IDSA Guidelines on the Diagnosis of COVID-19: Serologic Testing

Update History

August 18, 2020

Version 1.0 of the guideline has been released.

Abstract

Background: The role of serologic testing for SARS-CoV-2 has evolved during the pandemic as seroprevalence in global populations has increased. The Infectious Diseases Society of America (IDSA) convened an expert panel to perform a systematic review of the coronavirus disease 2019 (COVID-19) serology literature and construct updated best practice guidance related to SARS-CoV-2 serologic testing. This guideline is an update to the fourth in a series of rapid, frequently updated COVID-19 guidelines developed by IDSA.

Objective: To develop evidence-based recommendations and identify unmet research needs pertaining to the use of anti-SARS-CoV-2 antibody tests for diagnosis, decisions related to vaccination and administration of monoclonal antibodies or convalescent plasma in immunocompromised patients, and identification of a serologic correlate of immunity. 

Methods: A multidisciplinary panel of infectious diseases clinicians, clinical microbiologists and experts in systematic literature reviewed, identified, and prioritized clinical questions related to the use of SARS-CoV-2 serologic tests. Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make testing recommendations.

Results: The panel recommends against serologic testing to diagnose SARS-CoV-2 infection in the first two weeks after symptom onset (strong recommendations, low certainty of evidence). Serologic testing should not be used to provide evidence of COVID-19 in symptomatic patients with a high clinical suspicion and repeatedly negative nucleic acid amplification test results (strong recommendation, very low certainty of evidence). Serologic testing may assist with the diagnosis of multisystem inflammatory syndrome in children (strong recommendation, very low certainty of evidence). To seek evidence for prior SARS-CoV-2 infection, the panel suggests testing for IgG, IgG/IgM, or total antibodies to nucleocapsid protein three to five weeks after symptom onset (conditional recommendation, low certainty of evidence). In individuals with previous SARS-CoV-2 infection or vaccination, we suggest against routine serologic testing given no demonstrated benefit to improving patient outcomes (conditional recommendation, very low certainty of evidence.) The panel acknowledges further that a negative spike antibody test may be a useful metric to identify immunocompromised patients who are candidates for immune therapy.

Conclusions: The high seroprevalence of antibodies against SARS-CoV-2 worldwide limits the utility of detecting anti-SARS CoV-2 antibody. The certainty of available evidence supporting the use of serology for diagnosis was graded as very low to low. Future studies should use serologic assays calibrated to a common reference standard.

Executive Summary

As of December 2022, more than 96% of the U.S. population was estimated to have antibodies against SARS-CoV-2 [1]. While global seroprevalence data are more sparse, similar estimates have been reported from numerous other countries and regions [2]. The utility of anti-SARS-CoV-2 antibody testing for diagnostic or epidemiologic purposes has declined as global seroprevalence due to vaccination and natural infection has increased. The current IDSA Guideline for Serologic Testing in the Diagnosis of SARS-COV-2 Infection reflects this evolution. The panel now makes a strong (versus weak) recommendation against serologic testing to diagnose acute COVID-19 in the first 2 weeks after symptom onset. Similarly, the updated guideline recommends strongly against (versus previously recommending weakly for) using IgG antibodies to provide evidence of COVID-19 in symptomatic patients with a high clinical suspicion and repeatedly negative nucleic acid amplification tests (NAAT). Unlike NAAT which detect viral RNA, antibody-based assays measure the host’s humoral immune response to current or past infection. Anti-SARS-CoV-2 antibodies typically become detectable more than two weeks after onset of symptoms (Figure 1). As a result, SARS-CoV-2 serology lacks sufficient sensitivity to confidently exclude a diagnosis of coronavirus disease 2019 (COVID-19) when antibodies are not detected in the acute phase of illness. Furthermore, given the very high baseline seroprevalence of anti-SARS-CoV-2 antibodies in most populations, a positive serologic result may likely be due to vaccination, or a distant history of COVID-19 as opposed to an acute or recent SARS-CoV-2 infection.

For the current update, the panel identified very few clinical scenarios in which serologic testing may be useful. The first to assist in the diagnosis of Multisystem Inflammatory Syndrome in children (MIS-C). In addition, the panel agreed that a negative spike antibody test may be a useful metric to identify immunocompromised patients who are candidates for immune therapy, such as convalescent plasma or monoclonal antibodies, if such therapy were available, or to prioritize administration of monoclonal therapies when supplies are limited. When antibody testing is done, the panel makes a weak recommendation for using SARS-CoV-2 IgG, IgG/IgM, or total antibodies and against using IgM, due to lower sensitivity of IgM alone. IgA tests were not considered in the current, updated guideline because of their past poor performance and because they are rarely tested in clinical laboratories.

The current IDSA guideline includes two new recommendations. The first is a weak recommendation to use serologic assays that target nucleocapsid protein rather than spike protein when evidence of prior COVID-19 is desired. This recommendation is made to improve the specificity of testing in highly vaccinated populations, since most available vaccines result in formation of anti-spike antibodies, although some inactivated whole virus vaccines (e.g., CoronaVac and BBIBP-CorV, manufactured by Sinovac and Sinopharm, respectively) can also result in formation of anti-nucleocapsid antibodies.

The second new recommendation suggests against routine serologic testing in patients with previous SARS-CoV-2 infection or vaccination, given that no demonstrated benefits for improving patient outcomes were identified. Data were found to support higher levels of binding antibodies or the presence of neutralizing antibodies as being associated with protection against SARS-CoV-2 infection, but a single titer that predicts protection was not identified.

Summarized below are specific recommendations and comments related to the use of SARS-CoV-2 serologic testing in clinical practice. A detailed description of background, methods, evidence summary and rationales that support each recommendation can be found online and in the full text.

Recommendations

Recommendation 1: The IDSA panel recommends against using serologic testing to diagnose SARS-CoV-2 infection during the first two weeks following symptom onset (strong recommendation, low certainty of evidence).  

Remarks:

• Most studies included in this recommendation’s literature review assessed unvaccinated individuals and so the panel’s findings might not apply to individuals who have been vaccinated, especially with respect to specificity, rendering test accuracy worse than presented here.
• Similarly, in today’s population there is a higher likelihood of prior SARS-CoV-2 infection than assessed in the included studies, which could also negatively affect specificity, rendering test accuracy worse than presented.
• Analogous to other respiratory viruses where non-serologic tests are preferred for diagnosis of acute infection, serologic testing should not be routinely performed for diagnosis of acute COVID-19.

Recommendation 2: The IDSA panel recommends against using IgG antibodies to provide evidence of COVID-19 in symptomatic patients with a high clinical suspicion and repeatedly negative NAAT (strong recommendation, very low certainty of evidence).  

Remarks:

• Contemporary populations are more likely to have had prior SARS-CoV-2 infection or vaccination than the populations assessed in the included studies, which could negatively affect pooled specificity calculations, rendering test accuracy worse than presented here.

Recommendation 3:  To assist with the diagnosis of multisystem inflammatory syndrome in children (MIS-C), the IDSA panel recommends using both IgG antibody testing and NAAT to provide evidence of current or recent past COVID-19 (strong recommendation, very low certainty of evidence).

Remarks:

• Combining IgG antibody testing and NAAT may improve both the ability to diagnose MIS-C and to rule it out, compared to using NAAT alone. Knowing the patient’s vaccination and COVID-19 history may be helpful in interpreting serology results.
• Differentiating MIS-C from conditions with overlapping symptomatology, such as Kawasaki disease, is important because Kawasaki disease requires treatment with specific therapies such as intravenous immunoglobulin or rituximab if diagnosed. The two diseases also differ in terms of potential complications and need for long-term medication and follow-up.
• The January 2023 definition of MIS-C agreed upon by U.S. Centers for Disease Control and Prevention (CDC) and other public health officials requires evidence of current or recent SARS-CoV-2 infection by PCR, antigen, or serologic testing [3].

Recommendation 4: When evidence of previous SARS-CoV-2 infection is desired, the IDSA panel suggests testing for SARS-CoV-2 IgG, IgG/IgM, or total antibodies three to five weeks after symptom onset and against testing for SARS-CoV-2 IgM (conditional recommendation, low certainty of evidence).

Remarks:

• SARS-CoV-2 NAAT and antigen tests have superior performance characteristics for diagnosis of COVID-19, compared to serologic testing.
• There are very limited situations in which SARS-CoV-2 antibody testing might be useful, e.g., in helping to diagnose MIS-C.

Recommendation 5: When evidence of prior SARS-CoV-2 infection is desired, the IDSA panel suggests using serologic assays that target nucleocapsid protein rather than spike protein (conditional recommendation, low certainty of evidence).

Remarks:

• Most available vaccines result in formation of only anti-spike antibodies but some (e.g., CoronaVac and BBIBP-CorV, manufactured by Sinovac and Sinopharm, respectively) which contain inactivated whole virus, can also result in formation of anti-nucleocapsid antibodies [4].
• Given the high prevalence of vaccination in most populations and the persistence of anti-spike antibodies over time, detection of anti-spike antibodies has low positive predictive value for diagnosis of recent COVID-19 in most individuals.

Recommendation 6: In individuals with previous SARS-CoV-2 infection or vaccination, the IDSA panel suggests against routine serologic testing given no demonstrated benefit to improving patient outcomes (conditional recommendation, very low certainty of evidence).

Remarks

• Serologic testing may be useful for diagnosing MIS-C in pediatric patients, especially when NAAT or antigen testing is negative, to provide evidence of recent COVID-19 (see Recommendation 3 above).
• A negative spike antibody test may be a useful metric to identify immunocompromised patients who are candidates for immune therapy such as convalescent plasma or monoclonal antibodies, if such therapies were available, or to prioritize administration of monoclonal therapies when supplies are limited.

Background

Since its emergence in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over 760 million confirmed infections and nearly 7 million deaths worldwide [5].  Definitive diagnosis of coronavirus disease 19 (COVID-19) and asymptomatic SARS-CoV-2 infection rely on the direct detection of virus-specific RNA or virus-specific glycoprotein antigens in respiratory specimens. Serologic tests that use blood samples to detect the host antibody response to SARS-CoV-2 cannot diagnose SARS-CoV-2 infection or COVID-19, nor can they identify persons who are protected from future infection, but they may help confirm past infection. The current high seroprevalence of anti-SARS-Co-V-2 antibodies in most populations limits the utility of antibody testing for clinical or epidemiologic purposes.

Coronavirus genomes encode four major structural proteins including spike (S), envelope (E), membrane (M) and nucleocapsid (N). Both the S and N proteins of SARS-CoV-2 are immunogenic in humans; current serologic tests target antibodies directed against these antigens [6]. The S protein is the most exposed viral protein and is responsible for viral attachment and entry into host cells via binding to the angiotensin-converting enzyme 2 (ACE-2) receptor [7]. The S protein is comprised of an N-terminal S1 subunit, involved in virus-receptor binding, and a C-terminal S2 subunit involved in fusion to the host cell membrane. The S1 subunit is further divided into an N terminal domain (NTD) and a receptor binding domain (RBD). There has been particular focus on the SARS-CoV-2 RBD for vaccine development and targeted antibody therapies because neutralizing antibodies against this region effectively block viral entry [8, 9]. The N protein is an RNA-binding protein that is abundantly expressed during infection and plays a role in RNA transcription and replication [10].

There are two general types of antibodies, neutralizing antibodies (nAbs) and non-neutralizing (also known as binding antibodies) [11]. Neutralization is defined as the loss of infectivity that occurs when a nAb binds to a viral particle. Virus-specific or vaccine-induced nAbs can play a role in controlling viral infection, but definitive data is lacking to know whether individuals with detectable anti-SARS-CoV-2 nAbs are protected against reinfection. In comparison, binding antibodies are characterized by their inability to prevent viral infection of permissive cells. Regardless of their function, both types of virus-specific antibodies are potentially useful as diagnostic indicators of past infection or vaccination.

Commercially available anti-SARS-CoV-2 antibody tests use different technologies to qualitatively measure single immunoglobulin classes (IgM, IgG or IgA) or total antibody, and to differentiate nAbs from binding antibodies. IgM antibodies directed against microorganisms are typically produced first after infection and are used as a measure of recent infection. IgG antibodies generally develop later than IgM antibodies and remain elevated for months to years after infection. Although IgM antibodies can be detected within the first two weeks of symptoms in some patients, SARS-CoV-2 infection appears unusual in that IgM and IgG more commonly rise together, more than two weeks after the onset of symptoms [12]. Secretory IgA is important for mucosal immunity. IgA can also be detected systemically in certain types of infection including SARS-CoV-2, but comparatively little is known about the kinetics of IgA in blood. The components of “total antibody” presumably include IgM and IgG and theoretically other antigen-specific immunoglobulins as well.

The most common clinical diagnostic platforms utilized for SARS-CoV-2 include lateral flow (LF) devices, enzyme linked immunosorbent assays (ELISA) and chemiluminescent immunoassays (CIA). Lateral flow assays typically require a drop of blood (or serum or plasma) applied to a test strip, with results read in approximately 15-30 minutes. These devices are suitable for point-of-care testing and have potential to be deployed in the field as a part of large serological surveys. ELISA comes in a variety of different formats. Typically, a bound antigen-antibody complex is detected using a type-specific secondary antibody linked to a substrate that generates a colorimetric or fluorescent signal. CIA methods are similar to ELISA but use chemical probes that emit light instead of enzymatic substrates. Both ELISA and CIA are clinical laboratory-based methods amendable to high throughput testing using serum, plasma, or potentially dried blood spots. At this time, neutralization assays are mainly used in research settings or offered as laboratory developed tests by reference laboratories.

As of this writing, most commercially available SARS-CoV-2 antibody tests marketed in the U.S. have Emergency Use Authorization (EUA) through the U.S. Food and Drug Administration (FDA). Early in the pandemic, however, official EUA review was voluntary. Test developers were expected only to internally validate their tests and notify the FDA of their intent to market. As a result, the market was flooded with poorly performing assays. In response the FDA subsequently issued a “removed” test list that includes tests with significant performance problems, assays for which official EUA review was not appropriately submitted or assays voluntarily withdrawn by the developer. Subsequently, on September 23, 2021, the FDA revised the EUAs of certain molecular, antigen, and serology tests to establish additional Conditions of Authorization in response to the ongoing emergence of new SARS-CoV-2 variants.  

The lifting of the Federal COVID-19 Public Health Emergency on May 11, 2023 was accompanied by release of a transition plan by the FDA with recommendations for marketing submission and other actions needed to enable ongoing use of COVID-19 laboratory tests that were issued EUA [13].

Many serologic tests for SARS-CoV-2 are commercially available. While most of these assays are currently available under FDA EUA, it is expected that many will soon achieve FDA clearance. The speed of development has continued to outpace rigorous assessments of test performance. In response, IDSA convened an expert panel to systematically review the available serologic literature, compare pooled estimates of test accuracy and make evidence-based recommendations for informed use in clinical practice.

Methods

This guideline was developed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach for evidence assessment. This guideline serves as the second update to the original IDSA guidelines on the serologic testing of COVID-19 [14]. The list of questions addressed in the initial guideline and the current update can be found in Table s1.

Panel Composition

The panel was composed of clinicians and clinical microbiologists who are members of the Infectious Diseases Society of America (IDSA), the American Society for Microbiology (ASM), the Society for Healthcare Epidemiology of America (SHEA), and the Pediatric Infectious Diseases Society (PIDS). They represented the disciplines of infectious diseases, pediatrics, clinical microbiology, and healthcare epidemiology. The Evidence Foundation provided technical support and guideline methodologists for the development of this guideline.

Disclosure and Management of Potential Conflicts of Interest

The conflict of interest (COI) review group included two representatives from IDSA who were responsible for reviewing, evaluating and approving all disclosures. All members of the expert panel complied with the COI process for reviewing and managing conflicts of interest, which required disclosure of any financial, intellectual, or other interest that might be construed as constituting an actual, potential, or apparent conflict, regardless of relevancy to the guideline topic. The assessment of disclosed relationships for possible COI was based on the relative weight of the financial relationship (i.e., monetary amount) and the relevance of the relationship (i.e., the degree to which an association might reasonably be interpreted by an independent observer as related to the topic or recommendation of consideration). The COI review group ensured that the majority of the panel and chair were without potential relevant (related to the topic) conflicts. The chair and all members of the technical team were determined to have no COIs relevant to the guidelines.

Question Generation

Clinical questions were developed into a PICO format (Population, Intervention, Comparison, Outcomes) [15] prior to the first panel meeting. Using online surveys, the panel members decided to reassess the evidence and the recommendation for 4 PICO questions that were addressed in the initial guideline in 2020 [14]. Additionally, panel members prioritized 3 new questions that have emerged as clinically important (Table s1). Because very limited data were identified to answer two of these questions, they were combined in a single recommendation (Recommendation 6.)

Search Strategy

The National Institute of Health and Care Excellence (NICE) and the Centers for Disease Control and Prevention (CDC) highly sensitive search was reviewed by the methodologists in consultation with an experienced information specialist and was determined to have high sensitivity. Terms identified in the PICO questions and the term “COVID” were added to the search strategy used for the databases PubMed, Embase, and Cochrane for antigen, molecular, and serology diagnostic test terms (Table s2). Monthly searches were performed from 2019 through January 1, 2023. During September 2022, with the help of an information specialist, improvements to the search strategy were made to reflect the covid19/sarscov2 epidemic and remove general terms like “coronavirus” which may pick up articles that are about a different virus. (Table s2). Any reference lists and literature suggested by the panelists were also reviewed throughout the guideline development process. 

Screening and Study Selection

A member of the review team screened the titles and abstracts of the references identified by the search strategy and assessed if the study addressed antigen, molecular, or serologic testing. A member of the review team then assessed the studies addressing serologic testing in more detail using the full texts of the studies under consideration for potential inclusion in the review. When the inclusion of an article was debated, it was first resolved through discussion within the review team. In the case of disagreement, articles were discussed with the panel members to make the final decision.

Studies were included if they reported data on the diagnostic test accuracy of anti-SARS-CoV-2 IgM, IgG, and/or total antibody tests compared to NAAT as the reference standard. Studies were excluded if the tests evaluated were not EUA or European Commission (CE) approved, studies with fewer than 30 patients/samples, studies with incomplete test accuracy information (i.e., reported sensitivity without specificity), studies reporting atypical serology sample site collection (e.g., dried blood spots, mucosal fluids), machine learning studies, protocols, preprints, and abstracts.

Data Collection and Analysis

A member of the review team completed data extraction using a standardized data extraction form. in duplicate. Study characteristics (authors, publication year, country, study design, inclusion criteria, age, gender), index test information (timing from onset of symptoms, sample type, target antigen, platform, immunoglobulin class, FDA EUA status, and European Economic Area CE marking status), reference test (name of test, sample type), and diagnostic test accuracy results (true and false positives and negatives) were extracted.

For each study, the sensitivity and specificity of the diagnostic index test were calculated and the Clopper–Pearson method used to estimate 95% confidence intervals. We then fit the random-effects bivariate binomial model of Chu and Cole [16] to pool accuracy estimates using  the glmer function of the lme4 package in R (version 4.1.2). To pool accuracy estimates for analyses including fewer than 5 studies, we fit a fixed effects model as implemented in the meta package in R (version 4.1.2). Forest plots were used to plot individual and summary estimates and conducted subgroup analyses to explore heterogeneity. To evaluate the effects of study design on results, sensitivity analyses were performed by including or excluding case control studies and assessing the effect on pooled results of test accuracy.  

Risk of Bias and Certainty of Evidence

The Quality Assessment of Diagnostic Studies (QUADAS)-2 revised tool was used to assess the risk of bias in the test accuracy studies [17] (Table s3). When assessing evidence other than test accuracy in the studies of intervention, the Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-I) was used [18] (Table s4). The GRADE framework was used to assess the overall certainty by evaluating the body of evidence for each outcome on the following domains: risk of bias, imprecision, inconsistency, indirectness, and publication bias [19, 20]. GRADE summary of findings tables were developed using the GRADEpro Guideline Development Tool [21].

Evidence to Recommendations

The panel considered the core elements of GRADE evidence in the decision process, including certainty of evidence and balance between desirable and undesirable effects. Additional domains were acknowledged where applicable (e.g., feasibility, resource use, acceptability). For all recommendations, the expert panelists reached consensus. Voting rules were agreed on prior to the panel meeting for situations when consensus could not be reached.

As per GRADE methodology, recommendations were labeled as “strong” or “conditional.” The words “we recommend” indicate strong recommendations and “we suggest” indicate conditional recommendations. Figure 2 provides the suggested interpretation of strong and weak recommendations for patients, clinicians, and healthcare policymakers. For recommendations where the comparators are not formally stated, the comparison of interest was implicitly referred to as “not using the test.” Some recommendations acknowledge a current “knowledge gap” and aim at avoiding premature favorable recommendations for test use and to avoid encouraging the rapid diffusion of potentially non-useful tests.

Revision Process

The draft guideline underwent review for approval by the Standards and Practice Guidelines Subcommittee of the IDSA and by the IDSA Board of Directors external to the guideline development panel. The guideline was reviewed and endorsed by ASM, PIDS and SHEA.

Updating Process

Regular, frequent screening of the literature will take place to determine the need for revisions based on the likelihood that any new data will have an impact on the recommendations. If necessary, the entire expert panel will be reconvened to discuss potential changes.

Search Results

Systematic review of the literature identified 30,645 references of which 163 informed the evidence base for this guideline recommendations (Figure s1). Characteristics of the included studies can be found in (Tables s5-s9).

Recommendation 1: Serology Testing in the First Two Weeks After Symptom Onset

Recommendation 1: The IDSA panel recommends against using serologic testing to diagnose SARS-CoV-2 infection during the first two weeks following symptom onset (strong recommendation, low certainty of evidence).

Remarks:

• Most studies included in this recommendation’s literature review assessed unvaccinated individuals and so the panel’s findings might not apply to individuals who have been vaccinated, especially with respect to specificity, rendering test accuracy worse than presented here.
• Similarly, in today’s population there is a higher likelihood of prior SARS-CoV-2 infection than assessed in the included studies, which could also negatively affect specificity, rendering test accuracy worse than presented.
• Analogous to other respiratory viruses where non-serologic tests are preferred for diagnosis of acute infection, serologic testing should not be performed routinely for diagnosis of acute COVID-19.

Summary of the evidence

We found no direct evidence of patient- or population-centered outcomes of testing versus no testing in symptomatic patients. Therefore, the panel relied on diagnostic test accuracy data to inform this recommendation.

Using the applied search strategy, we identified 111 studies [22-132] that assessed diagnostic test accuracy of serologic tests (IgM, IgG, IgM or IgG) compared to a SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) test in the first two weeks after symptom onset. (Tables 1a-1c). Studies used varied sources for negative controls, including samples collected from healthy individuals, patients who had other respiratory or non-respiratory infections, patients with autoimmune diseases whose blood had been collected prior to the COVID-19 pandemic, symptomatic patients with negative NAAT for SARS-CoV-2, and/or patients hospitalized for reasons other than COVID-19. While most studies used case-control designs, some used longitudinal or cross-sectional cohort designs. For assays that detected and differentiated IgM from IgG using the same platform, an interpretation of “IgM or IgG” was considered a positive test (i.e., detection of one of the two immunoglobulins qualified as a positive test).

The total number of patient samples across all included studies ranged from 1,137 to 5,161 and 4,388 to 22,321, for sensitivity and specificity analyses, respectively (Figures s2a-s7b). The pooled sensitivity at one week after symptom onset ranged from 24 to 35% and at two weeks ranged from 64 to 74%, while the pooled specificity ranged from 98 to 99% (Tables 1a-1c).

The quality of evidence that informed sensitivity determinations was low, while the quality of evidence that informed specificity was moderate. Quality was rated downward for both sensitivity and specificity due to serious indirectness and unexplained inconsistency in sensitivity. Concerns with indirectness stemmed from the participants being evaluated in the pre-vaccination era, and before widespread infection.  Given the very high global estimates of current SARS-CoV-2 seroprevalence, the test accuracy estimated from these studies would likely not reflect performance today.

Benefits and harms

If performed within 14 days of onset of symptomatic infection, the low sensitivity of serologic tests can lead to a high number of falsely negative results. Individuals who test falsely negative would be classified as uninfected, when, in fact, they would be infected but they would not have developed a detectable antibody response. Although the specificity of serologic testing was calculated to be 98-99%, this likely does not represent performance in vaccinated and/or previously infected individuals, who were not assessed in the included studies. Tests with low specificity can lead to false positive result for recent infection at any time point of testing. A positive result can lead to the incorrect conclusion that an individual has been recently infected, thus eliminating the search for the true etiology of their symptoms, or resulting in unnecessary treatment or isolation.

Other considerations

IgM antibody responses often occur earlier after infection compared to IgG antibody responses. In contrast, with SARS-CoV-2 infection, there does not appear to be a substantial difference in the time after infection when IgM and IgG antibodies can be detected. At one week after onset of symptoms, the pooled sensitivity for IgM tests was 27% compared to 24% for IgG tests, and at two weeks post onset of symptoms, the pooled sensitivity of IgM tests was 64% compared to 66% for IgG tests.

Conclusions and research needs for this recommendation

Serologic testing should not be performed routinely for diagnosis of acute COVID-19, analogous to the situation with other respiratory viruses. Achieving a better understanding of the role of serology as a correlate of protection with current circulating variants is a research need, especially in populations at highest risk of severe disease such as the elderly and immunocompromised. Correlation of viral RNA shedding and culture positivity (or other surrogate for infectivity) should be studied relative to immunoglobulin titers over time to help inform isolation guidelines for patients with COVID-19.

Recommendation 2: Serology Testing in Individuals with High Clinical Suspicion for SARS-CoV-2 Infection and Negative NAAT

Recommendation 2: The IDSA panel recommends against using IgG antibodies to provide evidence of COVID-19 in symptomatic patients with a high clinical suspicion and repeatedly negative NAAT (strong recommendation, very low certainty of evidence).

Remarks

• Contemporary populations are more likely to have had prior SARS-CoV-2 infection or vaccination than the populations assessed in the included studies, which could negatively affect pooled specificity calculations, rendering test accuracy worse than presented here.

Summary of the evidence

We identified 19 studies [30, 109, 130, 133-148] that compared the diagnostic test accuracy of serologic tests among patients with high clinical suspicion for COVID-19 and negative NAAT throughout the course of their illness. The percent of PCR-negative/IgG-positive test results ranged from 0% to 93% with most studies reporting this test result combination for fewer than 50% of samples. The percent of samples with PCR-negative/IgM-positive test results ranged from 2% to 83%, and the percent of samples with PCR-negative/IgM- or IgG-positive test results ranged from 11% to 62%. Finally, the percent of samples that yielded PCR-negative/total antibody-positive results ranged between 0% and 60% These studies varied in terms of assay (chemistry, method, platform) and the timing of testing (e.g., <20 days versus >15 days) (Table s6).

The overall certainty of the evidence was very low due to concerns for risk of bias (case-control study design) and imprecision (as a result of small sample size). The use of clinical symptoms as a reference standard in some studies might have resulted in misclassification (i.e., labeling non-infected patients as true positive cases based on symptoms and serology alone).

Benefits and harms

The panel’s consensus opinion was that the clinical benefit of performing SARS-CoV-2 serologic testing in patients with high clinical suspicion for COVID-19 and repeatedly negative SARS-CoV-2 NAAT is low. This is because contemporary human populations have high SARS-CoV-2 seroprevalence due to natural, vaccine-induced, or hybrid immune responses. A positive serologic result for a symptomatic patient who tests repeatedly negative by NAAT may be attributed to vaccination and/or past infection as readily as to recent SARS-CoV-2 infection. Concluding that a positive serologic test is responsible for a patient’s current symptoms can lead to misdiagnosis, particularly in periods when SARS-CoV-2 circulation is low and other respiratory virus circulation is high. In individuals who have not been vaccinated or previously infected (the population included in this recommendation’s literature review), the negative predictive value of a SARS-CoV-2 serologic test is high when performed more than 2 weeks after symptom onset. In this instance, negative serologic results should prompt further evaluation of the patients’ symptoms for alternative etiologies, if symptoms persist.

Other considerations

No SARS-CoV-2 serologic test can differentiate between recent or remote infection. Serologic tests cannot differentiate a serologic response to a vaccine antigen from a response elicited by recent or remote infection.

Conclusions and research needs for this recommendation

Assessing anti-SARS-CoV-2 antibodies provides no added benefit over repeat NAAT for the diagnosis of acute COVID-19and may lead to diagnostic uncertainty. Further research on the role of serologic and immunologic testing for diagnosis or management of long-COVID may be warranted.

Recommendation 3: Serologic Testing in Pediatric Patients with Suspicion of MIS-C

Recommendation 3:  To assist with the diagnosis of multisystem inflammatory syndrome in children (MIS-C), the IDSA panel recommends using both IgG antibody testing and NAAT to provide evidence of current or recent past COVID-19 (strong recommendation, very low certainty of evidence).

Remarks:

• Combining IgG antibody testing with NAAT may improve both the ability to diagnose MIS-C and to rule it out, compared to using NAAT alone. Knowing the patient’s vaccination and COVID-19 history may be helpful in interpreting serology results.
• Differentiating MIS-C from conditions with overlapping symptomatology, such as Kawasaki disease, is important because Kawasaki disease requires treatment with specific therapies such as intravenous immunoglobulin or rituximab if diagnosed. The two diseases also differ in terms of potential complications and need for long-term medication and follow-up.
• The January 2023 definition of MIS-C agreed upon by U.S. CDC and other public health officials requires evidence of current or recent SARS-CoV-2 infection by PCR, antigen, or serologic testing [3].

Summary of the evidence

We identified 10 case series [149-158] that evaluated the use of SARS-CoV-2 serologic tests in pediatric patients presenting with signs of multisystem inflammatory syndrome in children (MIS-C) (Table s7). The case definitions of this inflammatory syndrome, typically manifesting with  fever and shock similar to Kawasaki Disease, varied across studies. Most reports were from early in the pandemic and did not require laboratory evidence of SARS-CoV-2 infection to define the syndrome. However, these studies reported a higher rate of MIS-C diagnosis when IgG antibodies were added to NAAT compared to using NAAT alone. NAAT was positive in ~30-50% of cases in these studies, while IgG antibodies were positive in >80% cases in most studies. The major limitation of the evidence is that not all case series specified the timing of testing (either NAAT or serology) with respect to symptom onset. In addition, the type of serologic test utilized and epidemiologic links to COVID-19 cases were also not uniformly specified. The overall quality of evidence was very low due to the limitations of the case series study design and serious risk of bias. Even with very low certainty evidence, the panel issued a strong recommendation given the potentially catastrophic consequences of missing a diagnosis of MIS-C.

Benefits and harms

The diagnosis of MIS-C is important to provide appropriate treatment and follow up care for children, but no specific test is available to confirm this diagnosis. Another acute inflammatory syndrome in children, Kawasaki Disease, which generally affects children less than 5 years of age, can present with symptoms very similar to those of MIS-C. Although the initial treatment of both MIS-C and Kawasaki Disease typically includes supportive care and hospitalization, the differentiation of these two syndromes is important because Kawasaki disease requires hospitalization and treatment with specific therapies such as intravenous immunoglobulin or rituximab if diagnosed. The two diseases also differ in terms of potential complications and need for long term medication and follow up. The management of children  with MIS-C usually requires supportive care, including hospitalization and treatment of shock and respiratory distress, evaluation of cardiac function, and administration of medications that decrease inflammation. Diagnostic tools including serology to help exclude the diagnosis of MIS-C can therefore be helpful and important, but serologic testing may not be helpful in the actual diagnosis of MIS-C as many children have serologic evidence of past COVID-19 disease and/or vaccination. Further, given the high seroprevalence of antibodies to SARS-CoV-2 in the pediatric population, a negative serologic test result provides stronger evidence against a diagnosis of MIS-C than a positive result provides evidence for MIS-C. Although the certainty of evidence to inform this recommendation was very low, the panel concluded that the potential harm associated with a misdiagnosis of MIS-C warranted a strong recommendation for serologic testing together with NAAT in suspected cases.  

Other considerations

The clinical description and definition of MIS-C, as well as other SARS-CoV-2-associated inflammatory syndromes in children and adults, have varied over the pandemic and across countries and regions. Different clinical criteria with or without laboratory evidence of infection make comparisons of early studies problematic. It should be noted that the 2023 CDC definition of a confirmed case of MIS-C [3] requires meeting clinical and laboratory criteria; the latter include detection of SARS-CoV-2 RNA or antigen in a specimen up to 60 days before or during hospitalization or post-mortem, or detection of SARS-CoV-2 specific antibodies in serum, plasma, or whole blood associated with the current illness resulting in or during hospitalization [159]. Assessment of the reliability, sensitivity, and specificity of laboratory diagnostic criteria to document MIS-C will be difficult in the future because laboratory criteria are now required for diagnosis, and because case rates of MIS-C are falling. Given that pediatric seroprevalence for SARS-CoV-2  was 96.3% in December 2022, it is not surprising that 99% of recent U.S. cases of MIS-C are seropositive for SARS-CoV-2 [160].  

Conclusions and research needs for this recommendation

Acute febrile inflammatory syndromes in children are challenging to diagnose, but updated definitions of MIS-C are making this diagnosis more uniform. Differentiation of Kawasaki Disease from MIS-C will continue to be an issue, particularly in young children. In addition, changes in MIS-C epidemiology have been seen, with fewer cases of MIS-C now reported in association with new SARS-CoV-2 variants [161]. In addition, COVID-19 vaccination is associated with reduced incidence of MIS-C, especially if two doses are given [162]. Continued investigation of the epidemiology and treatment of MIS-C is warranted.

Recommendation 4: Serologic Testing to Assess Previous SARS-CoV-2 Infection - Antibody Class

Recommendation 4: When evidence of previous SARS-CoV-2 infection is desired, the IDSA panel suggests testing for SARS-CoV-2 IgG, IgG/IgM, or total antibodies three to five weeks after symptom onset and suggests against testing for SARS-CoV-2 IgM (conditional recommendation, low certainty of evidence).

Remarks:

• SARS-CoV-2 NAAT and antigen tests have superior performance characteristics for diagnosis of COVID-19, compared to serologic testing.
• There are very limited situations in which SARS-CoV-2 antibody testing might be useful (e.g., in helping to diagnose MIS-C).

Summary of the evidence

Using our search strategy, 53 studies [22-24, 29, 30, 34, 35, 38-42, 47, 51, 53, 54, 57, 58, 60-63, 66, 67, 71, 73, 76, 82, 83, 90, 91, 93, 94, 98, 102, 105, 106, 109, 110, 112, 114, 117, 118, 121, 129, 134, 163-169] were identified that assessed the diagnostic accuracy of serologic tests (IgM, IgG, IgM or IgG, and total antibodies) between weeks 3 and 8 after symptom onset compared to SARS-CoV-2 NAAT (Tables 2a-2d). Many of these same studies also informed Recommendation 1 in this guideline.

The number of samples in these studies that were included in analyses of sensitivity ranged from 44 to 2,591 and the number included in the specificity analyses ranged from 386 to 10,537 (Figures s8a-s28b). The pooled sensitivity at week three after symptom onset ranged from 83% to 93%, at week four from 86% to 95%, at week five from 89% to 95%, at week six from 85% to 97%, at week seven between 73% and 92%, and at week eight between 73% and 94%, while the pooled specificity ranged from 98% to 100% (Tables 2a-2d). When analyzed by antibody class, IgM consistently demonstrated the lowest analytical sensitivity compared with IgG alone, IgM/IgG or total antibodies.  

The certainty of evidence that informed sensitivity determinations was low, while the certainty of evidence to inform specificity determinations was moderate. Quality was rated downward for both sensitivity and specificity due to serious indirectness, and due to unexplained inconsistency in sensitivity. Concerns with indirectness stemmed from the fact that study populations dated mainly from the pre-vaccination era, and preceded infection with currently circulating viral variants. Thus, the analyses presented here may overestimate test accuracy in contemporary populations with high SARS-CoV-2 seroprevalence.

Benefits and harms

There are limited data on antibody level stability after natural infection, and even less on interpretation of antibody levels in the setting of a patient who has been both vaccinated and infected. Clinicians must be aware of the limitations of antibody testing, as well as the impact of patient vaccination history. Most published studies were performed early in the pandemic, before widespread vaccination or large numbers of infected individuals. In the studies included in the literature review for this recommendation, all antibody classes had similar specificities up to 8 weeks, but the lack of sensitivity of IgM-only assays means that patients would be incorrectly classified as not having been infected.

Other considerations

Antibody testing to demonstrate prior infection may be helpful in limited scenarios. These could include evaluating patients with possible MIS-C or assessing immune response in immunocompromised patients with ongoing PCR positivity who might be candidates for monoclonal antibody or convalescent antibody therapy, if effective therapy were available, especially in setting of limited supplies.

Conclusions and research needs for this recommendation

Antibody testing for respiratory viruses is not part of routine clinical care and should not be used to guide decisions regarding vaccination or non-pharmacologic infection prevention precautions. Further study is needed to determine duration of antibody response to either vaccination or infection, and to clarify the clinical scenarios in which measuring these analytes can benefit individual patients or populations.

Recommendation 5: Serologic Testing to Assess Previous SARS-CoV-2 Infection - Antibody Target

Recommendation 5: When evidence of prior SARS-CoV-2 infection is desired, the IDSA panel suggests using serologic assays that target nucleocapsid protein rather than spike protein (conditional recommendation, low certainty of evidence).

Remarks:

• Most available vaccines result in formation of only anti-spike antibodies but some (e.g., CoronaVac and BBIBP-CorV, manufactured by Sinovac and Sinopharm, respectively) which contain inactivated whole virus, can also result in formation of anti-nucleocapsid antibodies [4].
• Given the high prevalence of vaccination in most populations and the persistence of anti-spike antibodies over time, detection of anti-spike antibodies has low positive predictive value for diagnosis of recent COVID-19 in most individuals.

Summary of the evidence

We identified 6 studies [55, 69, 109, 170-172] that assessed in the same study population the diagnostic test accuracy of serologic tests that target spike and nucleocapsid proteins and compared the results of a recent (past 1-8 weeks) positive SARS-CoV-2 NAAT (Tables 3a-3b). All six studies included results for IgG, and one study also assessed IgM [171]. The sensitivity of assays targeting spike were 69% (95% CI: 65 to 73) and 69% (95% CI: 49 to 84) for IgM and IgG, respectively. The sensitivity of assays targeting nucleocapsid were 63% (95% CI: 58 to 69) and 75% (95% CI: 58 to 87) for IgM and IgG, respectively. The specificity ranged between 99% and 100% for both targets with IgM and IgG (Figures 29a-30b).

The certainty of evidence that informed sensitivity and specificity for IgM was low, and the certainty of evidence that informed sensitivity and specificity for IgG was low and moderate, respectively. The certainty was downgraded for concerns related to indirectness and imprecision (single study for IgM) and unexplained inconsistency (sensitivity of IgG). Indirectness is a concern because these studies were conducted primarily in an unvaccinated population and with SARS-CoV-2 variants that no longer predominate in the population. Together, these factors may overestimate test accuracy for the current population, which has high seroprevalance for SARS-CoV-2 due to vaccination and/or natural infection. We did not lower the certainty for indirectness of comparison as the studies tested the same population with the same anti-spike and anti-nucleocapsid antibody assays.

Benefits and harms

Regardless of target, serologic assays are likely to underestimate recent infection by SARS-CoV-2. While specificity was high in the studies evaluated, studies were conducted before widespread SARS-CoV-2 vaccination and infection. Specificity of anti-spike IgG as a marker of prior infection is expected to be low when testing the current, highly vaccinated population, as the spike antigen is the target for most available vaccines. In contrast, a positive result for IgM or IgG nucleocapsid antibodies is indicative of prior infection in most individuals, with the exception of those who received a vaccine that resulted in formation of anti-nucleocapsid antibodies, such as the inactivated whole-virus vaccines available outside the U.S.

Other considerations

While not specifically evaluated, waning of antibody levels over time after natural infection and vaccination has been noted. In particular, nucleocapsid-specific antibodies may be more short-lived in both immunocompetent [173]and immunocompromised patients [174], although comparing results between studies is often difficult due to the different antibody assays used. As such, timing of antibody testing is critical to the negative predictive value of the test and should ideally be performed within 3-4 weeks of symptom onset.

Conclusions and research needs for this recommendation

Sensitivity and specificity of nucleocapsid and spike antibody tests are similar, although interpretation of results as indicative of past infection (anti-nucleocapsid) versus past infection or vaccination (anti-spike) requires that clinicians know and understand the antibody target of the test that is used. While NAAT remains the recommended approach for diagnosis of COVID-19, detection of anti-nucleocapsid IgG, combination IgG/IgM, or total antibodies may be useful for determining recent past infection in selected clinical situations, e.g., MIS-C (see Recommendation 3 above.)

Recommendation 6: Serologic Testing to Improve Outcomes in Individuals with History of Vaccination or Previous Infection

Recommendation 6: In individuals with previous SARS-CoV-2 infection or vaccination, the IDSA panel suggests against routine serologic testing given no demonstrated benefit to improving patient outcomes (conditional recommendation, very low certainty of evidence).

Remarks

• Serologic testing may be useful for diagnosing MIS-C in pediatric patients, especially when NAAT or antigen testing is negative, to provide evidence of recent COVID-19 (see Recommendation 3 above).
• A negative spike antibody test may be a useful metric to identify immunocompromised patients who are candidates for immune therapy such as convalescent plasma or monoclonal antibodies, if such therapies were available, or to prioritize administration of monoclonal therapies when supplies are limited.

Summary of Evidence

Studies addressing natural infection:

We found no direct evidence to correlate serologic testing with improved outcomes at the population or individual level for persons with prior COVID-19. We identified 6 studies [175-180], 5 cohort and 1 case control study [177] that evaluated the relationship between antibody level (e.g., seropositivity) and decreased SARS-CoV-2 reinfection rates. This included five studies that assessed binding antibodies and one that assessed neutralizing antibodies [175]. Across the cohort studies, subjects with a seropositive result post-infection appeared to have a lower likelihood of developing re-infection. In the case control study [177], doubling of the antibody level was associated with reduced odds of reinfection. These studies, however, varied in the definition of reinfection, the timing of testing in relation to history of COVID-19, the antibody test used, and the comparison groups. (Table s8).

Studies addressing vaccination:

We identified 10 post-vaccination studies [181-190] including 6 cohort studies, 1 clinical trial [184], 1 systematic review [183], and 2 case control studies [182, 189] that evaluated the relationship between binding antibody (bAb) level and SARS-CoV-2 breakthrough infection rates [189, 190]. Results were inconsistent: 5 studies reported a correlation between seropositivity and decreased SARS-CoV-2 infection rates, while 2 [187, 188] reported no difference in infection rates between those who had seroconverted after vaccination and those who had not. Of note, the number of breakthrough infections in some studies was small, and several studies focused on patient populations with immunocompromising conditions.

The presence of neutralizing antibodies (nAbs) appears to correlate with protection against breakthrough infection based on a clinical trial and a systematic review (Table s9). However, a single tier or threshold antibody level that is predictive of protection has not been identified, and unless calibrated to a common reference standard, quantitative results are not commutable across assays (See Other Considerations below). We also did not identify any studies measuring the predictive value of hybrid immunity (i.e., serologic testing in individuals with confirmed previous SARS-CoV-2 infection and COVID-19 vaccination).

Summary statement:

The overall quality of evidence was very low due to risk of bias (Table s4), indirectness, and imprecision. There is indirectness in comparison, as the included studies only describe differences between subjects who underwent serologic testing. It is unclear if patient outcomes are any different because of testing (i.e., if test results would lead to any meaningful changes in care or outcomes). It is unclear therefore if serologic testing provides any benefit for patient care decisions or to patients.

Benefits and Harms

Anti-SARS C0V-2 antibody tests help identify people who may have been infected with SARS-CoV-2 or were vaccinated. However, a universal antibody level that is predictive of protection from re-infection after infection or vaccination has not been identified. The panel did not identify any benefits to antibody testing in most individuals to inform management decisions.

There may be selected scenarios for immunocompromised hosts, however, where serologic testing could be considered. One example is for patients with symptomatic COVID-19 and significant humoral immune impairment who are being evaluated for treatment with convalescent plasma. The European Conference of Infections in Leukemia (ECIL-9) as well as the National Comprehensive Cancer Network (NCCN) recommend consideration of convalescent plasma for hematologic/BMT patients who are SARS-CoV-2 seronegative [191] [192-194]. An additional use of serology is for prioritization of new monoclonal antibody therapies, if they become available in the future, especially if supplies are limited. Prioritizing treatment for those individuals most in need of protection could help optimize utilization of resources. Of note, a thorough review of convalescent plasma or monoclonal antibody therapies for COVID-19 is outside of the scope of this guideline.

Positive anti-SARS-CoV-2 antibody testing is part of the CDC case definition for MIS-C [195]. However, false positive results may detract from identifying the true cause of illness. For example, for children it is important to differentiate MIS-C from other inflammatory processes such as bacterial infections, Kawasaki Disease or rheumatic fever because the management and long term follow up of these entities is different. There are also potential harms to serologic testing after vaccination. False positive results may promote a false sense of security and lead individuals to take fewer steps to protect themselves against SARS-CoV-2 or to not seek treatment when it would otherwise have been indicated.

False negative results are also possible, which could cause emotional distress for previously vaccinated individuals by leading them to assume that the vaccine was ineffective. Post-vaccination antibody test results may be negative in individuals without a history of previous natural infection if the test used does not detect the type of antibodies induced by the vaccine. 

Other considerations

While current EUA indications do not preclude the use of SARS-CoV2 antibody tests in vaccinated individuals, none of the currently authorized tests has been authorized to assess humoral immunity post-vaccination or to define a threshold of protection after infection. Therefore, the FDA recommends against SARS-CoV-2 antibody testing to assess immunity.

Detection of anti-RBD-bAbs has generally correlated with the emergence of nAbs and the detection of nAbs has been associated with protection against COVID-19. Vaccine clinical trial data also showed that higher antibody levels (either bAbs or nAbs) were associated with fewer breakthrough infections. Despite these observations, a definitive correlate of protection has not been identified. One complicating factor is that antibody levels measured across different studies used different antibody tests that had not been calibrated to a common reference standard such as the WHO international standard for anti-SARS-CoV-2 immunoglobulin [196]. Currently, only one commercial test has been authorized to detect nAbs from individuals with recent or prior SARS-CoV-2 infection [197]. While this assay has been calibrated against the WHO standard, it was not validated for testing post-vaccination or for predicting protection from re-infection. In addition, a given antibody titer may provide lower protection against variants compared with the strains included in the vaccine or that caused prior infection. Furthermore, serologic testing does not assess the full spectrum of immune responses to infection or vaccination. Induction of T-cell immunity plays a critical role in protection against SARS-CoV-2, and while the potential importance of viral mutations and T-cell immune evasion is debated, it is unlikely that variants will be able to evade SARS-CoV-2-specific cell mediated immunity. Currently, assays designed to quantify T-cell immune function are not widely available for clinical use.  

Conclusions and research needs for this recommendation

Higher antibody levels generally correlate with protection against SARS-CoV-2 infection, but a single titer that predicts protection has not yet been identified. Therefore, antibody testing (either with bAns or nAbs) to assess for immunity to SARS-CoV-2 is not recommended routinely. Antibody testing should not be used to guide vaccination, re-vaccination or booster decisions.

More research is needed to determine the role of SARS-CoV-2 antibody testing in evaluating immunity against SARS-CoV-2 and to better understand if antibody tests will be helpful for identifying “non-responders” who should receive repeated COVID-19 vaccination or a different schedule for boosters. Efforts to better predict antibody longevity, correlation of bAb levels to nAbs levels, and serological surrogates of immune protection (including how this may differ in individuals who also have a history of both natural COVID-19 and vaccination) are needed. Future studies should use standardized assays that are- calibrated to an international standard.

Discussion

Early in the COVID-19 pandemic, there was intense interest in measuring antibody responses to SARS-CoV-2 infection, with the hope that a correlate of protective immunity would be identified. Similar interest accompanied release of results of clinical trials of the first SARS-CoV-2 vaccines. In response, intensive and wide-ranging research into the immunology of SARS-CoV-2 was conducted. This work yielded important insights, including that prior infection and vaccination reduce the risk of severe and fatal COVID-19, and that the presence of neutralizing antibodies (versus their absence) and higher binding antibody concentrations (versus lower concentrations) provide greater risk reduction. Yet despite these discoveries, and after almost 800 million infections and administration of 13.5 billion vaccine doses [5], the hope that a serologic marker of protection will be found remains unrealized. Consequently, current clinical indications for testing SARS-CoV-2 antibodies are few. In addition, as seroprevalence approaches 100% in most human populations, measuring antibodies has declined in importance as a public health strategy to surveille for SARS-CoV-2 infection.

In the current guideline, the IDSA panel identified only one clinical situation in which antibody testing is recommended: to assist with the diagnosis of MIS-C in children. Of note, ongoing assessment of the value of serologic testing in this clinical setting will be difficult since a positive test result is included in the case definition [3]. The panel also acknowledges that a negative spike antibody test may be a useful metric to identify immunocompromised patients who are candidates for immune therapy such as convalescent plasma, monoclonal antibodies, or to prioritize administration of monoclonal therapies when supplies are limited.

To optimize diagnostic test accuracy when considering serologic testing, IgG, IgG/IgM, or total antibody assays are suggested over an IgM assay, due to reduced sensitivity of IgM alone. Testing should not be done during the first two weeks of symptoms, since antibody production is often not detectable until week 3 or later; of note, few data are available after 8 weeks of symptoms, and the panel did not assess studies that reported results after this time. If serology is being done to assess for evidence of previous SARS-CoV-2 infection in someone who has been vaccinated with an mRNA (e.g., Moderna COVID-19 vaccine), protein subunit (e.g. Novavax COVID-19 vaccine), or viral vector vaccine (e.g., J&J/Janssen COVID-19 vaccine, which is no longer available for use in the U.S.), serologic assays that target the nucleocapsid protein are preferred over those that target the spike protein, since these vaccines elicit anti-spike antibodies.

It is important to emphasize that serologic test performance remains variable and sometimes the same manufacturer’s assay performed quite differently across studies. Factors that may have contributed to heterogeneity across studies include differences in the patient population tested, the exact timing of testing relative to symptom onset and the use of different NAAT assays as the reference standard for comparison. Patients with mild symptoms, or those who are asymptomatic [198], may display weaker immune responses to SARS-CoV-2 compared to those with severe illness. Standardized reporting of disease severity was not included in most studies. The exact timing of testing was also not specified in all studies. Uncertainly around the timing of testing could have affected the time-stratified analyses. In addition, most studies did not include an international standard. Future assays should be calibrated against an international reference standard such as that developed by the WHO  [199]. While in the previous version of this guideline, the clinical performance of LF assays was more variable than ELISA or CIA tests, this difference was not observed in the current updated literature review. Finally, in a new subgroup analysis, we found no substantive differences in test characteristics (i.e., sensitivity and specificity) based on viral antigen (i.e, spike vs nucleocapsid protein).

Conclusions

Clinicians and public health officials need to understand the indications for serologic testing and the performance of serology assays used in their settings to accurately interpret anti-SARS-CoV-2 antibody test results. Whenever possible, serologic assays with established high sensitivity and specificity (i.e., ≥99.5%) should be employed. IgG, IgG/IgM and total antibody tests appear to have better sensitivity and specificity than other immunoglobulin classes and perform best when used between three to five weeks after symptom onset. The clinical indications for antibody testing to support a diagnosis of COVID-19 are limited. Antibodies to SARS-CoV-2 support the diagnosis of MIS-C in children. A negative spike antibody test may be a useful metric to identify immunocompromised patients who are candidates for immune therapy such as convalescent plasma, monoclonal antibodies, or to prioritize administration of monoclonal therapies when supplies are limited. The current high seroprevalence of anti-SARS-CoV-2 antibodies in most populations reduces the value of antibody testing for epidemiologic purposes. While higher antibody titers and presence of neutralizing antibodies correlate with reduced risk of SARS-CoV-2 infection, a correlate of immune protection from infection has not been defined.

Notes

Financial Support

This project was funded in part by a cooperative agreement with the Centers for Disease Control and Prevention (grant number 6 NU50CK000477-04-01). The Centers for Disease Control and Prevention is an agency within the Department of Health and Human Services (HHS). The contents of this guideline do not necessarily represent the policy of CDC or HHS and should not be considered an endorsement by the Federal Government.

COI Summary

The following list displays what has been reported to the IDSA. To provide thorough transparency, the IDSA requires full disclosure of all relationships, regardless of relevancy to the guideline topic. Evaluation of such relationships as potential conflicts of interest is determined by a review process which includes assessment by the Board of Directors liaison to the Standards and Practice Guideline Committee and, if necessary, the Conflicts of Interest (COI) and Ethics Committee. The assessment of disclosed relationships for possible COI is based on the relative weight of the financial relationship (i.e., monetary amount) and the relevance of the relationship (i.e., the degree to which an association might reasonably be interpreted by an independent observer as related to the topic or recommendation of consideration). The reader of these guidelines should be mindful of this when the list of disclosures is reviewed. M.H. serves on a clinical adjudication panel for Sanofi; receives research funding from the Centers for Disease Control and Prevention (CDC) and CDC Foundation; serves on the Society for Healthcare Epidemiology of America (SHEA) Board of Directors and Chair of the SHEA Education & Research Foundation; received other numerations from Sage, Medline, and Molnylycke; and served as Chair of the IDSA Diagnostics Committee. K.H. served an advisor to Quidel, BioFire, Pfizer, and Takeda; received other numerations from Quidel, Pfizer and Takeda; served Editor to American Society of Microbiology (ASM) and member of Clinical and Laboratory Standards Institute Antifungal Committee; received research funding from the National Institutes of Health (NIH); and served on the exam committee for the American Board of Internal Medicine, and associate editor for Open Forum Infectious Diseases. J.E. serves as a consultant for Sanofi Pasteur, Pfizer, and AstraZeneca; an advisor/consultant for Meissa Vaccines; receives research funding from the CDC, Pfizer, Brotman Baty Research Institute, Merck, Novavax, GlaxoSmithKline, and AstraZeneca; served as an advisor to Teva Pharmaceuticals; and served as member of Pediatric Infectious Diseases Society (PIDS) Publication Committee and Transplant ID Committee. R.H. serves on the advisory board for Specific Diagnostics; serves as an advisor for ThermoFisher, Qiagen, Torus, and Roche; serves as an editor for the Journal of Clinical Microbiology (JCM); serves as a member of the microbiology committee for the College of American Pathology and a member of the AST subcommittee for the Clinical and Laboratory Standards Institute (CLSI); serves as Vice-chair for the Diagnostics Committee at the Infectious Diseases Society of America (IDSA); serves on the Professional Practices Group at the American Society for Microbiology (ASM); receives research funding from Qiagen, bioMerieux, Momentum Diagnostics, Specific Diagnostics, IHMA and Pattern; served as a consultant for bioMerieux. M.L. serves as an advisor for Sanofi, Seqirus, Medicago, GSK, Janssen, Novavax, Pfizer, MD Brief; receives research funding from the Canadian Institutes of Health Research, World Health Organization (WHO), Medical Research Council (United Kingdom), has received in-kind supply of vaccine from Sanofi, has been paid for expert testimony on institutional and workplace vaccine policy, and has served on the DSMB for CanSino Biologics and an advisor to Merck. D.M. serves as a member of the direct taskforce for diagnostic stewardship for the Society for Healthcare Epidemiology of America (SHEA); receives research funding from the Centers for Disease Control and Prevention (CDC), National Institute of Health (NIH), Veterans Affairs, Health Services Research and Development (HRSD) and the Agency for Healthcare Research and Quality (AHRQ). R.P. has a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, and a patent on an anti-biofilm substance issued; serves as consultant to PhAST, Torus Biosystems, Day Zero Diagnostics, Mammoth Biosciences, Netflix, Abbott Laboratories, Oxford Nanopore Technologies, CARB-X, Qvella, and HealthTrackRx; receives other numeration from NBME, UpToDate, and the Infectious Disease Board Review Course; received grants from CD Diagnostics, Merck, Hutchison Biofilm Medical Solutions, Accelerate, ContraFect, TenNor Therapeutics Limited, Shionogi, NIH, BIOFIRE, Adaptive Phage Therapeutics, National Science Foundation, and the Department of Defense; and has served as a consultant to Curetis, Specific Technologies, NextGen Diagnostics, Pathoquest, Selux Diagnositcs, and 1928 Diagnostics. S.S. serves as a Board member for the Evidence Foundation, receives honoraria for evidence reviews, methodological support and teaching from the Evidence Foundation; serves on guideline panels for the American Gastroenterological Association (AGA); and receives research funding from the Department of Veterans Affairs Evidence Synthesis Program. Y.F.Y. serves as a Board member for the Evidence Foundation; receives honoraria for evidence reviews, methodological support and teaching from the Evidence Foundation, the AGA for evidence reviews, and the Institute for Clinical and Economic Review (ICER) for committee meetings; serves as a Director for the Evidence Foundation and for the U.S. GRADE Network; and served on an Independent Appraisal Committee for ICER. R.M. serves as a Board member for the Evidence Foundation; and receives honoraria for evidence reviews, methodological support and teaching from the Evidence Foundation. M.H.M. serves as a Board member for the Evidence Foundation; receives honoraria for evidence reviews, methodological support and teaching from the Evidence Foundation; receives research funding from the Agency for Healthcare Research and Quality, the Endocrine Society, and the Society for Vascular Surgery; has received research funding the American Society of Hematology and the WHO; and has served as a guideline methodologist for the WHO. A.B. received honorarium from the ICER. R.A.M. serves as a Board member for the Evidence Foundation; receives honoraria for evidence reviews, methodological support and teaching from the Evidence Foundation, and ICER for committee meetings; receives research funding from the NIH, the WHO, the American College of Rheumatology, the American Society of Hematology, and Bohringer Ingelheim; serves as Chair of the Midwest Comparative Effectiveness Public Advisory Council of the ICER; serves on the Methods Committee for Kidney Disease Improving Global Outcomes Work Group; serves on the Clinical Guidelines Committee for the Canadian Society of Nephrology; and previously served on the Clinical Guidelines Committee for the American College of Physicians (ACP). All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed. All other authors report no potential conflicts. 

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Supplementary Information

Full Supplementary Materials

Supplement A

• Figure s1. PRISMA Flow Diagram  
• Table s1. PICO questions Identified by the Panel through the two guideline versions  
• Table s2. Search Strategies   
• Table s3. QUADAS-2 Risk of Bias Assessment (for test accuracy studies)  
• Table s4. ROBINS-I Risk of Bias Assessment (for non-test accuracy comparative studies)  
• Table s6. Narrative summaries of studies informing question around performing serology testing in people with negative NAAT     
• Table s7. Narrative summaries of studies informing question around performing serology testing in people with suspected MISC    
• Table s8. Narrative summaries of studies informing question around performing serology testing in people with history of COVID-19 infection     
• Table s9. Narrative summaries of studies informing question around performing serology testing in people with history of COVID-19 vaccination

Supplement B

• Figure s2a. Forest plot for the sensitivity of week 1 IgM using NAAT as reference standard  
• Figure s2b. Forest plot for the specificity of week 1 IgM using NAAT as reference standard  
• Figure s3a. Forest plot for the sensitivity of week 2 IgM using NAAT as reference standard  
• Figure s3b. Forest plot for the specificity of week 2 IgM using NAAT as reference standard  
• Figure s4a. Forest plot for the sensitivity of week 1 IgG using NAAT as reference standard  
• Figure s4b. Forest plot for the specificity of week 1 IgG using NAAT as reference standard  
• Figure s5a. Forest plot for the sensitivity of week 2 IgG using NAAT as reference standard  
• Figure s5b. Forest plot for the specificity of week 2 IgG using NAAT as reference standard  
• Figure s6a. Forest plot for the sensitivity of week 1 IgM or IgG combination tests using NAAT as reference standard  
• Figure s6b. Forest plot for the specificity of week 1 IgM or IgG combination tests using NAAT as reference standard  
• Figure s7a. Forest plot for the sensitivity of week 2 IgM or IgG combination tests using NAAT as reference standard  
• Figure s7b. Forest plot for the specificity of week 2 IgM or IgG combination tests using NAAT as reference standard  

Supplement C

• Figure s8a. Forest plot for the sensitivity of week 3 IgM using NAAT as reference standard 
• Figure s8b. Forest plot for the specificity of week 3 IgM using NAAT as reference standard  
• Figure s9a. Forest plot for the sensitivity of week 4 IgM using NAAT as reference standard  
• Figure s9b. Forest plot for the specificity of week 4 IgM using NAAT as reference standard  
• Figure s10a. Forest plot for the sensitivity of week 5 IgM using NAAT as reference standard
• Figure s10b. Forest plot for the specificity of week 5 IgM using NAAT as reference standard  
• Figure s11a. Forest plot for the sensitivity of week 6 IgM using NAAT as reference standard 
• Figure s11b. Forest plot for the specificity of week 6 IgM using NAAT as reference standard  
• Figure s12a. Forest plot for the sensitivity of week 7 IgM using NAAT as reference standard  
• Figure s12b. Forest plot for the specificity of week 7 IgM using NAAT as reference standard
• Figure s13a. Forest plot for the sensitivity of week 8 IgM using NAAT as reference standard  
• Figure s13b. Forest plot for the specificity of week 8 IgM using NAAT as reference standard  
• Figure s14a. Forest plot for the sensitivity of week 3 IgG using NAAT as reference standard  
• Figure s14b. Forest plot for the specificity of week 3 IgG using NAAT as reference standard  
• Figure s15a. Forest plot for the sensitivity of week 4 IgG using NAAT as reference standard  
• Figure s15b. Forest plot for the specificity of week 4 IgG using NAAT as reference standard  
• Figure s16a. Forest plot for the sensitivity of week 5 IgG using NAAT as reference standard  
• Figure s16b. Forest plot for the specificity of week 5 IgG using NAAT as reference standard  
• Figure s17a. Forest plot for the sensitivity of week 6 IgG using NAAT as reference standard 
• Figure s17b. Forest plot for the specificity of week 6 IgG using NAAT as reference standard  
• Figure s18a. Forest plot for the sensitivity of week 7 IgG using NAAT as reference standard  
• Figure s18b. Forest plot for the specificity of week 7 IgG using NAAT as reference standard  
• Figure s19a. Forest plot for the sensitivity of week 8 IgG using NAAT as reference standard 
• Figure s19b. Forest plot for the specificity of week 8 IgG using NAAT as reference standard  
• Figure s20a. Forest plot for the sensitivity of week 3 IgM or IgG combination tests using NAAT as reference standard  
• Figure s20b. Forest plot for the specificity of week 3 IgM or IgG combination tests using NAAT as reference standard  
• Figure s21a. Forest plot for the sensitivity of week 4 IgM or IgG combination tests using NAAT as reference standard  
• Figure s21b. Forest plot for the specificity of week 4 IgM or IgG combination tests using NAAT as reference standard  
• Figure s22a. Forest plot for the sensitivity of week 5 IgM or IgG combination tests using NAAT as reference standard 
• Figure s22b. Forest plot for the specificity of week 5 IgM or IgG combination tests using NAAT as reference standard  
• Figure s23a. Forest plot for the sensitivity of week 6 IgM or IgG combination tests using NAAT as reference standard  
• Figure s23b. Forest plot for the specificity of week 6 IgM or IgG combination tests using NAAT as reference standard 
• Figure s24a. Forest plot for the sensitivity of week 3 Total Antibodies using NAAT as reference standard  
• Figure s24b. Forest plot for the specificity of week 3 Total Antibodies using NAAT as reference standard  
• Figure s25a. Forest plot for the sensitivity of week 4 Total Antibodies using NAAT as reference standard  
• Figure s25b. Forest plot for the specificity of week 4 Total Antibodies using NAAT as reference standard  
• Figure s26a. Forest plot for the sensitivity of week 5 Total Antibodies using NAAT as reference standard  
• Figure s26b. Forest plot for the specificity of week 5 Total Antibodies using NAAT as reference standard  
• Figure s27a. Forest plot for the sensitivity of week 6 Total Antibodies using NAAT as reference standard 
• Figure s27b. Forest plot for the specificity of week 6 Total Antibodies using NAAT as reference standard  
• Figure s28a. Forest plot for the sensitivity of week 7 Total Antibodies using NAAT as reference standard  
• Figure s28b. Forest plot for the specificity of week 7 Total Antibodies using NAAT as reference standard

Supplement D

• Figure s29a. Forest plot for the sensitivity of IgG assays targeting spike using NAAT as reference standard 
• Figure s29b. Forest plot for the specificity of IgG assays targeting spike using NAAT as reference standard  
• Figure s30a. Forest plot for the sensitivity of IgG assays targeting Nucleocapsid using NAAT as reference standard  
• Figure s30b. Forest plot for the specificity of IgG assays targeting Nucleocapsid using NAAT as reference standard