Antibody tests for identification of current and past infection with SARS-CoV-2.
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.
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.
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.
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).
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.
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.
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.
Fox T
，Geppert J
，Dinnes J
，Scandrett K
，Bigio J
，Sulis G
，Hettiarachchi D
，Mathangasinghe Y
，Weeratunga P
，Wickramasinghe D
，Bergman H
，Buckley BS
，Probyn K
，Sguassero Y
，Davenport C
，Cunningham J
，Dittrich S
，Emperador D
，Hooft L
，Leeflang MM
，McInnes MD
，Spijker R
，Struyf T
，Van den Bruel A
，Verbakel JY
，Takwoingi Y
，Taylor-Phillips S
，Deeks JJ
，Cochrane COVID-19 Diagnostic Test Accuracy Group
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《Cochrane Database of Systematic Reviews》
Dynamic IgG seropositivity after rollout of CoronaVac and BNT162b2 COVID-19 vaccines in Chile: a sentinel surveillance study.
By July 14, 2021, 81·3 % of adults (aged ≥18 years) in Chile had received a first SARS-CoV-2 vaccine and 72·3% had received a second SARS-CoV-2 vaccine, with the majority of people given Sinovac's inactivated CoronaVac vaccine (75·3% of vaccines dispensed) or Pfizer-BioNTech's mRNA BNT162b2 vaccine (20·9% of vaccines dispensed). Due to the absence of simultaneous real-world data for these vaccines, we aimed to compare SARS-CoV-2 IgG positivity between vaccines using a dynamic national monitoring strategy.
From March 12, 2021, 28 testing stations for SARS-CoV-2 IgG detection were installed in hotspots based on cellular-phone mobility tracking within the most populated cities in Chile. Individuals voluntarily approaching the testing stations were invited to do a lateral flow test by finger prick and respond to a questionnaire on sociodemographic characteristics, vaccination status (including type of vaccine if one was received), variables associated with SARS-CoV-2 exposure, and comorbidities. We compared the proportion of individuals testing positive for anti-SARS-CoV-2 IgG across sites by week since vaccination between recipients of CoronaVac and BNT162b2. Unvaccinated participants served as a control population and were matched to vaccinated individuals on the basis of date of presentation to the testing station, gender, and age group. Individuals were excluded from the analysis if they were younger than 18 years, had no declared gender, had an invalid IgG test result, had previously tested positive for SARS-CoV-2 infection on PCR, could not recall their vaccination status, or had been immunised against COVID-19 with vaccines other than CoronaVac or BNT162b2. Here, we report data collected up to July 2, 2021.
Of 64 813 individuals enrolled, 56 261 were included in the final analysis, of whom 33 533 (59·6%) had received at least one dose of the CoronaVac vaccine, 8947 (15·9%) had received at least one dose of the BNT162b2 vaccine, and 13 781 (24·5%) had not received a vaccine. SARS-CoV-2 IgG positivity during week 4 after the first dose of CoronaVac was 28·1% (95% CI 25·0-31·2; 220 of 783 individuals), reaching a peak of 77·4% (75·5-79·3; 1473 of 1902 individuals) during week 3 after the second dose. SARS-CoV-2 IgG positivity during week 4 after the first dose of the BNT162b2 vaccine was 79·4% (75·7-83·1; 367 of 462 individuals), increasing to 96·5% (94·9-98·1; 497 of 515 individuals) during week 3 after the second dose and remaining above 92% until the end of the study. For unvaccinated individuals, IgG seropositivity ranged from 6·0% (4·4-7·6; 49 of 810 individuals) to 18·7% (12·5-24·9; 28 of 150 individuals) during the 5 month period. Regression analyses showed that IgG seropositivity was significantly lower in men than women and in people with diabetes or chronic diseases for CoronaVac vaccine recipients (p<0·0001), and for individuals aged 60 years and older compared with people aged 18-39 years for both vaccines (p<0·0001), 3-16 weeks after the second dose.
IgG seropositivity was lower after CoronaVac than after BNT162b2 and declined over time since vaccination for CoronaVac recipients but not BNT162b2 recipients. Prolonged IgG monitoring will allow further evaluation of seropositivity overtime, providing data, in conjunction with effectiveness studies, for possible future re-assessment of vaccination strategies.
Instituto Sistemas Complejos de Ingeniería and Ministerio de Salud Chile.
For the Spanish translation of the abstract see Supplementary Materials section.
Sauré D
，O'Ryan M
，Torres JP
，Zuniga M
，Santelices E
，Basso LJ
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ResearchGate
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