Comparison of 2 fully automated tests detecting antibodies against nucleocapsid N and spike S1/S2 proteins in COVID-19

Capillary driven microfluidic sequential flow device for point-of-need ELISA: COVID-19 serology testing

A capillary-driven microfluidic sequential flow device, designed for eventual at-home or doctor's office use, was developed to perform an enzyme-linked immunosorbent assay (ELISA) for serology assays. Serology assays that detect SARS-CoV-2 antibodies can be used to determine prior infection, immunity status, and/or individual vaccination status and are typically run using well-plate ELISAs in centralized laboratories, but in this format SARs-CoV-2 serology tests are too expensive and/or slow for most situations. Instead, a point-of-need device that can be used at home or in doctor's offices for COVID-19 serology testing would provide critical information for managing infections and determining immune status. Lateral flow assays are common and easy to use, but lack the sensitivity needed to reliably detect SARS-CoV-2 antibodies in clinical samples. This work describes a microfluidic sequential flow device that is as simple to use as a lateral flow assay, but as sensitive as a well-plate ELISA through sequential delivery of reagents to the detection area using only capillary flow. The device utilizes a network of microfluidic channels made of transparency film and double-sided adhesive combined with paper pumps to drive flow. The geometry of the channels and storage pads enables automated sequential washing and reagent addition steps with two simple end-user steps. An enzyme label and colorimetric substrate produce an amplified, visible signal for increased sensitivity, while the integrated washing steps decrease false positives and increase reproducibility. Naked-eye detection can be used for qualitative results or a smartphone camera for quantitative analysis. The device detected antibodies at 2.8 ng mL-1 from whole blood, while a well-plate ELISA using the same capture and detection antibodies could detect 1.2 ng mL-1. The performance of the capillary-driven immunoassay (CaDI) system developed here was confirmed by demonstrating SARS-CoV-2 antibody detection, and we believe that the device represents a fundamental step forward in equipment-free point-of-care technology.

Label-free impedimetric immunosensor for point-of-care detection of COVID-19 antibodies

The COVID-19 pandemic has posed enormous challenges for existing diagnostic tools to detect and monitor pathogens. Therefore, there is a need to develop point-of-care (POC) devices to perform fast, accurate, and accessible diagnostic methods to detect infections and monitor immune responses. Devices most amenable to miniaturization and suitable for POC applications are biosensors based on electrochemical detection. We have developed an impedimetric immunosensor based on an interdigitated microelectrode array (IMA) to detect and monitor SARS-CoV-2 antibodies in human serum. Conjugation chemistry was applied to functionalize and covalently immobilize the spike protein (S-protein) of SARS-CoV-2 on the surface of the IMA to serve as the recognition layer and specifically bind anti-spike antibodies. Antibodies bound to the S-proteins in the recognition layer result in an increase in capacitance and a consequent change in the impedance of the system. The impedimetric immunosensor is label-free and uses non-Faradaic impedance with low nonperturbing AC voltage for detection. The sensitivity of a capacitive immunosensor can be enhanced by simply tuning the ionic strength of the sample solution. The device exhibits an LOD of 0.4 BAU/ml, as determined from the standard curve using WHO IS for anti-SARS-CoV-2 immunoglobulins; this LOD is similar to the corresponding LODs reported for all validated and established commercial assays, which range from 0.41 to 4.81 BAU/ml. The proof-of-concept biosensor has been demonstrated to detect anti-spike antibodies in sera from patients infected with COVID-19 within 1 h. Photolithographically microfabricated interdigitated microelectrode array sensor chips & label-free impedimetric detection of COVID-19 antibody.

Antibody tests for identification of current and past infection with SARS-CoV-2

BACKGROUND

The diagnostic challenges associated with the COVID-19 pandemic resulted in rapid development of diagnostic test methods for detecting SARS-CoV-2 infection. Serology tests to detect the presence of antibodies to SARS-CoV-2 enable detection of past infection and may detect cases of SARS-CoV-2 infection that were missed by earlier diagnostic tests. Understanding the diagnostic accuracy of serology tests for SARS-CoV-2 infection may enable development of effective diagnostic and management pathways, inform public health management decisions and understanding of SARS-CoV-2 epidemiology.

OBJECTIVES

To assess the accuracy of antibody tests, firstly, to determine if a person presenting in the community, or in primary or secondary care has current SARS-CoV-2 infection according to time after onset of infection and, secondly, to determine if a person has previously been infected with SARS-CoV-2. Sources of heterogeneity investigated included: timing of test, test method, SARS-CoV-2 antigen used, test brand, and reference standard for non-SARS-CoV-2 cases.

SEARCH METHODS

The COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) was searched on 30 September 2020. We included additional publications from the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre) 'COVID-19: Living map of the evidence' and the Norwegian Institute of Public Health 'NIPH systematic and living map on COVID-19 evidence'. We did not apply language restrictions.

SELECTION CRITERIA

We included test accuracy studies of any design that evaluated commercially produced serology tests, targeting IgG, IgM, IgA alone, or in combination. Studies must have provided data for sensitivity, that could be allocated to a predefined time period after onset of symptoms, or after a positive RT-PCR test. Small studies with fewer than 25 SARS-CoV-2 infection cases were excluded. We included any reference standard to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR), clinical diagnostic criteria, and pre-pandemic samples).

DATA COLLECTION AND ANALYSIS

We use standard screening procedures with three reviewers. Quality assessment (using the QUADAS-2 tool) and numeric study results were extracted independently by two people. Other study characteristics were extracted by one reviewer and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and, for meta-analysis, we fitted univariate random-effects logistic regression models for sensitivity by eligible time period and for specificity by reference standard group. Heterogeneity was investigated by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and summarised results for tests that were evaluated in 200 or more samples and that met a modification of UK Medicines and Healthcare products Regulatory Agency (MHRA) target performance criteria.

MAIN RESULTS

We included 178 separate studies (described in 177 study reports, with 45 as pre-prints) providing 527 test evaluations. The studies included 64,688 samples including 25,724 from people with confirmed SARS-CoV-2; most compared the accuracy of two or more assays (102/178, 57%). Participants with confirmed SARS-CoV-2 infection were most commonly hospital inpatients (78/178, 44%), and pre-pandemic samples were used by 45% (81/178) to estimate specificity. Over two-thirds of studies recruited participants based on known SARS-CoV-2 infection status (123/178, 69%). All studies were conducted prior to the introduction of SARS-CoV-2 vaccines and present data for naturally acquired antibody responses. Seventy-nine percent (141/178) of studies reported sensitivity by week after symptom onset and 66% (117/178) for convalescent phase infection. Studies evaluated enzyme-linked immunosorbent assays (ELISA) (165/527; 31%), chemiluminescent assays (CLIA) (167/527; 32%) or lateral flow assays (LFA) (188/527; 36%). Risk of bias was high because of participant selection (172, 97%); application and interpretation of the index test (35, 20%); weaknesses in the reference standard (38, 21%); and issues related to participant flow and timing (148, 82%). We judged that there were high concerns about the applicability of the evidence related to participants in 170 (96%) studies, and about the applicability of the reference standard in 162 (91%) studies. Average sensitivities for current SARS-CoV-2 infection increased by week after onset for all target antibodies. Average sensitivity for the combination of either IgG or IgM was 41.1% in week one (95% CI 38.1 to 44.2; 103 evaluations; 3881 samples, 1593 cases), 74.9% in week two (95% CI 72.4 to 77.3; 96 evaluations, 3948 samples, 2904 cases) and 88.0% by week three after onset of symptoms (95% CI 86.3 to 89.5; 103 evaluations, 2929 samples, 2571 cases). Average sensitivity during the convalescent phase of infection (up to a maximum of 100 days since onset of symptoms, where reported) was 89.8% for IgG (95% CI 88.5 to 90.9; 253 evaluations, 16,846 samples, 14,183 cases), 92.9% for IgG or IgM combined (95% CI 91.0 to 94.4; 108 evaluations, 3571 samples, 3206 cases) and 94.3% for total antibodies (95% CI 92.8 to 95.5; 58 evaluations, 7063 samples, 6652 cases). Average sensitivities for IgM alone followed a similar pattern but were of a lower test accuracy in every time slot. Average specificities were consistently high and precise, particularly for pre-pandemic samples which provide the least biased estimates of specificity (ranging from 98.6% for IgM to 99.8% for total antibodies). Subgroup analyses suggested small differences in sensitivity and specificity by test technology however heterogeneity in study results, timing of sample collection, and smaller sample numbers in some groups made comparisons difficult. For IgG, CLIAs were the most sensitive (convalescent-phase infection) and specific (pre-pandemic samples) compared to both ELISAs and LFAs (P < 0.001 for differences across test methods). The antigen(s) used (whether from the Spike-protein or nucleocapsid) appeared to have some effect on average sensitivity in the first weeks after onset but there was no clear evidence of an effect during convalescent-phase infection. Investigations of test performance by brand showed considerable variation in sensitivity between tests, and in results between studies evaluating the same test. For tests that were evaluated in 200 or more samples, the lower bound of the 95% CI for sensitivity was 90% or more for only a small number of tests (IgG, n = 5; IgG or IgM, n = 1; total antibodies, n = 4). More test brands met the MHRA minimum criteria for specificity of 98% or above (IgG, n = 16; IgG or IgM, n = 5; total antibodies, n = 7). Seven assays met the specified criteria for both sensitivity and specificity. In a low-prevalence (2%) setting, where antibody testing is used to diagnose COVID-19 in people with symptoms but who have had a negative PCR test, we would anticipate that 1 (1 to 2) case would be missed and 8 (5 to 15) would be falsely positive in 1000 people undergoing IgG or IgM testing in week three after onset of SARS-CoV-2 infection. In a seroprevalence survey, where prevalence of prior infection is 50%, we would anticipate that 51 (46 to 58) cases would be missed and 6 (5 to 7) would be falsely positive in 1000 people having IgG tests during the convalescent phase (21 to 100 days post-symptom onset or post-positive PCR) of SARS-CoV-2 infection.

AUTHORS' CONCLUSIONS

Some antibody tests could be a useful diagnostic tool for those in whom molecular- or antigen-based tests have failed to detect the SARS-CoV-2 virus, including in those with ongoing symptoms of acute infection (from week three onwards) or those presenting with post-acute sequelae of COVID-19. However, antibody tests have an increasing likelihood of detecting an immune response to infection as time since onset of infection progresses and have demonstrated adequate performance for detection of prior infection for sero-epidemiological purposes. The applicability of results for detection of vaccination-induced antibodies is uncertain.

Review of COVID-19 testing and diagnostic methods

More than six billion tests for COVID-19 has been already performed in the world. The testing for SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) virus and corresponding human antibodies is essential not only for diagnostics and treatment of the infection by medical institutions, but also as a pre-requisite for major semi-normal economic and social activities such as international flights, off line work and study in offices, access to malls, sport and social events. Accuracy, sensitivity, specificity, time to results and cost per test are essential parameters of those tests and even minimal improvement in any of them may have noticeable impact on life in the many countries of the world. We described, analyzed and compared methods of COVID-19 detection, while representing their parameters in 22 tables. Also, we compared test performance of some FDA approved test kits with clinical performance of some non-FDA approved methods just described in scientific literature. RT-PCR still remains a golden standard in detection of the virus, but a pressing need for alternative less expensive, more rapid, point of care methods is evident. Those methods that may eventually get developed to satisfy this need are explained, discussed, quantitatively compared. The review has a bioanalytical chemistry prospective, but it may be interesting for a broader circle of readers who are interested in understanding and improvement of COVID-19 testing, helping eventually to leave COVID-19 pandemic in the past.

Longitudinal SARS-CoV-2 Seroconversion Course and Antibody Levels by Blood Groups in Convalescent Plasma Donors in Turkey

Objective

The present study investigates the seroconversion time course of the IgG antibody against SARS-CoV-2 and ascertains whether its levels change according to the patient’s ABO blood group.

Method

A total of 36,003-convalescent plasma (CP) donations of 12,315 Turkish Red Crescent CP donors were analyzed. The ABO blood group of the CP donors was determined by Gel Centrifugation; and IgG was measured using the Euroimmun anti-SARS-CoV-2 ELISA. The differences in the distributions of mean IgG ratios among the different ABO blood groups were analyzed with One-Way ANOVA and Independent Samples T-test.

Results

Among the CP donors, 98.4% were male. An antibody response to SARS-CoV-2 was noted-although in a few CP donors- on the 244th day, and a significant association between the ABO blood groups and the mean IgG ratios was noted (p: 0.001). The highest (mean±SD) antibody level was observed in the AB blood group (39.5±15.7), followed by the B (37.9±11.5) and the A blood groups (36.6±10.7), while the lowest value was recorded in the O blood group (34.4±11.5). Significant differences between all paired groups were noted in pairwise comparisons. The Rh (-) blood group (37.4±13.6) had a significantly higher antibody level than the Rh (+) blood group (36.3±11.2) (p: 0.005).

Conclusion

An antibody response to SARS-CoV-2 was noted in a CP donor on the 244th day. The average IgG ratios were higher in the CP donors with the AB blood group, but lower in the O blood group. These results may be considered a valuable indication of the effectiveness of CP therapy used for the treatment of COVID-19 patients with clinically relevant blood types.

Adoption of improved neural network blade pattern recognition in prevention and control of corona virus disease-19 pandemic

To explore the adoption effect of improved neural network blade pattern in corona virus disease (COVID)-19, comparative analysis is implemented. First, the following hypotheses are proposed. I: in addition to the confirmed cases and deaths, people suspected of being infected are also involved in the spread of the epidemic. II: patients who have been cured may also develop secondary infections, so it is considered that there is still a link between cured cases and the spread of the epidemic. III: only the relevant data of the previous day is used to predict the epidemic prevention and control of the next day. Then, the epidemic data from February 1st to February 15th in X province were selected as the control. The combined neural network model is used for prevention and control prediction, and the prediction results of the traditional neural network model are compared. The results show that the predictions of the daily new cases by the five neural network models have little difference with the actual value, and the trend is basically consistent. However, there are still differences in some time nodes. The errors of neural network 1 on the 6th and network 3 on the 13th are large. The accuracy of the combined neural network prediction model is high, and there is little difference between the result and the actual value at each time node. The prediction of the cumulative number of diagnoses per day of the five neural network models is also analyzed, and the results are relatively ideal. In addition, the accuracy of the combined neural network prediction model is high, and the difference between the result and the actual value at each time node is relatively small. It is found that the standard deviations of neural networks 2 and 3 are relatively high through the comparison of the deviations. The deviation means of the five models were all relatively low, and the mean deviation and standard deviation of the combined neural network model are the lowest. It is found that the accuracy of prediction on the epidemic spread in this province is good by comparing the performance of each neural network model. Regarding various indicators, the prediction accuracy of the combined neural network model is higher than that of the other four models, and its performance is also the best. Finally, the MSE of the improved neural network model is lower compared with the traditional neural network model. Moreover, with the change of learning times, the change trend of MSE is constant (P < 0.05 for all). In short, the improved neural network blade model has better performance compared with that of the traditional neural network blade model. The prediction results of the epidemic situation are accurate, and the application effect is remarkable, so the proposed model is worthy of further promotion and application in the medical field.

SARS-CoV-2 serology: Validation of high-throughput chemiluminescent immunoassay (CLIA) platforms and a field study in British Columbia

Background

SARS-CoV-2 antibody testing is required for estimating population seroprevalence and vaccine response studies. It may also increase case identification when used as an adjunct to routine molecular testing. We performed a validation study and evaluated the use of automated high-throughput assays in a field study of COVID-19-affected care facilities.

Methods

Six automated assays were assessed: 1) DiaSorin LIAISON^TM SARS-CoV-2 S1/S2 IgG; 2) Abbott ARCHITECT^TM SARS-CoV-2 IgG; 3) Ortho VITROS^TM Anti-SARS-CoV-2 Total; 4) VITROS^TM Anti-SARS-CoV-2 IgG; 5) Siemens SARS-CoV-2 Total Assay; and 6) Roche Elecsys^TM Anti-SARS-CoV-2. The validation study included 107 samples (42 known positive; 65 presumed negative). The field study included 296 samples (92 PCR positive; 204 PCR negative or not PCR tested). All samples were tested by the six assays.

Results

All assays had sensitivities >90% in the field study, while in the validation study, 5/6 assays were >90% sensitive and DiaSorin was 79% sensitive. Specificities and negative predictive values were >95% for all assays. Field study estimated positive predictive values at 1–10% disease prevalence were 100% for Siemens, Abbott and Roche, while DiaSorin and Ortho assays had lower PPVs at 1% prevalence, but PPVs increased at 5–10% prevalence. In the field study, addition of serology increased diagnoses by 16% compared to PCR testing alone.

Conclusions

All assays evaluated in this study demonstrated high sensitivity and specificity for samples collected at least 14 days post-symptom onset, while sensitivity was variable 0–14 days after infection. The addition of serology to the outbreak investigations increased case detection by 16%.

Clinical Utility of Biosensing Platforms for Confirmation of SARS-CoV-2 Infection

Despite collaborative efforts from all countries, coronavirus disease 2019 (COVID-19) pandemic has been continuing to spread globally, forcing the world into social distancing period, making a special challenge for public healthcare system. Before vaccine widely available, the best approach to manage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is to achieve highest diagnostic accuracy by improving biosensor efficacy. For SARS-CoV-2 diagnostics, intensive attempts have been made by many scientists to ameliorate the drawback of current biosensors of SARS-CoV-2 in clinical diagnosis to offer benefits related to platform proposal, systematic analytical methods, system combination, and miniaturization. This review assesses ongoing research efforts aimed at developing integrated diagnostic tools to detect RNA viruses and their biomarkers for clinical diagnostics of SARS-CoV-2 infection and further highlights promising technology for SARS-CoV-2 specific diagnosis. The comparisons of SARS-CoV-2 biomarkers as well as their applicable biosensors in the field of clinical diagnosis were summarized to give scientists an advantage to develop superior diagnostic platforms. Furthermore, this review describes the prospects for this rapidly growing field of diagnostic research, raising further interest in analytical technology and strategic plan for future pandemics.

SARS-CoV-2 vaccines in advanced clinical trials: Where do we stand?

The ongoing SARS-CoV-2 pandemic has led to the focused application of resources and scientific expertise toward the goal of developing investigational vaccines to prevent COVID-19. The highly collaborative global efforts by private industry, governments and non-governmental organizations have resulted in a number of SARS-CoV-2 vaccine candidates moving to Phase III trials in a period of only months since the start of the pandemic. In this review, we provide an overview of the preclinical and clinical data on SARS-CoV-2 vaccines that are currently in Phase III clinical trials and in few cases authorized for emergency use. We further discuss relevant vaccine platforms and provide a discussion of SARS-CoV-2 antigens that may be targeted to increase the breadth and durability of vaccine responses.

Comparative Assessment of Sera from Individuals after S-Gene RNA-Based SARS-CoV-2 Vaccination with Spike-Protein-Based and Nucleocapsid-Based Serological Assays

Due to the beginning of vaccination against COVID-19, serological discrimination between vaccine-associated humoral response and serology-based surveillance of natural SARS-CoV-2 infections as well as breakthrough infections becomes an issue of relevance. Here, we assessed the differentiated effects of the application of an RNA vaccine using SARS-CoV-2 spike protein epitopes on the results of both anti-spike protein–based serology (EUROIMMUN) and anti-nucleocapsid-based serology (VIROTECH). A total of 80 serum samples from vaccinees acquired at different time points after vaccination was assessed. While positive or borderline serological response in the anti-spike protein assay was observed for all samples (90% both IgG and IgA, 6.3% IgA only, 3.8% borderline IgG only), only a single case of a falsely positive IgM was observed for the anti-nucleocapsid assay as expected due to this assay’s specificity. Positive anti-spike protein antibodies were already detectable in the second week after the first dose of vaccination, with higher titers after the second dose of the vaccine. In conclusion, the combined application of anti-spike protein–based serology and anti-nucleocapsid-based serology will provide a useful option for the discrimination of vaccination response and natural infection.

Radioligand Assay-Based Detection of Antibodies against SARS-CoV-2 in Hospital Workers Treating Patients with Severe COVID-19 in Japan

This study aimed to clarify whether infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is prevalent among the staff of a hospital providing treatment to patients with severe coronavirus disease 2019 (COVID-19) using radioligand assay (RLA). One thousand samples from the staff of a general hospital providing treatment to patients with severe COVID-19 were assayed for SARS-CoV-2 nucleocapsid protein (N) IgG using RLA. Nine patients with COVID-19 who had been treated in inpatient settings and had already recovered were used as control subjects, and 186 blood donor samples obtained more than 10 years ago were used as negative controls. Four of the 1000 samples showed apparently positive results, and approximately 10 or more samples showed slightly high counts. Interestingly, a few among the blood donor samples also showed slightly high values. To validate the results, antibody examinations using ELISA and neutralizing antibody tests were performed on 21 samples, and chemiluminescence immunoassay (CLIA) was performed on 201 samples, both resulting in a very high correlation. One blood donor sample showed slightly positive results in both RLA and CLIA, suggesting a cross-reaction. This study showed that five months after the pandemic began in Japan, the staff of a general hospital with a tertiary emergency medical facility had an extremely low seroprevalence of the antibodies against SARS-CoV-2. Further investigation will be needed to determine whether the slightly high results were due to cross-reactions or a low titer of anti-SARS-CoV-2 antibodies. The quantitative RLA was considered sensitive enough to detect low titers of antibodies.