perspectives of magnetic biosensors.

Safety of International Professional Sports Competitions During the COVID-19 Pandemic: The Association Football Experience

Major sporting events were suspended during the most acute phase of the COVID-19 pandemic. Competitions are resuming with enhanced hygiene protocols and altered mechanics. While risks for players and staff have been studied, the impact of large-scale tournaments on the communities that host them remains largely unstudied. CONMEBOL Copa América is one of the first wide-scale international tournaments to be conducted in its original format since the beginning of the COVID-19 pandemic. The tournament saw 10 national teams compete in four Brazilian cities during a period of heightened viral transmission. The analysis of over 28,000 compulsory PCR tests showed that positive cases did not lead to the uncontrolled spread of the disease among staff and players. More importantly, the data indicate that locally hired staff were not exposed to increased risk while working. The Copa América experience shows that international sporting competitions can be conducted safely even under unfavourable epidemiological situations.

Agnostic Sequencing for Detection of Viral Pathogens

The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.

Deciphering Microbiota of Acute Upper Respiratory Infections: A Comparative Analysis of PCR and mNGS Methods for Lower Respiratory Trafficking Potential

Although it is clinically important for acute respiratory tract (co)infections to have a rapid and accurate diagnosis, it is critical that respiratory medicine understands the advantages of current laboratory methods. In this study, we tested nasopharyngeal samples (n = 29) with a commercially available PCR assay and compared the results with those of a hybridization-capture-based mNGS workflow. Detection criteria for positive PCR samples was Ct < 35 and for mNGS samples it was >40% target coverage, median depth of 1X and RPKM > 10. A high degree of concordance (98.33% PPA and 100% NPA) was recorded. However, mNGS yielded positively 29 additional microorganisms (23 bacteria, 4 viruses, and 2 fungi) beyond PCR. We then characterized the microorganisms of each method into three phenotypic categories using the IDbyDNA Explify^® Platform (Illumina^® Inc, San Diego, CA, USA) for consideration of infectivity and trafficking potential to the lower respiratory region. The findings are significant for providing a comprehensive yet clinically relevant microbiology profile of acute upper respiratory infection, especially important in immunocompromised or immunocompetent with comorbidity respiratory cases or where traditional syndromic approaches fail to identify pathogenicity. Accordingly, this technology can be used to supplement current syndrome-based tests, and data can quickly and effectively be phenotypically characterized for trafficking potential, clinical (co)infection, and comorbid consideration-with promise to reduce morbidity and mortality.

Optimizing SARS-CoV-2 Pooled Testing Strategies Through Differentiated Pooling for Distinct Groups

Pooled testing has been successfully used to expand SARS-CoV-2 testing, especially in settings requiring high volumes of screening of lower-risk individuals, but efficiency of pooling declines as prevalence rises. We propose a differentiated pooling strategy that independently optimizes pool sizes for distinct groups with different probabilities of infection to further improve the efficiency of pooled testing. We compared the efficiency (results obtained per test kit used) of the differentiated strategy with a traditional pooling strategy in which all samples are processed using uniform pool sizes under a range of scenarios. For most scenarios, differentiated pooling is more efficient than traditional pooling. In scenarios examined here, an improvement in efficiency of up to 3.94 results per test kit could be obtained through differentiated versus traditional pooling, with more likely scenarios resulting in 0.12 to 0.61 additional results per kit. Under circumstances similar to those observed in a university setting, implementation of our strategy could result in an improvement in efficiency between 0.03 to 3.21 results per test kit. Our results can help identify settings, such as universities and workplaces, where differentiated pooling can conserve critical testing resources.

A Metasynthesis and Meta-analysis of the Impact and Diagnostic Safety of COVID-19 Symptom Agnostic Rapid Testing in Low- and Middle-Income Countries: Protocol for a Systematic Review

BACKGROUND

Amid all public health measures to contain COVID-19, the most challenging has been how to break the transmission chain. This has been even more challenging in low- and middle-income countries (LMICs). A public health emergency warrants a public health perspective, which comes down to prevention. Rapid mass testing has been advocated throughout the pandemic as a way to promptly deal with asymptomatic infections, but its usefulness in LMICs is yet to be fully understood.

OBJECTIVE

The study objectives of this paper are to (1) investigate the impact of the different rapid mass testing options for SARS-CoV-2 that have been delivered at point of care in LMICs and (2) evaluate the diagnostic safety (accuracy) of rapid mass testing for SARS-CoV-2 in LMICs.

METHODS

This review will systematically search records in PubMed, EBSCOhost, Cochrane library, Global Index Medicus COVID-19 Register, and Scopus. Records will be managed using Mendeley reference manager and SWIFT-Review. Risk of bias for randomized controlled trials will be assessed using the RoB 2 assessment tool, while nonrandomized interventions will be assessed using the tool developed by the Evidence Project. A narrative approach will be used to synthesize data under the first objective, and either a meta-analysis or synthesis without meta-analysis for the second objective. Tables, figures, and textual descriptions will be used to present findings. The overall body of evidence for the first objective will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach, and for the second objective using GRADE.

RESULTS

The screening of records has been finalized. We hope to finalize the synthesis by the end of February 2023 and to prepare the manuscript for publication by April 2023. The study will be reported in accordance with standard guidelines for the reporting of systematic reviews. Review results will be disseminated through conferences and their peer-reviewed publication in a relevant journal.

CONCLUSIONS

This review highlights the role of a preventive approach in infection control using rapid mass testing. It also flags the overriding need to involve users and providers in the evaluation of such tests in the settings for which they are intended. This will be the first review to the best of our knowledge to generate both qualitative and quantitative evidence regarding rapid mass testing specific to LMICs.

TRIAL REGISTRATION

PROSPERO CRD42022283776; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=283776.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/41132.

Screening and confirmation tests for SARS-CoV-2: benefits and drawbacks

Background

Coronavirus disease 2019 is a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that emerged in late 2019 and has activated an ongoing international public health emergency. SARS-CoV-2 was discovered in Wuhan, China, in December 2019 and rapidly spread to other cities and countries. Currently, SARS-CoV-2 diagnostic tests have relied heavily on detecting viral genes, antigens, and human antibodies. Hence, this review discusses and analyses the existing screening and confirmation tests for SARS-CoV-2, including the real-time reverse transcriptase polymerase chain reaction (RT-PCR), lateral flow immunoassay (LFIA), and enzyme-linked immunosorbent assay (ELISA).

Main body

The illustrations of each testing were presented to provide the readers with an understanding of the scientific principles behind the testing methods. The comparison was made by highlighting the advantages and disadvantages of each testing. ELISA is ideal for performing the maximum population screening to determine immunological capacity, although its inability to provide reliable results on the status of the infection. Recently, LFIA has been approved as a quicker way of determining whether a patient is infected at the analysis time without using particular instruments and non-laboratory settings. RT-PCR is the gold-standard approach in terms of sensitivity and specificity.

Conclusion

However, the combination of LFIA or ELISA with RT-PCR is also proposed in this review to obtain an adequate level of sensitivity and specificity.

Graphic Abstract

McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices

Worldwide COVID-19 is a highly infectious and rapidly spreading disease in almost all age groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the timely diagnosis of COVID-19 infection. In the proposed work, a deep learning-based P-shot N-ways Siamese network along with prototypical nearest neighbor classifiers is implemented for the classification of COVID-19 infection from lung CT scan slices. For this, a Siamese network with an identical sub-network (weight sharing) is used for image classification with a limited dataset for each class. The feature vectors are obtained from the pre-trained sub-networks having weight sharing. The performance of the proposed methodology is evaluated on the benchmark MosMed dataset having categories zero (healthy control) and numerous COVID-19 infections. The proposed methodology is evaluated on (a) chest CT scans provided by medical hospitals in Moscow, Russia for 1110 patients, and (b) case study of low-dose CT scans of 42 patients provided by Avtaran healthcare in India. The deep learning-based Siamese network (15-shot 5-ways) obtained an accuracy of 98.07%, the sensitivity of 95.66%, specificity of 98.83%, and F1-score of 95.10%. The proposed work outperforms the COVID-19 infection severity classification with limited scans availability for numerous infection categories.

Narrative review on century of respiratory pandemics from Spanish flu to COVID-19 and impact of nanotechnology on COVID-19 diagnosis and immune system boosting

The rise of the highly lethal severe acute respiratory syndrome-2 (SARS-2) as corona virus 2019 (COVID-19) reminded us of the history of other pandemics that happened in the last century (Spanish flu) and stayed in the current century, which include Severe-Acute-Respiratory-Syndrome (SARS), Middle-East-Respiratory-Syndrome (MERS), Corona Virus 2019 (COVID-19). We review in this report the newest findings and data on the origin of pandemic respiratory viral diseases, reservoirs, and transmission modes. We analyzed viral adaption needed for host switch and determinants of pathogenicity, causative factors of pandemic viruses, and symptoms and clinical manifestations. After that, we concluded the host factors associated with pandemics morbidity and mortality (immune responses and immunopathology, ages, and effect of pandemics on pregnancy). Additionally, we focused on the burdens of COVID-19, non-pharmaceutical interventions (quarantine, mass gatherings, facemasks, and hygiene), and medical interventions (antiviral therapies and vaccines). Finally, we investigated the nanotechnology between COVID-19 analysis and immune system boosting (Nanoparticles (NPs), antimicrobial NPs as antivirals and immune cytokines). This review presents insights about using nanomaterials to treat COVID-19, improve the bioavailability of the abused drugs, diminish their toxicity, and improve their performance.

Household transmission of the Delta COVID-19 variant in Queensland, Australia: a case series

Household transmission plays a key role in the spread of COVID-19 through populations. In this paper, we report on the transmission of COVID-19 within households in a metropolitan area in Australia, examine the impact of various factors and highlight priority areas for future public health responses. We collected and reviewed retrospective case report data and follow-up interview responses from households with a positive case of the Delta COVID-19 variant in Queensland in 2021. The overall secondary attack rate (SAR) among household contacts was 29.6% and the mean incubation period for secondary cases was 4.3 days. SAR was higher where the index case was male (57.9% vs. 14.3%) or aged ≤12 years (38.7% vs. 17.4%) but similar for adult contacts that were double vaccinated (35.7%) and unvaccinated (33.3%). Most interview participants emphasised the importance of clear, consistent and compassionate health advice as a key priority for managing outbreaks in the home. The overall rate of household transmission was slightly higher than that reported in previous studies on the wild COVID-19 variant and secondary infections developed more rapidly. While vaccination did not appear to affect the risk of transmission to adult subjects, uptake in the sample was ultimately high.

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine-Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.

The chronification of post-COVID condition associated with neurocognitive symptoms, functional impairment and increased healthcare utilization

Post-COVID condition is prevalent in 10–35% of cases in outpatient settings, however a stratification of the duration and severity of symptoms is still lacking, adding to the complexity and heterogeneity of the definition of post-COVID condition and its oucomes. In addition, the potential impacts of a longer duration of disease are not yet clear, along with which risk factors are associated with a chronification of symptoms beyond the initial 12 weeks. In this study, follow-up was conducted at 7 and 15 months after testing at the outpatient SARS-CoV-2 testing center of the Geneva University Hospitals. The chronification of symptoms was defined as the continuous presence of symptoms at each evaluation timepoint (7 and 15 months). Adjusted estimates of healthcare utilization, treatment, functional impairment and quality of life were calculated. Logistic regression models were used to evaluate the associations between the chronification of symptoms and predictors. Overall 1383 participants were included, with a mean age of 44.3 years, standard deviation (SD) 13.4 years, 61.4% were women and 54.5% did not have any comorbidities. Out of SARS-CoV-2 positive participants (n = 767), 37.0% still had symptoms 7 months after their test of which 47.9% had a resolution of symptoms at the second follow-up (15 months after the infection), and 52.1% had persistent symptoms and were considered to have a chronification of their post-COVID condition. Individuals with a chronification of symptoms had an increased utilization of healthcare resources, more recourse to treatment, more functional impairment, and a poorer quality of life. Having several symptoms at testing and difficulty concentrating at 7 months were associated with a chronification of symptoms. COVID-19 patients develop post-COVID condition to varying degrees and duration. Individuals with a chronification of symptoms experience a long-term impact on their health status, functional capacity and quality of life, requiring a special attention, more involved care and early on identification considering the associated predictors.

Modeling the optimization of COVID-19 pooled testing: How many samples can be included in a single test?

Objectives

This study tries to answer the crucial question of how many biological samples can be optimally included in a single test for COVID-19 pooled testing.

Methods

It builds a novel theoretical model which links the local population to be tested in a region, the number of biological samples included in a single test, the “attitude” toward resource cost saving and time taken in a single test, as well as the corresponding resource cost function and time function, together. The numerical simulation results are then used to formulate the resource cost function as well as the time function. Finally, a loss function to be minimized is constructed and the optimal number of samples included is calculated.

Results

In a numerical example, we consider a region of 1 million population which needs to be tested for the infection of COVID-19. The solution calculates the optimal number of biological samples included in a single test as 4.254 when the time taken is given the weight of 50% under the infection probability of 10%. Other combinations of numerical results are also presented.

Conclusions

As we can see in our simulation results, given the infection probability at 10%, setting the number of biological samples included in a single test (in the integer level) at [4,6] is reasonable for a wide range of the subjective attitude between time and resource costs. Therefore, in the current practice, 5-mixed samples would sound better than the commonly used 10-mixed samples.

Sensitivity of Reverse Transcription Polymerase Chain Reaction Tests for Severe Acute Respiratory Syndrome Coronavirus 2 Through Time

BACKGROUND

Reverse transcription polymerase chain reaction (RT-PCR) tests are the gold standard for detecting recent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Reverse transcription PCR sensitivity varies over the course of an individual's infection, related to changes in viral load. Differences in testing methods, and individual-level variables such as age, may also affect sensitivity.

METHODS

Using data from New Zealand, we estimate the time-varying sensitivity of SARS-CoV-2 RT-PCR under varying temporal, biological, and demographic factors.

RESULTS

Sensitivity peaks 4-5 days postinfection at 92.7% (91.4%-94.0%) and remains over 88% between 5 and 14 days postinfection. After the peak, sensitivity declined more rapidly in vaccinated cases compared with unvaccinated, females compared with males, those aged under 40 compared with over 40s, and Pacific peoples compared with other ethnicities.

CONCLUSIONS

Reverse transcription PCR remains a sensitive technique and has been an effective tool in New Zealand's border and postborder measures to control coronavirus disease 2019. Our results inform model parameters and decisions concerning routine testing frequency.

Multi-center validation of an artificial intelligence system for detection of COVID-19 on chest radiographs in symptomatic patients

OBJECTIVES

While chest radiograph (CXR) is the first-line imaging investigation in patients with respiratory symptoms, differentiating COVID-19 from other respiratory infections on CXR remains challenging. We developed and validated an AI system for COVID-19 detection on presenting CXR.

METHODS

A deep learning model (RadGenX), trained on 168,850 CXRs, was validated on a large international test set of presenting CXRs of symptomatic patients from 9 study sites (US, Italy, and Hong Kong SAR) and 2 public datasets from the US and Europe. Performance was measured by area under the receiver operator characteristic curve (AUC). Bootstrapped simulations were performed to assess performance across a range of potential COVID-19 disease prevalence values (3.33 to 33.3%). Comparison against international radiologists was performed on an independent test set of 852 cases.

RESULTS

RadGenX achieved an AUC of 0.89 on 4-fold cross-validation and an AUC of 0.79 (95%CI 0.78-0.80) on an independent test cohort of 5,894 patients. Delong's test showed statistical differences in model performance across patients from different regions (p < 0.01), disease severity (p < 0.001), gender (p < 0.001), and age (p = 0.03). Prevalence simulations showed the negative predictive value increases from 86.1% at 33.3% prevalence, to greater than 98.5% at any prevalence below 4.5%. Compared with radiologists, McNemar's test showed the model has higher sensitivity (p < 0.001) but lower specificity (p < 0.001).

CONCLUSION

An AI model that predicts COVID-19 infection on CXR in symptomatic patients was validated on a large international cohort providing valuable context on testing and performance expectations for AI systems that perform COVID-19 prediction on CXR.

KEY POINTS

• An AI model developed using CXRs to detect COVID-19 was validated in a large multi-center cohort of 5,894 patients from 9 prospectively recruited sites and 2 public datasets. • Differences in AI model performance were seen across region, disease severity, gender, and age. • Prevalence simulations on the international test set demonstrate the model's NPV is greater than 98.5% at any prevalence below 4.5%.

Prospects of NIR fluorescent nanosensors for green detection of SARS-CoV-2

The pandemic of the novel coronavirus disease 2019 (COVID-19) is continuously causing hazards for the world. Effective detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can relieve the impact, but various toxic chemicals are also released into the environment. Fluorescence sensors offer a facile analytical strategy. During fluorescence sensing, biological samples such as tissues and body fluids have autofluorescence, giving false-positive/negative results because of the interferences. Fluorescence near-infrared (NIR) nanosensors can be designed from low-toxic materials with insignificant background signals. Although this research is still in its infancy, further developments in this field have the potential for sustainable detection of SARS-CoV-2. Herein, we summarize the reported NIR fluorescent nanosensors with the potential to detect SARS-CoV-2. The green synthesis of NIR fluorescent nanomaterials, environmentally compatible sensing strategies, and possible methods to reduce the testing frequencies are discussed. Further optimization strategies for developing NIR fluorescent nanosensors to facilitate greener diagnostics of SARS-CoV-2 for pandemic control are proposed.

SARS-CoV-2 Risk Quantification Model and Validation Based on Large-Scale Dutch Test Events

In response to the outbreak of SARS-CoV-2, many governments decided in 2020 to impose lockdowns on societies. Although the package of measures that constitute such lockdowns differs between countries, it is a general rule that contact between people, especially in large groups of people, is avoided or prohibited. The main reasoning behind these measures is to prevent healthcare systems from becoming overloaded. As of 2021 vaccines against SARS-CoV-2 are available, but these do not guarantee 100% risk reduction and it will take a while for the world to reach a sufficient immune status. This raises the question of whether and under which conditions events like theater shows, conferences, professional sports events, concerts, and festivals can be organized. The current paper presents a COVID-19 risk quantification method for (large-scale) events. This method can be applied to events to define an alternative package of measures replacing generic social distancing.

A paper-based optical sensor for the screening of viruses through the cysteine residues of their surface proteins: A proof of concept on the detection of coronavirus infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious threat to human health. Current methods such as reverse transcription polymerase chain reaction (qRT-PCR) are complex, expensive, and time-consuming. Rapid, and simple screening methods for the detection of SARS-CoV-2 are critically required to fight the current pandemic. In this work we present a proof of concept for, a simple optical sensing method for the screening of SARS-CoV-2 through its spike protein subunit S1. The method utilizes a target-specific extractor chip to bind the protein from the biological specimens. The disulfide bonds of the protein are then reduced into a biothiol with sulfhydryl (SH) groups that react with a blue-colored benzothiazole azo dye-Hg complex (BAN-Hg) and causes the spontaneous change of its blue color to pink which is observable by the naked eye. A linear relationship between the intensity of the pink color and the logarithm of reduced S1 protein concentration was found within the working range 130 ng.mL⁻¹-1.3 pg mL⁻¹. The lowest limit of detection (LOD) of the assay was 130 fg mL⁻¹. A paper based optical sensor was fabricated by loading the BAN-Hg sensor onto filter paper and used to screen the S1 protein in spiked saliva and patients’ nasopharyngeal swabs. The results obtained by the paper sensor corroborated with those obtained by qRT-PCR. The new paper-based sensing method can be extended to the screening of many viruses (e.g. the human immunodeficiency virus, the human polyomavirus, the human papilloma virus, the adeno associated viruses, the enteroviruses) through the cysteine residues of their capsid proteins. The new method has strong potential for screening viruses at pathology labs and in remote areas that lacks advanced scientific infrastructure. Further clinical studies are warranted to validate the new sensing method.

Diagnostic Performance of SARS-CoV-2 Rapid Antigen Test in relation to RT-PCR Cq Value

Background

Early detection of the SARS-CoV-2 is crucial for both the improvement of turnaround time and limiting the spread of the virus in the community. Thus, this study aims to establish rapid antigen tests as an effective diagnostic tool to improve the testing strategies of COVID-19 diagnosis.

Methods

A laboratory based cross-sectional study was performed on the patients that visited Sukraraj Tropical and Infectious Disease Hospital (STIDH) in Kathmandu, Nepal, from November 2020 to January 2021. A total of 213 nasopharyngeal swabs were collected from both symptomatic and asymptomatic patients for rapid antigen test, followed by RT-PCR assay as reference test for confirmation of COVID-19. A standard questionnaire was administered to collect other information from patients. Data were collected and analyzed using SPSS version 20.

Results

Out of 213 individuals, 75 tested positive in Ag-RDT test, while 118 tested positive for SARS-CoV-2 RNA genome via Real time PCR assay. The overall diagnostic performance of Ag-RDT showed 63.6% sensitivity and 97.9% specificity. The diagnostic accuracy of Ag- RDT was 78.9% with κ value 0.590, showing moderate agreement with RT-PCR. Significant difference (p value <0.001) was observed between Ag- RDT+ and Ag- RDT- results when compared to Cq values obtained from RT- PCR.

Conclusion

The promising performance of Ag-RDT renders it useful as screening tool alongside RT-PCR to reduce transmission via improving contact tracing, implementation of local mitigation strategies, and refining existing testing protocol for diagnosis of COVID-19.

PERFORMANCE EVALUATION OF SIX DIFFERENT SARS-CoV-2 ANTIBODY IMMUNOASSAYS: DISEASE SEVERITY AND SERUM SAMPLING TIME AFFECT THE SENSITIVITY

Comparative validation data and clinical performance data are essential for the reliable interpretation of SARS-CoV-2 antibody test results. This study aimed to assess the performance of six SARS-CoV-2 IgG immunoassays in different disease severity settings. Four automated chemiluminescence immunoassays Access (Beckman Coulter), Architect (Abbott), Atellica-IM (Siemens) and Elecsys (Roche) and two ELISA assays (SARS-CoV-2 IgG-S1-based and NCP IgG, Euroimmun) were evaluated in 143 patients and 50 pre-pandemic control sera. Accuracy and precision tests were performed for validation. Overall sensitivity differed between 73.38-88.65%, being higher in spike protein-based assays. Specificity was ≥ 98% in all immunoassays. IgG response was lower for the samples taken <20 days post-symptom onset (87.30%) than for the samples taken ≥20 days post-symptom onset (94.80%). Higher rate of antibody was detected in the clinically moderate disease group. In the asymptomatic and mild group more antibody positivity was detected with spike protein-based assays. Clinical performance of the immunoassays differs according to disease severity and antigen targeted; moderate disease leading to highest rate of IgG response. All the assays tested were eligible for the detection of SARS-CoV-2 IgG however, spike-based assays revealed relatively higher sensitivity than the nucleoprotein-based assays particularly in the asymptomatic and mild disease severity.

Identifying SARS-COV-2 infected patients through canine olfactive detection on axillary sweat samples; study of observed sensitivities and specificities within a group of trained dogs

There is an increasing need for rapid, reliable, non-invasive, and inexpensive mass testing methods as the global COVID-19 pandemic continues. Detection dogs could be a possible solution to identify individuals infected with SARS-CoV-2. Previous studies have shown that dogs can detect SARS-CoV-2 on sweat samples. This study aims to establish the dogs’ sensitivity (true positive rate) which measures the proportion of people with COVID-19 that are correctly identified, and specificity (true negative rate) which measures the proportion of people without COVID-19 that are correctly identified. Seven search and rescue dogs were tested using a total of 218 axillary sweat samples (62 positive and 156 negative) in olfaction cones following a randomised and double-blind protocol. Sensitivity ranged from 87% to 94%, and specificity ranged from 78% to 92%, with four dogs over 90%. These results were used to calculate the positive predictive value and negative predictive value for each dog for different infection probabilities (how likely it is for an individual to be SARS-CoV-2 positive), ranging from 10–50%. These results were compared with a reference diagnostic tool which has 95% specificity and sensitivity. Negative predictive values for six dogs ranged from ≥98% at 10% infection probability to ≥88% at 50% infection probability compared with the reference tool which ranged from 99% to 95%. Positive predictive values ranged from ≥40% at 10% infection probability to ≥80% at 50% infection probability compared with the reference tool which ranged from 68% to 95%. This study confirms previous results, suggesting that dogs could play an important role in mass-testing situations. Future challenges include optimal training methods and standardisation for large numbers of detection dogs and infrastructure supporting their deployment.

RT-PCR negative COVID-19

Background

COVID-19 is a multi-system infection with emerging evidence-based antiviral and anti-inflammatory therapies to improve disease prognosis. However, a subset of patients with COVID-19 signs and symptoms have repeatedly negative RT-PCR tests, leading to treatment hesitancy. We used comparative serology early in the COVID-19 pandemic when background seroprevalence was low to estimate the likelihood of COVID-19 infection among RT-PCR negative patients with clinical signs and/or symptoms compatible with COVID-19.

Methods

Between April and October 2020, we conducted serologic testing of patients with (i) signs and symptoms of COVID-19 who were repeatedly negative by RT-PCR (‘Probables’; N = 20), (ii) signs and symptoms of COVID-19 but with a potential alternative diagnosis (‘Suspects’; N = 15), (iii) no signs and symptoms of COVID-19 (‘Non-suspects’; N = 43), (iv) RT-PCR confirmed COVID-19 patients (N = 40), and (v) pre-pandemic samples (N = 55).

Results

Probables had similar seropositivity and levels of IgG and IgM antibodies as propensity-score matched RT-PCR confirmed COVID-19 patients (60.0% vs 80.0% for IgG, p-value = 0.13; 50.0% vs 72.5% for IgM, p-value = 0.10), but multi-fold higher seropositivity rates than Suspects and matched Non-suspects (60.0% vs 13.3% and 11.6% for IgG; 50.0% vs 0% and 4.7% for IgM respectively; p-values < 0.01). However, Probables were half as likely to receive COVID-19 treatment than the RT-PCR confirmed COVID-19 patients with similar disease severity.

Conclusions

Findings from this study indicate a high likelihood of acute COVID-19 among RT-PCR negative with typical signs/symptoms, but a common omission of COVID-19 therapies among these patients. Clinically diagnosed COVID-19, independent of RT-PCR positivity, thus has a potential vital role in guiding treatment decisions.

How to organise travel restrictions in the new future: lessons from the COVID-19 response in Hong Kong and Singapore

It has been nearly 2 years since the first case of COVID-19 was reported. Governments worldwide have introduced numerous non-pharmaceutical interventions (NPIs) to combat this disease. Many of these NPIs were designed in response to initial outbreaks but are unsustainable in the long term. Governments are exploring how to adjust their current NPIs to resume normal activities while effectively protecting their population. As one of the most controversial NPIs, the implementation of travel restrictions varies across regions. Some governments have abandoned their previous travel restrictions because of the induced costs to society and on the economy. Other areas, including Hong Kong (Special Administrative Region of China) and Singapore, continue employing these NPIs as a long-term disease prevention tactic. However, the multidimensional impacts of travel restrictions require careful consideration of how to apply restrictions more appropriately. We have proposed an adapted framework to examine Hong Kong and Singapore's travel restrictions. We aimed to study these two regions' experiences in balancing disease control efforts with easing the burden on lives and livelihoods. Based on the experiences of Hong Kong and Singapore, we have outlined six policy recommendations to serve as the cornerstone for future research and policy practices.

Evaluation and Validation of the Roche Elecsys SARS-CoV-2 Antigen Electro-Chemiluminescent Immunoassay in a Southeast Asian Region

Introduction: SARS-CoV-2 antigen tests can complement and substitute for RT-PCR tests. Centralized laboratory automated SARS-CoV-2 antigen tests that can be scaled to process a large number COVID-19 cases simultaneously are now available. We have evaluated the new Roche Elecsys SARS-CoV-2 antigen electro-chemiluminescent immunoassay. Methods: The Roche SARS-CoV-2 antigen assay is a double-antibody sandwich electro-chemiluminescent immunoassay, which reports a cut-off index (COI) (COI ≥ 1.0 considered positive). We assessed assay precision and linearity, and confirmed the reactivity limit. We determined the assay sensitivity and specificity with a verification group (289 controls and 61 RT-PCR positive COVID-19 cases). Assay performance was also validated against the consecutive samples we received (7657 controls and 17 cases) for SARS-CoV-2 antigen testing from June to October 2021. Result: The assay had a within-run precision CV of 3.0% at COI 0.68, and a CV of 1.5% at COI 3.49. Between-run precision was 3.0% at COI 0.68 and 1.8% at COI 3.49. The assay was linear from COI 0.65 to 7.84. All 35 C₅₀ ± 20% test results performed over 7 days were positive/negative, respectively. In the verification group, overall sensitivity was 42.6% (26/61 positive, 95% CI 30.0–55.9), and specificity was 99.7% (1/289 positive, 95% CI 98.1–100). The agreement between the SARS-CoV-2 antigen and the RT-PCR cycle threshold (Ct) count was good (r = 0.90). In cases with Ct counts ≤ 30, the antigen assay sensitivity improved to 94.7% (18/19 positive, 95% CI 74.0–99.9). In our validation group, antigen sensitivity was 62.5% (5/8 antigen positive, 95% CI 24.5–91.5) within the first week of disease onset, but no cases were reactive after the first week of disease onset. Conclusion: The Elecsys SARS-CoV-2 antigen assay has good performance within manufacturer specifications. The sensitivity of the Roche antigen assay was greatest when used in patients with lower RT-PCR Ct values (≤30) and within the first week of disease onset.

Lateral flow-based nucleic acid detection of SARS-CoV-2 using enzymatic incorporation of biotin-labeled dUTP for POCT use

The degree of detrimental effects inflicted on mankind by the COVID-19 pandemic increased the need to develop ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable) POCT (point of care testing) to overcome the current and any future pandemics. Much effort in research and development is currently advancing the progress to overcome the diagnostic pressure built up by emerging new pathogens. LAMP (loop-mediated isothermal amplification) is a well-researched isothermal technique for specific nucleic acid amplification which can be combined with a highly sensitive immunochromatographic readout via lateral flow assays (LFA). Here we discuss LAMP-LFA robustness, sensitivity, and specificity for SARS-CoV-2 N-gene detection in cDNA and clinical swab-extracted RNA samples. The LFA readout is designed to produce highly specific results by incorporation of biotin and FITC labels to 11-dUTP and LF (loop forming forward) primer, respectively. The LAMP-LFA assay was established using cDNA for N-gene with an accuracy of 95.65%. To validate the study, 82 SARS-CoV-2-positive RNA samples were tested. Reverse transcriptase (RT)-LAMP-LFA was positive for the RNA samples with an accuracy of 81.66%; SARS-CoV-2 viral RNA was detected by RT-LAMP-LFA for as low as CT-33. Our method reduced the detection time to 15 min and indicates therefore that RT-LAMP in combination with LFA represents a promising nucleic acid biosensing POCT platform that combines with smartphone based semi-quantitative data analysis. 

Longitudinal SARS-CoV-2 seroprevalence in Portugal and antibody maintenance 12 months after infection

During the COVID-19 pandemic, Portugal has experienced three distinct SARS-CoV-2 infection waves. We previously documented the prevalence of SARS-CoV-2 immunity, measured by specific antibodies, in September 2020, 6 months after the initial moderate wave. Here, we show the seroprevalence changes 6 months later, up to the second week of March 2021, shortly following the third wave, which was one of the most severe in the world, and 2 months following the start of the vaccination campaign. A longitudinal epidemiological study was conducted, with a stratified quota sample of the Portuguese population. Serological testing was performed, including ELISA determination of antibody class and titers. The proportion of seropositives, which was 2.2% in September 2020, rose sharply to 17.3% (95% CI: 15.8-18.8%) in March 2021. Importantly, circulating IgG and IgA antibody levels were very stable 6 months after the initial determination and up to a year after initial infection, indicating long-lasting infection immunity against SARS-CoV-2. Moreover, vaccinated people had higher IgG levels from 3 weeks post-vaccination when compared with previously infected people at the same time post-infection.

Household quarantine of second degree contacts is an effective non-pharmaceutical intervention to prevent tertiary cases in the current SARS-CoV pandemic

BACKGROUND

Given the characteristics of SARS-CoV2 with regard to transmission before the onset of symptoms and varying manifestation indices according to age, isolation and quarantine have limited efficacy in the current pandemic. Household quarantine in second degree contacts (Hh-Q2°) outside the case household has so far only been addressed by modellers. In the literature there is no publication based on field data.

METHODS

In a retrospective cohort study on real field data from a county health department (CHD), all PCR-confirmed cases and related contact persons put into quarantine were analysed. Hh-Q2° was used in our CHD from the onset of the pandemic.

RESULTS

From 9 March to 8 December 2020, 353 PCR-confirmed cases were registered in the CHD Ploen, Northern Germany: 225 (63.7%) primary, 107 (30.3%) secondary and 21 (5.9%) tertiary cases. The 107 secondary cases resulted out of 470 (22.8%) close or 1°contacts and 21 tertiary cases out of 179 (11.7%) indirect or 2°contacts put into quarantine. The efficacy of Hh-Q2° was 51.5% (11.7%/22.8%) of that of quarantine in 1°contacts; 16.4% of all converted cases in quarantined persons were ascertained by Hh-Q2°. One in ten 1°contacts in households with tertiary cases remained asymptomatic.

CONCLUSION

The impact of Hh-Q2° in preventing further spread of SARS-CoV2 was considerable. With half the conversion rate in 2°contacts compared to 1°contacts, the efficacy of Hh-Q2° is substantial. Hh-Q2° should definitely be used routinely to control the spread of SARS-CoV2 more efficiently and national authorities should include it in their guidelines.

Single-Cell Immunogenomic Approach Identified SARS-CoV-2 Protective Immune Signatures in Asymptomatic Direct Contacts of COVID-19 Cases

The response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely impacted by the level of virus exposure and status of the host immunity. The nature of protection shown by direct asymptomatic contacts of coronavirus disease 2019 (COVID-19)-positive patients is quite intriguing. In this study, we have characterized the antibody titer, SARS-CoV-2 surrogate virus neutralization, cytokine levels, single-cell T-cell receptor (TCR), and B-cell receptor (BCR) profiling in asymptomatic direct contacts, infected cases, and controls. We observed significant increase in antibodies with neutralizing amplitude in asymptomatic contacts along with cytokines such as Eotaxin, granulocyte-colony stimulating factor (G-CSF), interleukin 7 (IL-7), migration inhibitory factor (MIF), and macrophage inflammatory protein-1α (MIP-1α). Upon single-cell RNA (scRNA) sequencing, we explored the dynamics of the adaptive immune response in few representative asymptomatic close contacts and COVID-19-infected patients. We reported direct asymptomatic contacts to have decreased CD4⁺ naive T cells with concomitant increase in CD4⁺ memory and CD8⁺ Temra cells along with expanded clonotypes compared to infected patients. Noticeable proportions of class switched memory B cells were also observed in them. Overall, these findings gave an insight into the nature of protection in asymptomatic contacts.

Mild SARS-CoV-2 Illness Is Not Associated with Reinfections and Provides Persistent Spike, Nucleocapsid, and Virus-Neutralizing Antibodies

Uncertainty exists whether mild COVID-19 confers immunity to reinfection. Questions also remain regarding the persistence of antibodies against SARS-CoV-2 after mild infection. We prospectively followed at-risk individuals with and without SARS-CoV-2 for reinfection and monitored the spike and nucleocapsid antibodies. This prospective cohort study was conducted over two visits, 3 to 6 months apart, between May 2020 and February 2021. Adults with and without COVID-19, verified by FDA EUA-approved SARS-CoV-2 RT-PCR assays, were screened for spike and nucleocapsid antibody responses using FDA EUA-approved immunoassays and for pseudoviral neutralization activity. The subjects were monitored for symptoms, exposure to COVID-19, COVID-19 testing, seroconversion, reinfection, and vaccination. A total of 653 subjects enrolled; 129 (20%) had a history of COVID-19 verified by RT-PCR at enrollment. Most had mild disease, with only three requiring hospitalization. No initially seropositive subjects experienced a subsequent COVID-19 infection during the follow-up versus 15 infections among initially seronegative subjects (infection rates of 0.00 versus 2.05 per 10,000 days at risk [P = 0.0485]). In all, 90% of SARS-CoV-2-positive subjects produced spike and nucleocapsid responses, and all but one of these had persistent antibody levels at follow-up. Pseudoviral neutralization activity was widespread among participants, did not decrease over time, and correlated with clinical antibody assays. Reinfection with SARS-CoV-2 was not observed among individuals with mild clinical COVID-19, while infections continued in a group without known prior infection. Spike and nucleocapsid COVID-19 antibodies were associated with almost all infections and persisted at stable levels for the study duration. IMPORTANCE This article demonstrates that people who have mild COVID-19 illnesses and produce antibodies are protected from reinfection for up to 6 months afterward. The antibodies that people produce in this situation are stable for up to 6 months as well. Clinical antibody assays correlate well with evidence of antibody-related viral neutralization activity.

SARS-CoV-2 Antibody Binding and Neutralization in Dried Blood Spot Eluates and Paired Plasma

Wide-scale assessment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibodies is critical to understanding population seroprevalence, correlates of protection, and the longevity of vaccine-elicited responses. Most SARS-CoV-2 studies characterize antibody responses in plasma/sera. While reliable and broadly used, these samples pose several logistical restrictions, such as requiring venipuncture for collection and a cold chain for transportation and storage. Dried blood spots (DBS) overcome these barriers as they can be self-collected by fingerstick and mailed and stored at ambient temperature. Here, we evaluate the suitability of DBS for SARS-CoV-2 antibody assays by comparing several antibody responses between paired plasma and DBS from SARS-CoV-2 convalescent and vaccinated individuals. We found that DBS not only reflected plasma antibody binding by enzyme-linked immunosorbent assay (ELISA) and epitope profiles using phage display, but also yielded SARS-CoV-2 neutralization titers that highly correlated with paired plasma. Neutralization measurement was further streamlined by adapting assays to a high-throughput 384-well format. This study supports the adoption of DBS for numerous SARS-CoV-2 binding and neutralization assays. IMPORTANCE Plasma and sera isolated from venous blood represent conventional sample types used for the evaluation of SARS-CoV-2 antibody responses after infection or vaccination. However, collection of these samples is invasive and requires trained personnel and equipment for immediate processing. Once collected, plasma and sera must be stored and shipped at cold temperatures. To define the risk of emerging SARS-CoV-2 variants and the longevity of immune responses to natural infection and vaccination, it will be necessary to measure various antibody features in populations around the world, including in resource-limited areas. A sampling method that is compatible with these settings and is suitable for a variety of SARS-CoV-2 antibody assays is therefore needed to continue to understand and curb the COVID-19 pandemic.

Discovery Proteomics for COVID-19: Where We Are Now

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus responsible for the pandemic coronavirus disease 2019 (COVID-19), which has had a devastating impact on society. Here, we summarize proteomic research that has helped elucidate hallmark proteins associated with the disease with respect to both short- and long-term diagnosis and prognosis. Additionally, we review the highly variable humoral response associated with COVID-19 and the increased risk of autoimmunity.

Comparing the diagnostic accuracy of rapid antigen detection tests to real time polymerase chain reaction in the diagnosis of SARS-CoV-2 infection: A systematic review and meta-analysis

BACKGROUND

Timely and accurate diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is crucial to reduce the risk of viral transmission. We investigated the diagnostic accuracy of rapid antigen detection tests (RADTs) in the diagnosis of SARS-CoV-2 infection.

METHODS

A systematic literature search was performed using Pubmed, Embase, and the Cochrane Central Register. The sensitivity, specificity, diagnostic odds ratio (DOR), and a hierarchical summary receiver-operating characteristic curve (HSROC) of RADTs were pooled using meta-analysis. We used commercial and laboratory-developed reverse transcriptase-polymerase chain reaction (RT-PCR) as reference standards.

RESULTS

We identified 24 studies comprising 14,188 patients. The overall pooled sensitivity, specificity, and DOR of RADTs for diagnosis of SARS-CoV-2 were 0.68 (95%CI, 0.59 - 0.76), 0.99 (95%CI, 0.99 - 1.00), and 426.70 (95% CI, 168.37 - 1081.65), respectively. RADTs and RT-PCR had moderate agreement with an estimated pooled Cohen's kappa statistic of 0.75 (95%CI, 0.74-0.77), and area under the HSROC of 0.98 (95%CI, 0.96 - 0.99). The pooled sensitivity of RADTs was significantly increased in subjects with viral load of Ct-value ≤25 or in those within 5 days after symptom onset than it was in subjects with lower viral loads or longer symptom duration.

CONCLUSIONS

The overall sensitivity of RADTs was inferior to that of the RT-PCR assay. The RADTs were more sensitive for samples of Ct-value ≤ 25 and might be suitable for subjects in the community within 5 days of symptom onset.

Evaluation of the correlation between the access SARS-CoV-2 IgM and IgG II antibody tests with the SARS-CoV-2 surrogate virus neutralization test

Fully automated immunoassays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies that are strongly correlated with neutralization antibodies (nAbs) are clinically important because they enable the assessment of humoral immunity after infection and vaccination. Access SARS-CoV-2 immunoglobulin M (IgM) and immunoglobulin G (IgG) II antibody tests are semi-quantitative, fully automated immunoassays that detect anti-receptor-binding domain (RBD) antibodies and might reflect nAb levels in coronavirus disease 2019 (COVID-19). However, no studies have investigated the clinical utility of these tests in association with nAbs to date. To evaluate the clinical utility of Access SARS-CoV-2 IgM and IgG II antibody tests and their correlation with the SARS-CoV-2 surrogate virus neutralization test (sVNT) that measures nAbs in patients with COVID-19, we analyzed 54 convalescent serum samples from COVID-19 patients and 89 serum samples from non-COVID-19 patients. The presence of anti-RBD antibodies was detected using Access SARS-CoV-2 IgM and IgG II antibody tests, while nAbs were measured by sVNT. The sensitivity and specificity of sVNT were 94.4% and 98.9%, respectively. There were strong positive correlations between the inhibition values of sVNT and the results of the Access SARS-CoV-2 IgM (R = 0.95, R²  = 0.90, p < 0.001) and IgG II antibody tests (R = 0.96, R²  = 0.92, p < 0.001). In terms of the presence of nAbs, the sensitivity and specificity were 98.1% and 98.9% in the IgM assay and 100.0% and 100.0% in the IgG II assay, respectively. The Access SARS-CoV-2 IgM and IgG II antibody tests showed high sensitivity and specificity for the detection of nAbs in COVID-19 patients and might be alternatives for measuring nAbs.

On the effect of COVID-19 pandemic in the excess of human mortality. The case of Brazil and Spain

Excess of deaths is a technique used in epidemiology to assess the deaths caused by an unexpected event. For the present COVID–19 pandemic, we discuss the performance of some linear and nonlinear time series forecasting techniques widely used for modeling the actual pandemic and provide estimates for this metric from January 2020 to April 2021. We apply the results obtained to evaluate the evolution of the present pandemic in Brazil and Spain, which allows in particular to compare how well (or bad) these countries have managed the pandemic. For Brazil, our calculations refute the claim made by some officials that the present pandemic is “a little flu”. Some studies suggest that the virus could be lying dormant across the world before been detected for the first time. In that regard, our results show that there is no evidence of deaths by the virus in 2019.

Efficacy of systematic coronavirus screening by PCR and viral cultures in addition to triage in limiting the spread of SARS-CoV-2 within a hemodialysis unit

BACKGROUND

Patients with end-stage-renal-disease (ESRD) undergoing hemodialysis (HD) represent a vulnerable population for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, due to their intrinsic fragility and increased exposure to the virus. Therefore, applying effective screening strategies and infection control measures is essential to control the spread of the epidemic within hemodialysis centers.

OBJECTIVE

Description and evaluation of the efficacy of systematic screening by rt-PCR and viral cultures, in addition to triage to limit the spread of the epidemic. Evaluation of the performance of these tests using "post-hoc" SARS-CoV-2 serology as a surrogate marker of infection.

METHODS

One hundred and forty-four patients undergoing hemodialysis in the Nephrology-Hemodialysis center of CHU Brugmann, Brussels, benefited from systematic virological screening using viral cultures in asymptomatic patients, or molecular tests (rt-PCR) for symptomatic ones, in addition to general prevention measures. Post-hoc serology was performed in all patients.

RESULTS

Thirty-eight (26.3%) individuals were infected with SARS-CoV-2. Seventeen infected patients (44.7%) were asymptomatic and thus detected by viral culture. Our strategy allowed us to detect and isolate 97.4% of the infected patients, as proven by post-hoc serology. Only one patient, missed by clinical screening and sequential viral cultures, had a positive serology.

CONCLUSION

The implementation of a control and prevention strategy based on a systematic clinical and virological screening showed its effectiveness in limiting (and shortening) the spread of the SARS-CoV-2 epidemic within our hemodialysis unit.

Comparison of SARS-CoV-2 Detection by Rapid Antigen and by Three Commercial RT-qPCR Tests: A Study from Martin University Hospital in Slovakia

The global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is having a tremendous impact on the global economy, health care systems and the lives of almost all people in the world. The Central European country of Slovakia reached one of the highest daily mortality rates per 100,000 inhabitants in the first 3 months of 2021, despite implementing strong prophylactic measures, lockdowns and repeated nationwide antigen testing. The present study reports a comparison of the performance of the Standard Q COVID-19 antigen test (SD Biosensor) with three commercial RT-qPCR kits (vDetect COVID-19-MultiplexDX, gb SARS-CoV-2 Multiplex-GENERI BIOTECH Ltd. and Genvinset COVID-19 [E]-BDR Diagnostics) in the detection of infected individuals among employees of the Martin University Hospital in Slovakia. Health care providers, such as doctors and nurses, are classified as “critical infrastructure”, and there is no doubt about the huge impact that incorrect results could have on patients. Out of 1231 samples, 14 were evaluated as positive for SARS-CoV-2 antigen presence, and all of them were confirmed by RT-qPCR kit 1 and kit 2. As another 26 samples had a signal in the E gene, these 40 samples were re-isolated and subsequently re-analysed using the three kits, which detected the virus in 22, 23 and 12 cases, respectively. The results point to a divergence not only between antigen and RT-qPCR tests, but also within the “gold standard” RT-qPCR testing. Performance analysis of the diagnostic antigen test showed the positive predictive value (PPV) to be 100% and negative predictive value (NPV) to be 98.10%, indicating that 1.90% of individuals with a negative result were, in fact, positive. If these data are extrapolated to the national level, where the mean daily number of antigen tests was 250,000 in April 2021, it points to over 4700 people per day being misinterpreted and posing a risk of virus shedding. While mean Ct values of the samples that were both antigen and RT-qPCR positive were about 20 (kit 1: 20.47 and 20.16 for Sarbeco E and RdRP, kit 2: 19.37 and 19.99 for Sarbeco E and RdRP and kit 3: 17.47 for ORF1b/RdRP), mean Ct values of the samples that were antigen-negative but RT-qPCR-positive were about 30 (kit 1: 30.67 and 30.00 for Sarbeco E and RdRP, kit 2: 29.86 and 31.01 for Sarbeco E and RdRP and kit 3: 27.47 for ORF1b/RdRP). It confirms the advantage of antigen test in detecting the most infectious individuals with a higher viral load. However, the reporting of Ct values is still a matter of ongoing debates and should not be conducted without normalisation to standardised controls of known concentration.

Insights into household transmission of SARS-CoV-2 from a population-based serological survey

Understanding the risk of infection from household- and community-exposures and the transmissibility of asymptomatic infections is critical to SARS-CoV-2 control. Limited previous evidence is based primarily on virologic testing, which disproportionately misses mild and asymptomatic infections. Serologic measures are more likely to capture all previously infected individuals. We apply household transmission models to data from a cross-sectional, household-based population serosurvey of 4,534 people ≥5 years from 2,267 households enrolled April-June 2020 in Geneva, Switzerland. We found that the risk of infection from exposure to a single infected household member aged ≥5 years (17.3%,13.7-21.7) was more than three-times that of extra-household exposures over the first pandemic wave (5.1%,4.5-5.8). Young children had a lower risk of infection from household members. Working-age adults had the highest extra-household infection risk. Seropositive asymptomatic household members had 69.4% lower odds (95%CrI,31.8-88.8%) of infecting another household member compared to those reporting symptoms, accounting for 14.5% (95%CrI, 7.2-22.7%) of all household infections.

Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients

BACKGROUND

Understanding the false negative rates of SARS-CoV-2 RT-PCR testing is pivotal for the management of the COVID-19 pandemic and it has implications for patient management. Our aim was to determine the real-life clinical sensitivity of SARS-CoV-2 RT-PCR.

METHODS

This population-based retrospective study was conducted in March-April 2020 in the Helsinki Capital Region, Finland. Adults who were clinically suspected of SARS-CoV-2 infection and underwent SARS-CoV-2 RT-PCR testing, with sufficient data in their medical records for grading of clinical suspicion were eligible. In addition to examining the first RT-PCR test of repeat-tested individuals, we also used high clinical suspicion for COVID-19 as the reference standard for calculating the sensitivity of SARS-CoV-2 RT-PCR.

RESULTS

All 1,194 inpatients (mean [SD] age, 63.2 [18.3] years; 45.2% women) admitted to COVID-19 cohort wards during the study period were included. The outpatient cohort of 1,814 individuals (mean [SD] age, 45.4 [17.2] years; 69.1% women) was sampled from epidemiological line lists by systematic quasi-random sampling. The sensitivity (95% CI) for laboratory confirmed cases (repeat-tested patients) was 85.7% (81.5-89.1%) inpatients; 95.5% (92.2-97.5%) outpatients, 89.9% (88.2-92.1%) all. When also patients that were graded as high suspicion but never tested positive were included in the denominator, the sensitivity (95% CI) was: 67.5% (62.9-71.9%) inpatients; 34.9% (31.4-38.5%) outpatients; 47.3% (44.4-50.3%) all.

CONCLUSIONS

The clinical sensitivity of SARS-CoV-2 RT-PCR testing was only moderate at best. The relatively high false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations, and when using RT-PCR as a reference for other tests.

Investigating the utility of COVID-19 antibody testing in end-stage renal disease patients receiving haemodialysis: a cohort study in the United Kingdom

Background

End-stage renal disease (ESRD) patients receiving haemodialysis (HD) are a vulnerable group of patients with increased mortality from COVID-19. Despite improved understanding, the duration of host immunity following COVID-19 infection and role of serological testing alone or in addition to real-time reverse transcription polymerase chain reaction (rRT-PCR) testing in the HD population is not fully understood, which this study aimed to investigate.

Methods

There were two parts to this study. Between 15th March 2020 to 15th July 2020, patients receiving HD who tested positive on rRT-PCR for SARS-CoV-2 were recruited into the COVID-19 arm, whilst asymptomatic patients without a previous diagnosis of COVID-19 were recruited to the epidemiological arm of the Salford Kidney Study (SKS). All patients underwent monthly testing for anti-SARS-CoV-2 antibodies as per routine clinical practice since August 2020. The aims were twofold: firstly, to determine seroprevalence and COVID-19 exposure in the epidemiological arm; secondly, to assess duration of the antibody response in the COVID-19 arm. Baseline characteristics were reviewed between groups. Statistical analysis was performed using SPSS. Mann-Whitney U and Chi-squared tests were used for testing significance of difference between groups.

Results

In our total HD population of 411 patients, 32 were PCR-positive for COVID-19. Of the remaining patients, 237 were recruited into the SKS study, of whom 12 (5.1%) had detectable anti-SARS-CoV-2 antibodies. Of the 32 PCR-positive patients, 27 (84.4%) were symptomatic and 25 patients admitted to hospital due to their symptoms. Of the 22 patients in COVID-19 arm that underwent testing for anti-SARS-CoV-2 IgG antibodies beyond 7 months, all had detectable antibodies.

A higher proportion of the patients with COVID-19 were frail compared to patients without a diagnosis of COVID-19 (64.3% vs 34.1%, p = 0.003). Other characteristics were similar between the groups. Over a median follow up of 7 months, a higher number of deaths were recorded in patients with a diagnosis of COVID-19 compared to those without (18.7% vs 5.9%, p = 0.003).

Conclusions

Serological testing in the HD population is a valuable tool to determine seroprevalence, monitor exposure, and guide improvements for infection prevention and control (IPC) measures to help prevent local outbreaks. This study revealed HD patients mount a humoral response detectable until at least 7 months after COVID-19 infection and provides hope of similar protection with the vaccines recently approved.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02366-2.

Perspective: diagnostic laboratories should urgently develop T cell assays for SARS-CoV-2 infection

Introduction: Diagnostic tests play a critical role in the management of Sars-CoV-2, the virus responsible for COVID-19. There are two groups of tests, which are in widespread use to identify patients who have contracted the virus. The commonly used reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) test becomes negative once viral shedding ceases by approximately 2-3weeks. Antibody tests directed to viral antigens become positive after the second week of infection. IgG antibody responses to the virus are muted in children, pregnant females, and those with mild symptoms. IgA and IgM antibodies rapidly wane, although IgG antibodies directed to the receptor-binding domain (RBD) of the spike (S) glycoprotein are more durable. Current data show variability in the sensitivity of commercial and in-house antibody tests to SARS-CoV-2.Areas covered: The role of T cells in acute illness is uncertain, but long-term protection against the virus may rely on memory T cell responses. Measuring memory T cell responses is important for retrospective confirmation of cases, who may have been infected early in the pandemic before reliable RT-qPCR tests were available and whose SARS-CoV-2 antibodies may have become undetectable. Relevant peer-reviewed published references from PubMed are included up to 15 March 2021.Expert opinion: After surveying the literature, the authors present the case for urgent development of diagnostic T cell assays for SARS-CoV-2 by accredited laboratories.

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.