Analysis of the diagnostic value of serum specific antibody testing for coronavirus disease 2019

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.

Immunogenicity after CoronaVac vaccination

OBJECTIVE

This study aimed to investigate the seropositivity of CoronaVac-SinoVac vaccination in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) risk factors and comorbidities.

METHODS

Immunoglobulin (IgG) antibody responses were examined on the 21st day after the second dose of CoronaVac-SinoVac 6 μg vaccine on the 28th day. SARS-CoV-2 IgG antibody levels were measured by using the enzyme-linked immunosorbent assay method in vaccinated health care workers (n=134) (Group I), vaccinated polymerase chain reaction (PCR) (+) who had coronavirus-19 (COVID-19) disease (n=21) (Group II), and unvaccinated PCR (+) (n=28) (Group III) participants. Subgroups were formed in Group I according to the presence of COVID-19 risk factors and comorbidities (diabetes mellitus, cardiovascular disease, and asthma/allergy) and demographic data.

RESULTS

Seropositivity rates were 95.5, 100, and 89.3% for Groups I, II, and III, respectively. IgG antibody levels were found significantly higher in the group between the ages of 20-30 in group I compared to those aged 31-50 and over 50 (both p<0.01). It was found significantly higher in normal-weight individuals than in the overweight and obese group (both p<0.01). IgG antibody levels were found significantly lower in people with cardiovascular disease and diabetes mellitus compared with those who did not (p<0.05 and p<0.001, respectively). There was a negative correlation between IgG antibody response values and body mass index and age in Group I (r= -0.336, p<0.001 and r= -0.307, p<0.001, respectively).

CONCLUSION

IgG antibody values decrease with age and with increasing body mass index. The presence of comorbidities (i.e., diabetes mellitus and cardiovascular disease) decreased COVID-19 IgG antibody values.

Role and utility of COVID-19 laboratory testing in low-income and middle-income countries: protocol for rapid evidence synthesis

INTRODUCTION

Accurate and affordable laboratory testing is key to timely diagnosis and appropriate management of patients with COVID-19. New laboratory test protocols are released into the market under emergency use authorisation with limited evidence on diagnostic test accuracy. As such, robust evidence on the diagnostic accuracy and the costs of available tests is urgently needed to inform policy and practice especially in resource-limited settings. We aim to determine the diagnostic test accuracy, cost-effectiveness and utility of laboratory test strategies for COVID-19 in low-income and middle-income countries.

METHODS AND ANALYSIS

This will be a multistaged, protocol-driven systematic review conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for diagnostic test accuracy studies. We will search for relevant literature in at least six public health databases, including PubMed, Google Scholar, MEDLINE, Scopus, Web of Science and the WHO Global Index Medicus. In addition, we will search Cochrane Library, COVID-END and grey literature databases to identify additional relevant articles before double-screening and abstraction of data. We will conduct a structured narrative and quantitative synthesis of the results guided by the Fryback and Thornbury framework for assessing a diagnostic test. The primary outcome is COVID-19 diagnostic test accuracy. Using the GRADE approach specific to diagnostic accuracy tests, we will appraise the overall quality of evidence and report the results following the original PRISMA statement. The protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO; https://www.crd.york.ac.uk/prospero/).

ETHICS AND DISSEMINATION

Ethical review was done by the School of Biomedical Sciences Research Ethics Committee and the Uganda National Council for Science and Technology. The published article will be accessible to policy and decision makers. The findings of this review will guide clinical practice and policy decisions and highlight areas for future research.PROSPERO registration number CRD42020209528.

Detection of SARS-CoV-2 antibodies in pediatric patients: An Iranian referral hospital-based study

BACKGROUND

As the extent of the pandemic and its seroprevalence pattern has been less clarified in pediatrics to date, we aimed to conduct this study to investigate the clinical and laboratory characteristics of COVID-19 in Iranian children, with a focus on evaluating the antibody prevalence and its relation with the laboratory tests.

METHODS

All children with highly suspected COVID-19 were included. Anti-nucleoprotein SARS-CoV-2 were measured using SARS-CoV-2 immunoglobulin M (IgM) and SARS-CoV-2 IgG ELISA kits. Hypothesis testing was carried out through SPSS to unravel any association between the measurement tools and important clinical and laboratory characteristics.

RESULTS

In this study, 254 patients were evaluated and 117 cases (46%) were male. The nucleic acid detection results for patient 55 were negative, but the IgM and IgG results were positive. Totally, 190 patients were tested for IgM in which only 14 (7.3%) had positive tests. Positive IgG was detected in 51 (20%) out of 254 patients; among them, 30 patients had negative SARS-CoV-2 RT-PCR (59%). Lower level of platelets in IgG positive group in comparison with the IgG negative group was observed (P value: 0.015). Moreover, higher alanine aminotransferase (ALT) was observed in the in IgG positive group (P value: 0.02). In patients with positive IgM, relative hypocalcemia (median of 8.25; IQR: 8.02-8.62) was found which appeared to be significant (P value: 0.02).

CONCLUSION

This is the first largest study describing the SARS-CoV-2 seropositivity among children in Iran and provides important insight about the COVID-19 infection in children.