The Influence of Time on the Sensitivity of SARS-CoV-2 Serological Testing

The Influence of Time on the Sensitivity of SARS-CoV-2 Serological Testing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Influence of Time on the Sensitivity of SARS-CoV-2 Serological Testing Arturo Torres Ortiz, Fernanda Fenn Torrente, Adam Twigg, James Hatcher, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1286644/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Serological testing is used to quantify SARS-CoV-2 seroprevalence, guide booster vaccination and select patients for anti-SARS-CoV-2 antibodies therapy. However, our understanding of how serological tests perform as time passes after infection is limited. Methods: Four assays were compared in parallel: 1) the multiplexed spike, nucleoprotein and receptor binding domain Meso Scale Discovery (MSD) assay 2) the Roche Elecsys-Nucleoprotein assay (Roche-N) 3) the Roche Spike assay (Roche-S) and 4) the Abbott Nucleoprotein assay (Abbott-N) on serial positive monthly samples from hospital staff up to 200 days following infection as part of the Co-Stars study. Results: We demonstrate that 50% of the Abbott-N assays give a negative result after 175 days (median survival time 95% CI 168-185 days) while the Roche-N assay (93% survival probability at 200 days, 95% CI 88-97%) maintained seropositivity. The MSD spike (97% survival probability at 200 days, 95% CI 95-99%) and the Roche-S assay (95% survival probability at 200 days, 95% CI 93-97%) also remained seropositive. The best performing quantitative Roche-S assay showed no evidence of waning Spike antibody titres over 200-days. Conclusions: The Abbott-N assay fails to detect SARS-CoV-2 antibodies as time passes since infection. In contrast the Roche and the MSD assays maintained high sensitivity. The limitations of the Abbott assay must be considered in clinical decision making. The long duration of detectable neutralizing spike antibody titres by the quantitative Roche-S assay provides further evidence in support of long-lasting SARS-CoV-2 protection to pre-existing strains of SARS-CoV-2 following natural infection. Trial registration : Co-STARs study was registered with ClinicalTrials.gov on May 8th, 2020, with trial number NCT04380896 (www.clinicaltrials.gov, NCT04380896) SARS-CoV-2 COVID-19 virus nucleoprotein spike protein antibody assay serology. Figures Figure 1 Figure 2 Figure 3 Introduction Following natural infection or vaccination, sensitive measurement of SARS-CoV-2 serological status is important to identify immune correlates of protection from future waves of the pandemic, evaluate those in need of booster vaccination and identify candidates for SARS-CoV-2 antibody therapy. The rapid response to the COVID-19 pandemic has led to the development of a wide range of serological tests suitable for evaluating SARS-CoV-2 exposure, infection or vaccination status [ 1 – 3 ]. Typically, these tests are approved for use by the regulatory authorities based on their performance against a panel of reference sera including positive and negative controls at either 14- or 21-days post infection [ 4 ]. Public Health England reported a 93.9% sensitivity for the Abbott SARS-CoV-2 IgG Nucleoprotein assay [ 5 ] and 100% for the Roche Elecsys Nucleoprotein assay at ≥14 days post infection [ 6 ]. This led to widespread adoption of these tests across NHS laboratories for testing at population level. Other studies have confirmed this test performance at 14-21 days post infection [ 7 , 8 ]. Population level serological studies have also based their conclusions - vital to guide national policy - on the basis of these tests [ 9 ] without considering how time since infection influences the performance of the test. The problem with this approach is that it does not take into account SARS-CoV-2 humoral dynamics and changes in avidity over time [ 10 , 11 ]. Although serological tests with limited diagnostic range may demonstrate excellent sensitivity shortly after infection, it is unclear how they will perform with time following infection or vaccination. In order to address this question, we applied 4 widely used serological assays in parallel to serial samples from the Co-STARs study [ 12 ] in which staff testing seropositive to SARS-CoV-2 were followed for up to 200 days following infection. We compared the proportion of samples that remained seropositive over time using a survival analysis and determined the decay rate of the nucleoprotein (N) antibody and the spike (S) antibody for each test using a previously published mathematical model fitted to the data. Materials And Methods Study setting and design Serological testing was performed on stored serum samples collected as part of the Co-STARs study ( www.clinicaltrials.gov , NCT04380896) run at Great Ormond Street Hospital between April and November 2020 [ 10 ]. The study had national Integrated Research Application System (IRAS) approval and all experimental protocols were approved. Briefly, Co-STARs was a 1-year single-centre prospective cohort study of antibody responses to COVID-19 infection in healthcare workers. Serum samples were taken from the 3657 participants at baseline and underwent a screening ELISA using the EDI assay. Repeated monthly serum samples were then taken from those with a seropositive baseline screening test for up to 250 days after the date of infection. Those samples identified as seropositive with available symptom start date had further confirmatory testing with the quantitative three antigen MSD assay. Study participants: The majority of hospital staff were eligible for the Co-STARS study [ 12 ]. Only those participants with significant immunosuppression, those that had received blood products within 6 months of recruitment and those that had active and ongoing symptoms of SARS-CoV-2 infection (within the last 21 days) were excluded. Only samples from individuals with at least one positive test from any platform were included in the analysis. Moreover, individuals without a known symptom start date were removed. Data Collection As part of the Co-STARs study all participants undertook a detailed standardised online questionnaire at study entry [ 12 ]. This included the date of onset of COVID-19 symptoms, and any SARS-CoV-2 diagnostic test results. Comparison of serological assays Samples taken as part of the Co-STARS study [ 12 ] which had an accompanying symptom start date available for analysis were initially screened for seropositivity by the EDI assay or by any of the three antigens of the Meso Scale Discovery (MSD) assay. The selected samples underwent testing with 4 serological assays: 1) The Roche Elecsys Anti-SARS-CoV-2 electrochemiluminescence immunoassay (ECLIA) assay detects the nucleocapsid (N) antigen (Roche-N); 2) the Roche Elecsys Anti-SARS-CoV-2 S electrochemiluminescence immunoassay (ECLIA) assay detects the spike (S) antigen (Roche-S); 3) the Abbott Nucleoprotein Chemiluminescent Microparticle Immunoassay (CLMIA) assay detects the nucleocapsid (N) antigen (Abbott-N); 4) The four antigen Meso Scale Discovery (MSD) assay was undertaken at the WHO Pneumococcal Supranational Reference Laboratory at the UCL Institute of Child Health. Only 3 antigens were reported from the MSD assay (the Spike, the Nucleoprotein and the receptor binding domain, RBD) as the baseline test performance of the N-terminal domain (NTD) antibody response was insufficient for further evaluation as previously reported [ 13 ]. The Roche-N and Roche-S assays were undertaken by the Laboratory Medicine Service of Swansea Bay University Health Board, Morriston Hospital, Swansea. The Abbott-N assay was undertaken by Public Health Wales Microbiology at Cardiff and Vale University Hospital. All samples were stored and transported between laboratories at -80oC and only removed for aliquoting prior to testing to avoid unnecessary freeze-thaw cycles. Statistical Analysis and Modelling In order to evaluate the relative proportion of seropositive tests in the parallel serological assays over time, a time-to-event analysis was performed using the time from symptom onset and the first negative test for each assay after a first positive test as the event of interest using the R package survival [ 14 , 15 ]. Only tests taken >14 days after symptom onset were considered in the analysis (albeit no tests were performed between 14- and 21-days post symptoms meaning >14 or >21 days post symptom results were identical). A participant was defined as seropositive when at least one of the 4 tests undertaken was seropositive. If the other tests that were run in parallel never became seropositive, the time-to-event was set to the earliest test taken for that individual. If a participant never became seronegative during the follow-up period, a right-censored observation was added at the time of the last serological test. Additionally, the decay rate after 21 days since symptom onset was estimated using a Bayesian generalized mixed model, where time from symptom onset was included as a fixed effect and study participants as a random effect. The decay rate was estimated from the slope of the regression model. Results A total of 950 samples from 329 participants seropositive by any assay after 14 days underwent testing with the Roche-N, Roche-S, the MSD and the Abbott-N assay. The majority of the participants (98%, 321/329) had a positive result by two or more assays. Antibody Decay with Time Plotting the raw log transformed antibody titres over time since symptom onset (Figure 1 ) demonstrated that antibody dynamics were dependent on the assay undertaken. The production of spike antibodies was demonstrated to be maintained at high levels up to 200 days when evaluated by the MSD and the quantitative Roche -S assay. All nucleoprotein antibody assays demonstrated decay of the nucleoprotein antibody over time. This was most pronounced in the Abbott-N assay and much less so in the Roche -N assay which demonstrated slow waning of the nucleoprotein antibody. Assay Sensitivity with Time Post Symptom Onset The existing published test performance for all assays undertaken is provided in Table 1 . The sensitivity of all assays (at least 14 days from symptom onset) at 50, 100 and 150 days is provided in Table 2 . All assays demonstrated a reasonable sensitivity at 50 days following infection. As time passed following infection, the Abbott-N assay rapidly became seronegative, with a median survival time inferred at 175 days (95% CI 168-185 days), whereas the survival probability at 150 days was inferred to be 95% for the Roche-N (95% CI 0.92 - 0.97), and 91% for the MSD-N assay (95% CI 0.87 - 0.94). The Roche-S and MSD-S assays remained seropositive for the duration of the study. The MSD-RBD assay showed some evidence of waning seropositivity over time (90% Survival probability at 150 days, 95% CI 0.88 - 0.94). A total of 45% (159/329) of the individuals had a negative result using the Abbott-N assay during the course of the study. For the MSD test, 16% (52/329) of participants had a negative test for the N antigen, 11% (36/329) for RBD, and 3% (11/329) for the S antigen. For the Roche platform, 5.5% (18/329) of the individuals had a negative result with the Roche-N assay, while only 4.8% (16/329) of them had a negative result for the S antigen over the course of the study. Table 1 A summary of the existing published data for the commercially available tests in this comparison. The corresponding antigen target and published sensitivity, specificity, positive predictive value and negative predictive value (if available). Tests Manufacturer Target Antigen Type Sens † Spec # Samples/Patients * Days post symptom onset Abbott-N [ 16 ] Abbott-N Nucleoprotein CLMIA 100.0% (day 17) 99.9% 689/125 ≥21 Roche-N [ 17 ] Roche Cobas Nucleoprotein ECLIA 99.5% 99.8% 496/102 ≥14 Roche-S [ 18 ] Roche Cobas Spike protein ECLIA 96.6% 100% 1485 ‡ /331 ≥15 MSD [ 13 ] Meso Scale Discovery Nucleoprotein ECLIA 87.2% 92.8% 196/196 ≥21 Spike protein 97.9% 97.4% 47/47 ≥21 RBD (receptor binding domain) 93.6% 92.3% 47/47 ≥21 ECLIA: Electro Chemiluminescent Immunoassay, CLMIA: Chemiluminescent Microparticle Immuno Assay PPV: Positive Predictive Value, NPV: Negative Predictive Value, Sens: Sensitivity, Spec: Specificity, ELISA: Enzyme Linked Immunosorbent Assay † The highest reported sensitivity ‡233 of these samples were tested at ≥15 days post PCR diagnosis * For Sensitivity Testing Table 2 Sensitivity of compared assays at 50, 100 and 150 days from symptom onset. Survival probability (95% CI) 50-day 100-day 150-day Abbott-N 0.985 (0.97;0.99) 0.919 (0.89;0.95) 0.655 (0.6;0.71) Roche-N 0.988 (0.98;1.0) 0.963 (0.94;0.98) 0.949 (0.92;0.97) Roche-S 0.991 (0.98;1.0) 0.966 (0.95;0.99) 0.952 (0.93;0.98) MSD -N 0.988 (0.98;1.0) 0.972 (0.95;0.99) 0.907 (0.87;0.94) -S 0.997 (0.99;1.0) 0.978 (0.96;0.99) 0.968 (0.95;0.99) -RBD 0.994 (0.99;1.0) 0.969 (0.95;0.99) 0.909 (0.88;0.94) Mathematical Model Fits to Estimate Long-Term Antibody Decay To estimate the decay rate for each antibody and assay studied, a generalized linear mixed model was fitted to the trajectory of antibody decay after 21 days from symptom onset, where the decay rate was estimated as the slope of the antibody titer through time. Under the most sensitive and quantitative Roche -S assay the spike antibody demonstrated no decay at all and rather a slow rate of increased titres over time from symptom onset (0.0031, 95% CI 0.0018 — 0.0044, Fig. 2 b). In accordance with the raw observed data, all nucleoprotein antibodies under the mathematical model decayed (Fig. 2 a, Fig. 2 b). This was most pronounced in the Abbott-N assay (-0.022, 95% CI -0.023 — -0.02) and least pronounced in the Roche -N assay (-0.0025, 95% CI -0.0039 — -0.0012, Fig. 2 b, Table 3 ). The Roche-S assay target the spike antibody, the Abbott-N and the Roche-N assays target the N-antibody while the MSD assay targets the N-, the S- and the antibody to the Receptor Binding Domain (RBD) of the spike protein in parallel. (a) Kaplan-Meier curve and numbers at risk (the number of participants under follow up with serological tests available for analysis at that time point) for different serological tests. Y-axis represents the probability of remaining seropositive, while the X-axis shows days after symptom onset with numbers of participants under follow up shown in the table below. (b) Inferred posterior density distributions of the decay rate in a generalized linear mixed model. Table 3 Decay rate for each serological assay (log arbitrary units per day) estimated in a generalized linear mixed model. Mean 95% CI MSD-N -0.0121 -0.0134;-0.0107 MSD-RBD -0.0068 -0.008;-0.0055 MSD-S -0.0035 -0.0048;-0.0023 Abbott-N -0.0216 -0.0229;-0.0204 Roche-S 0.0031 0.0018;0.0044 Roche-N -0.0025 -0.0039;-0.0012 The lower performance of the Abbott-N assay can be explained by a lower detection of titer values as their concentration wanes over time. When compared to the quantitative MSD-N, 26% (222/860) of all positive samples by the MSD-N were negative for the Abbott-N test (Fig. 3 ). A total of 75% of samples (137/ 183) positive by the MSD-N with an MSD arbitrary titer value lower than 403 were negative for the Abbott-N assay. The quantitative results for the MSD-N assay were compared to those of the Abbot-N test for each sample taken. Colours divide the samples depending on whether it was positive (green) or negative (red) for the MSD-N assay. Dotted red lines represent the seropositivity threshold for the Abbott-N assay (horizontal) and the MSD-N test (vertical). Discussion Sensitive measurement of SARS-CoV-2 seropositivity is key to evaluate who has been infected or exposed to SARS-CoV-2, to determine the correlates of protection from future disease, stratify those that need booster vaccination and target the use of anti-SARS-CoV-2 antibodies to those that are seronegative. To our knowledge no other study has evaluated the sensitivity of multiple diagnostic tests in parallel on longitudinally collected serological samples. This study demonstrates that as time elapses after infection, the sensitivity of serological testing varies widely depending on the test used. Although serological tests may be demonstrated to perform well 14-21 days after infection, this initial test performance often diminishes as time passes. In order to evaluate whether or not the population maintains SARS-CoV-2 antibodies it is vital that we utilize serological tests that remain sensitive over time. Initial published baseline test performance reports concluded that the Abbott-N assay was a high-performance test and a key tool in SARS-CoV-2 surveillance [ 16 ]. Our data demonstrate that as time passes following infection the sensitivity of this assay declines rapidly until at <6 months following infection it is no more than 50% sensitive. Our findings support the concerns raised by others regarding the poor performance of some nucleoprotein based assays [ 19 , 20 ]. In contrast, the Roche assays, particularly the Roche Elecsys Anti-SARS-CoV-2 Spike assay maintained high sensitivity for the 200-day duration of the study. Although there remains no single correlate of sterilizing or protective immunity following SARS-CoV-2 infection or vaccination, it is clear that natural infection and the presence of neutralizing spike antibodies decreases the possibility of re-infection and the severity of disease upon re-exposure to currently circulating strains [ 21 ]. Our finding that neutralizing spike antibodies remained at high titres 200 days after infection adds to our previous study on this topic [ 10 ] and provides further evidence in support of long-lasting protection against severe disease from currently circulating strains. Fitting mathematical models to the raw data of the Roche spike assay demonstrated that spike antibody titres did not decay but rather increased slightly over the duration of the study. The Roche nucleoprotein assay also maintained sensitivity for the duration of the study with a low rate of decay. Although this assay is semi-quantitative, our findings suggest that this could be used to sensitively identify those that have been vaccinated from those that have been both vaccinated and infected. This has relevance for the diagnosis of long covid, MIS-C and COVID infection post vaccination. Many studies have evaluated the impact of time on test sensitivity over the first 3 weeks following symptom onset [ 22 – 24 ]. However, we found no other study that had examined the sensitivity of antibody testing on parallel longitudinal samples collected between 1-6 months after infection or exposure. Assays with a higher titer cut-off for detection may perform well in the initial period after infection, but fail to detect seropositivity as antibody levels wane over time. We show that the Abbott-N test failed to detect 75% of samples positive for the MSD-N with a titer value lower than 403, which makes the Abbott-N assay less suitable for seroprevalence studies. Barzin et al [ 25 ] used Abbott-N testing alone to determine SARS-CoV-2 seroprevalence in 2,973 asymptomatic out-patients in North Carolina estimating a seroprevalence of 0.8%. Similarly, Wilkins et al [ 26 ] used Abbott-N on 6510 healthcare workers up to 150 days after symptom onset and estimated a seroprevalence of 4.8%. Our findings suggest that previously published surveys of SARS-CoV-2 seroprevalence such as these could have significantly underestimated the true prevalence of SARS-CoV-2 humoral immunity. Memory T-cell interferon gamma release or proliferation assays in response to SARS-CoV-2 antigens provide an alternative means of assessing prior exposure to infection. However, these assays are limited by cross reactive immunity to the seasonal coronaviruses decreasing specificity [ 27 , 28 ]. Although all serological tests used in the study demonstrated a high initial specificity, one limitation of this study is that only 38% of participants had a confirmatory SARS-CoV-2 PCR result. Our data may therefore be influenced by an unknown proportion of falsely positive serological tests. However, at entry to the study, all seropositive participants had both a screening EDI nucleoprotein assay and an MSD assay performed which limited the chances of a falsely positive result due to a single erroneous test. Not all samples were processed at the same time; the Roche and Abbott-N assays were processed 3 months after the MSD assays. Despite this, we believe that sample storage and freeze-thawing cycles are unlikely to have influenced our findings as the Roche quantitative spike assay was performed last and demonstrated the highest prolonged levels of spike antibody of all tests used. Conclusions In summary, although serological tests may demonstrate high sensitivity 3-weeks after SARS-CoV-2 infection, this is far from the case with some tests 6-months after infection. The Abbott-N assay performed poorly at this time, whereas the Roche and MSD tests maintained a high sensitivity for the 200 days of the study. Tests that perform poorly over time will lead to spurious estimates in population level seroprevalence studies and findings from these studies should be adjusted to account for sensitivity of the test used and the time since infection. Test performance as time passes post infection should be considered before evaluating who is a candidate for booster vaccination or anti-SARS-CoV-2 antibody therapy. Abbreviations SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 MSD Meso Scale Discovery Roche-N Roche Elecsys-Nucleoprotein assay Roche-S Roche Elecsys-Spike assay Abbott-N Abbott Nucleoprotein assay Co-STARs COVID-19 Staff Testing of Antibody Responses Study ELISA Enzyme Linked Immunosorbent Assay EDI assay Epitope Diagnostics, Inc. CLMIA Chemiluminescent Microparticle Immunoassay RBD Receptor binding domain NTD N-terminal domain ECLIA Electro Chemiluminescent Immunoassay MIS-C Multisystem inflammatory syndrome in children PCR polymerase chain reaction CI confidence interval Declarations Ethical Approval and Consent to Participate: The study had national Integrated Research Application System (IRAS) approval and all participants in the study provided informed consent. All methods were carried out in accordance with relevant guidelines and regulations. Consent for Publication: Not applicable. Availability of data and materials: The datasets generated and/or analysed during the current study are available in the Health Data Research Innovation UK (HDRUK) repository, https://web.www.healthdatagateway.org/dataset/435bfcda-f378-44f6-9387-042d959eb945. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interests: The authors declare that they have no competing interest. Funding: LG was supported by the Wellcome Trust (201470/Z/16/Z), the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award number 1R01AI146338, the GOSH Charity (VC0921) and the GOSH/ICH Biomedical Research Centre (www.nihr.ac.uk). AS was supported by the Wellcome Trust (220565/Z/20/Z). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Authors’ Contributions The first draft of the manuscript was prepared by: ATO, FFT, AT, JH, RD, ALM, DG, RS, KG and LG. The study was designed and implemented by: LG, ATO, JH, RD, RS, DG and KG. Testing for SARS-CoV-2 RNA and antibody was conducted by: LG, FFT, ALM, KG, JH, RD, RS and DG. Data analysis was carried out by ATO and LG. Acknowledgements We would like to dedicate this article to the staff members who died of COVID-19 at Great Ormond Street Hospital during the first wave of the pandemic. We would also like to thank all the staff at Great Ormond Street Hospital who have taken part in the study. In addition, we are very grateful for all the hard work undertaken by the Great Ormond Street rapid response and microbiology laboratory staff and the staff in the immunology laboratories both in the Camelia Botnar Laboratory and the Great Ormond Street Institute of Child Health who ensured that all the PCR tests and serological assays were completed in a timely manner. The authors would also like to thank the biomedical scientists and colleagues in the affiliated laboratories for their hard work in running the samples and collating the results. RD would like to thanks Linda Tyson and Jon Evans of the Wales National Virology Centre, PHW Microbiology Cardiff. RS would like to thank Non Gwynn, Jenna Walters, James Murphy and colleagues in Laboratory Medicine, Morriston Hospital, Swansea. References Bastos ML, Tavaziva G, Abidi SK, Campbell JR, Haraoui L-P, Johnston JC, et al. Diagnostic accuracy of serological tests for covid-19: systematic review and meta-analysis. BMJ. 2020;370:m2516. Kubina R, Dziedzic A. Molecular and Serological Tests for COVID-19. A Comparative Review of SARS-CoV-2 Coronavirus Laboratory and Point-of-Care Diagnostics. Diagnostics (Basel). 2020;10:434. La Marca A, Capuzzo M, Paglia T, Roli L, Trenti T, Nelson SM. Testing for SARS-CoV-2 (COVID-19): a systematic review and clinical guide to molecular and serological in-vitro diagnostic assays. Reprod Biomed Online. 2020;41:483–99. Cheng MP, Yansouni CP, Basta NE, Desjardins M, Kanjilal S, Paquette K, et al. Serodiagnostics for Severe Acute Respiratory Syndrome–Related Coronavirus-2. Ann Intern Med. 2020;:M20-2854. Evaluation_of_Abbott_SARS_CoV_2_IgG_PHE.pdf. Evaluation_of_Roche_Elecsys_anti_SARS_CoV_2_PHE_200610_v8.1_FINAL.pdf. Coste AT, Jaton K, Papadimitriou-Olivgeris M, Greub G, Croxatto A. Comparison of SARS-CoV-2 serological tests with different antigen targets. J Clin Virol. 2021;134:104690. Ainsworth M, Andersson M, Auckland K, Baillie JK, Barnes E, Beer S, et al. Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison. The Lancet Infectious Diseases. 2020;20:1390–400. Pollán M, Pérez-Gómez B, Pastor-Barriuso R, Oteo J, Hernán MA, Pérez-Olmeda M, et al. Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study. The Lancet. 2020;:S0140673620314835. Grandjean L, Saso A, Ortiz AT, Lam T, Hatcher J, Thistlethwayte R, et al. Long-Term Persistence of Spike Antibody and Predictive Modeling of Antibody Dynamics Following Infection with SARS-CoV-2. Clinical Infectious Diseases. 2021. https://doi.org/10.1093/cid/ciab607 . Bauer G, Struck F, Schreiner P, Staschik E, Soutschek E, Motz M. The challenge of avidity determination in SARS-CoV-2 serology. Journal of Medical Virology. 2021;93:3092–104. Great Ormond Street Hospital for Children NHS Foundation Trust. COVID-19 Staff Testing of Antibody Responses Study (CO-STARS). Clinical trial registration. clinicaltrials.gov; 2021. Johnson M, Wagstaffe HR, Gilmour KC, Mai AL, Lewis J, Hunt A, et al. Evaluation of a novel multiplexed assay for determining IgG levels and functional activity to SARS-CoV-2. J Clin Virol. 2020;130:104572. R: The R Project for Statistical Computing. https://www.r-project.org/ . Accessed 16 Dec 2021. Therneau TM, Grambsch PM. The Cox Model. In: Therneau TM, Grambsch PM, editors. Modeling Survival Data: Extending the Cox Model. New York, NY: Springer; 2000. p. 39–77. Bryan A, Pepper G, Wener MH, Fink SL, Morishima C, Chaudhary A, et al. Performance Characteristics of the Abbott Architect SARS-CoV-2 IgG Assay and Seroprevalence in Boise, Idaho. Journal of Clinical Microbiology. 58:e00941-20. Muench P, Jochum S, Wenderoth V, Ofenloch-Haehnle B, Hombach M, Strobl M, et al. Development and Validation of the Elecsys Anti-SARS-CoV-2 Immunoassay as a Highly Specific Tool for Determining Past Exposure to SARS-CoV-2. Journal of Clinical Microbiology. 58:e01694-20. Elecsys Anti-SARS-CoV-2 S - Instructions for Use | FDA. https://www.fda.gov/media/144037 . Accessed 9 Sep 2021. Rosadas C, Randell P, Khan M, McClure MO, Tedder RS. Testing for responses to the wrong SARS-CoV-2 antigen? The Lancet. 2020;396:e23. Bolotin S, Tran V, Osman S, Brown KA, Buchan SA, Joh E, et al. SARS-CoV-2 seroprevalence survey estimates are affected by anti-nucleocapsid antibody decline. J Infect Dis. 2021;:jiaa796. Hall VJ, Foulkes S, Charlett A, Atti A, Monk EJM, Simmons R, et al. SARS-CoV-2 infection rates of antibody-positive compared with antibody-negative health-care workers in England: a large, multicentre, prospective cohort study (SIREN). The Lancet. 2021;397:1459–69. Whitman JD, Hiatt J, Mowery CT, Shy BR, Yu R, Yamamoto TN, et al. Evaluation of SARS-CoV-2 serology assays reveals a range of test performance. Nat Biotechnol. 2020;38:1174–83. Piec I, English E, Thomas MA, Dervisevic S, Fraser WD, John WG. Performance of SARS-CoV-2 serology tests: Are they good enough? PLOS ONE. 2021;16:e0245914. Wang H, Ai J, Loeffelholz MJ, Tang Y-W, Zhang W. Meta-analysis of diagnostic performance of serology tests for COVID-19: impact of assay design and post-symptom-onset intervals. Emerg Microbes Infect. 9:2200–11. Barzin A, Schmitz JL, Rosin S, Sirpal R, Almond M, Robinette C, et al. SARS-CoV-2 Seroprevalence among a Southern U.S. Population Indicates Limited Asymptomatic Spread under Physical Distancing Measures. mBio. 2020;11:e02426-20. Wilkins JT, Gray EL, Wallia A, Hirschhorn LR, Zembower TR, Ho J, et al. Seroprevalence and Correlates of SARS-CoV-2 Antibodies in Health Care Workers in Chicago. Open Forum Infectious Diseases. 2021;8. Le Bert N, Tan AT, Kunasegaran K, Tham CYL, Hafezi M, Chia A, et al. SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 2020;584:457–62. Lipsitch M, Grad YH, Sette A, Crotty S. Cross-reactive memory T cells and herd immunity to SARS-CoV-2. Nat Rev Immunol. 2020;20:709–13. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 11 Apr, 2022 Reviews received at journal 10 Apr, 2022 Reviews received at journal 05 Apr, 2022 Reviewers agreed at journal 30 Mar, 2022 Reviewers agreed at journal 21 Mar, 2022 Reviewers invited by journal 21 Mar, 2022 Editor assigned by journal 10 Mar, 2022 Editor invited by journal 15 Feb, 2022 Submission checks completed at journal 15 Feb, 2022 First submitted to journal 22 Jan, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1286644","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":83998399,"identity":"338d99e3-f0c5-49b1-8a03-ac6c34b13e4f","order_by":0,"name":"Arturo Torres Ortiz","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Arturo","middleName":"Torres","lastName":"Ortiz","suffix":""},{"id":83998400,"identity":"9016fa05-627e-4e1e-99f4-89202cf7c01f","order_by":1,"name":"Fernanda Fenn Torrente","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fernanda","middleName":"Fenn","lastName":"Torrente","suffix":""},{"id":83998401,"identity":"bb9ce5d1-edad-465e-b029-9e1308dc43bd","order_by":2,"name":"Adam Twigg","email":"","orcid":"","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Twigg","suffix":""},{"id":83998402,"identity":"c8f6eed0-ae37-45d5-85e0-b34ccef563d4","order_by":3,"name":"James Hatcher","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Hatcher","suffix":""},{"id":83998403,"identity":"63caf6fb-55ce-4d54-bf36-e703e32966bc","order_by":4,"name":"Anja Saso","email":"","orcid":"","institution":"London School of Hygiene \u0026 Tropical Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anja","middleName":"","lastName":"Saso","suffix":""},{"id":83998404,"identity":"4ab5e2bf-b5f6-44c6-868e-54ee8b718a25","order_by":5,"name":"Tanya Lam","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tanya","middleName":"","lastName":"Lam","suffix":""},{"id":83998405,"identity":"8ba1d0a3-0580-4e38-acdd-8f1703728635","order_by":6,"name":"Marina Johnson","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Johnson","suffix":""},{"id":83998406,"identity":"b60a6d78-8ee2-42d8-b757-bd1f53a2fed0","order_by":7,"name":"Helen Wagstaffe","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Helen","middleName":"","lastName":"Wagstaffe","suffix":""},{"id":83998407,"identity":"f94dcdcb-753e-4a14-a6d9-a41d9f90cb20","order_by":8,"name":"Rishi Dhillon","email":"","orcid":"","institution":"University Hospital of Wales","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rishi","middleName":"","lastName":"Dhillon","suffix":""},{"id":83998408,"identity":"9afca1da-64a4-4406-8276-0e3998aad5f6","order_by":9,"name":"Anabelle Lea Mai","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anabelle","middleName":"Lea","lastName":"Mai","suffix":""},{"id":83998409,"identity":"e15061dd-964c-4462-b0b3-6a4e750091df","order_by":10,"name":"David Goldblatt","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Goldblatt","suffix":""},{"id":83998410,"identity":"67b22010-87df-49e6-b312-d263e1883fe5","order_by":11,"name":"Rachel Still","email":"","orcid":"","institution":"Swansea Bay University Health Board","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rachel","middleName":"","lastName":"Still","suffix":""},{"id":83998411,"identity":"104084fe-81aa-431e-92c4-6f339881e27b","order_by":12,"name":"Matthew Buckland","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"","lastName":"Buckland","suffix":""},{"id":83998412,"identity":"c3e11a24-2ee3-49a4-ba30-df97b221b3c6","order_by":13,"name":"Kimberly Gilmour","email":"","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kimberly","middleName":"","lastName":"Gilmour","suffix":""},{"id":83998413,"identity":"a2915b58-9c26-40b2-b410-d5b35668ee2a","order_by":14,"name":"Louis Grandjean","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACPgjFzAwkGB8wMFiAuYwNeLSwIWlhNmBgkCBeC5gtQaQW9msffu6wZudnP3usmqdGgoG//QCb5Ay8WniKZ/aeSWeW7MlLu81zTIJB4kwCm+QG/FqSGXjbDjMbHMgxu83bAHTYDQY2yQcEtDD+BWqxP//GrBikRZ6wFvbDzGBbJHLMmEFaDEBa8DqMmYeZWbYtnVnixhtjyTnHJHgMzyQ2W+LzPj97+2PGt23Wyfz9OYYf3tTYyMkdP3zwZg8eLQzMPAYgKhnG5yEQKyDA/gBE2hFQNQpGwSgYBSMZAACx1T2CiJLbbAAAAABJRU5ErkJggg==","orcid":"","institution":"Great Ormond Street Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Louis","middleName":"","lastName":"Grandjean","suffix":""}],"badges":[],"createdAt":"2022-01-22 14:29:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1286644/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1286644/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":18325123,"identity":"9767792d-404e-4304-a85f-dc77545c1d77","added_by":"auto","created_at":"2022-02-17 14:58:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83974,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLog transformed serial serological antibody titre data plotted by time from symptom onset\u003c/strong\u003e Antibody dynamics are dependent on the assay used with the sensitive Roche-S and MSD-S assay demonstrating maintenance of the spike protein antibody while the nucleoprotein antibody is shown to wane with the MSD and Abbott-N assays but to a lesser extent with the Roche-N assay.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"ScientificReportsFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1286644/v1/323b8b78c30c4609c274f59b.png"},{"id":18325125,"identity":"f6e6629c-0c01-4fa0-9405-2cae6f27dcb8","added_by":"auto","created_at":"2022-02-17 14:58:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":85781,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of seropositivity and antibody dynamics between serological tests.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e The Roche-S assay target the spike antibody, the Abbott-N and the Roche-N assays target the N-antibody while the MSD assay targets the N-, the S- and the antibody to the Receptor Binding Domain (RBD) of the spike protein in parallel. (a) Kaplan-Meier curve and numbers at risk (the number of participants under follow up with serological tests available for analysis at that time point) for different serological tests. Y-axis represents the probability of remaining seropositive, while the X-axis shows days after symptom onset with numbers of participants under follow up shown in the table below. (b) Inferred posterior density distributions of the decay rate in a generalized linear mixed model.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"ScientificReportsFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1286644/v1/cc7545bcf133a4db4733b18f.png"},{"id":18325124,"identity":"84ddf65a-f637-4dff-8614-382ebea3f668","added_by":"auto","created_at":"2022-02-17 14:58:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":85095,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of antibody titers between the Abbott-N assay and the MSD-N assay.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e The quantitative results for the MSD-N assay were compared to those of the Abbot-N test for each sample taken. Colours divide the samples depending on whether it was positive (green) or negative (red) for the MSD-N assay. Dotted red lines represent the seropositivity threshold for the Abbott-N assay (horizontal) and the MSD-N test (vertical).\u0026nbsp;\u003c/p\u003e","description":"","filename":"ScientificReportsFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1286644/v1/5cbdd5c95dee5c78357e341c.png"},{"id":18325126,"identity":"360d4017-539d-4c02-96ea-d53d35ceefad","added_by":"auto","created_at":"2022-02-17 14:58:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":702684,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1286644/v1/9c31c914-2e01-4976-a6c5-4ba979974ca2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Influence of Time on the Sensitivity of SARS-CoV-2 Serological Testing","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFollowing natural infection or vaccination, sensitive measurement of SARS-CoV-2 serological status is important to identify immune correlates of protection from future waves of the pandemic, evaluate those in need of booster vaccination and identify candidates for SARS-CoV-2 antibody therapy. The rapid response to the COVID-19 pandemic has led to the development of a wide range of serological tests suitable for evaluating SARS-CoV-2 exposure, infection or vaccination status [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Typically, these tests are approved for use by the regulatory authorities based on their performance against a panel of reference sera including positive and negative controls at either 14- or 21-days post infection [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePublic Health England reported a 93.9% sensitivity for the Abbott SARS-CoV-2 IgG Nucleoprotein assay [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and 100% for the Roche Elecsys Nucleoprotein assay at \u0026ge;14 days post infection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This led to widespread adoption of these tests across NHS laboratories for testing at population level. Other studies have confirmed this test performance at 14-21 days post infection [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Population level serological studies have also based their conclusions - vital to guide national policy - on the basis of these tests [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] without considering how time since infection influences the performance of the test. The problem with this approach is that it does not take into account SARS-CoV-2 humoral dynamics and changes in avidity over time [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although serological tests with limited diagnostic range may demonstrate excellent sensitivity shortly after infection, it is unclear how they will perform with time following infection or vaccination.\u003c/p\u003e \u003cp\u003eIn order to address this question, we applied 4 widely used serological assays in parallel to serial samples from the Co-STARs study [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] in which staff testing seropositive to SARS-CoV-2 were followed for up to 200 days following infection. We compared the proportion of samples that remained seropositive over time using a survival analysis and determined the decay rate of the nucleoprotein (N) antibody and the spike (S) antibody for each test using a previously published mathematical model fitted to the data.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting and design\u003c/h2\u003e \u003cp\u003eSerological testing was performed on stored serum samples collected as part of the Co-STARs study (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.clinicaltrials.gov\" target=\"_blank\"\u003ewww.clinicaltrials.gov\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e, NCT04380896) run at Great Ormond Street Hospital between April and November 2020 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The study had national Integrated Research Application System (IRAS) approval and all experimental protocols were approved. Briefly, Co-STARs was a 1-year single-centre prospective cohort study of antibody responses to COVID-19 infection in healthcare workers. Serum samples were taken from the 3657 participants at baseline and underwent a screening ELISA using the EDI assay. Repeated monthly serum samples were then taken from those with a seropositive baseline screening test for up to 250 days after the date of infection. Those samples identified as seropositive with available symptom start date had further confirmatory testing with the quantitative three antigen MSD assay.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants:\u003c/h2\u003e \u003cp\u003eThe majority of hospital staff were eligible for the Co-STARS study [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Only those participants with significant immunosuppression, those that had received blood products within 6 months of recruitment and those that had active and ongoing symptoms of SARS-CoV-2 infection (within the last 21 days) were excluded. Only samples from individuals with at least one positive test from any platform were included in the analysis. Moreover, individuals without a known symptom start date were removed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eAs part of the Co-STARs study all participants undertook a detailed standardised online questionnaire at study entry [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This included the date of onset of COVID-19 symptoms, and any SARS-CoV-2 diagnostic test results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eComparison of serological assays\u003c/h2\u003e \u003cp\u003eSamples taken as part of the Co-STARS study [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] which had an accompanying symptom start date available for analysis were initially screened for seropositivity by the EDI assay or by any of the three antigens of the Meso Scale Discovery (MSD) assay. The selected samples underwent testing with 4 serological assays: 1) The Roche Elecsys Anti-SARS-CoV-2 electrochemiluminescence immunoassay (ECLIA) assay detects the nucleocapsid (N) antigen (Roche-N); 2) the Roche Elecsys Anti-SARS-CoV-2 S electrochemiluminescence immunoassay (ECLIA) assay detects the spike (S) antigen (Roche-S); 3) the Abbott Nucleoprotein Chemiluminescent Microparticle Immunoassay (CLMIA) assay detects the nucleocapsid (N) antigen (Abbott-N); 4) The four antigen Meso Scale Discovery (MSD) assay was undertaken at the WHO Pneumococcal Supranational Reference Laboratory at the UCL Institute of Child Health. Only 3 antigens were reported from the MSD assay (the Spike, the Nucleoprotein and the receptor binding domain, RBD) as the baseline test performance of the N-terminal domain (NTD) antibody response was insufficient for further evaluation as previously reported [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The Roche-N and Roche-S assays were undertaken by the Laboratory Medicine Service of Swansea Bay University Health Board, Morriston Hospital, Swansea. The Abbott-N assay was undertaken by Public Health Wales Microbiology at Cardiff and Vale University Hospital. All samples were stored and transported between laboratories at -80oC and only removed for aliquoting prior to testing to avoid unnecessary freeze-thaw cycles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis and Modelling\u003c/h2\u003e \u003cp\u003eIn order to evaluate the relative proportion of seropositive tests in the parallel serological assays over time, a time-to-event analysis was performed using the time from symptom onset and the first negative test for each assay after a first positive test as the event of interest using the R package \u003cem\u003esurvival\u003c/em\u003e [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Only tests taken \u0026gt;14 days after symptom onset were considered in the analysis (albeit no tests were performed between 14- and 21-days post symptoms meaning \u0026gt;14 or \u0026gt;21 days post symptom results were identical). A participant was defined as seropositive when at least one of the 4 tests undertaken was seropositive. If the other tests that were run in parallel never became seropositive, the time-to-event was set to the earliest test taken for that individual. If a participant never became seronegative during the follow-up period, a right-censored observation was added at the time of the last serological test. Additionally, the decay rate after 21 days since symptom onset was estimated using a Bayesian generalized mixed model, where time from symptom onset was included as a fixed effect and study participants as a random effect. The decay rate was estimated from the slope of the regression model.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 950 samples from 329 participants seropositive by any assay after 14 days underwent testing with the Roche-N, Roche-S, the MSD and the Abbott-N assay. The majority of the participants (98%, 321/329) had a positive result by two or more assays.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAntibody Decay with Time\u003c/strong\u003e \u003cp\u003ePlotting the raw log transformed antibody titres over time since symptom onset (Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) demonstrated that antibody dynamics were dependent on the assay undertaken. The production of spike antibodies was demonstrated to be maintained at high levels up to 200 days when evaluated by the MSD and the quantitative Roche -S assay. All nucleoprotein antibody assays demonstrated decay of the nucleoprotein antibody over time. This was most pronounced in the Abbott-N assay and much less so in the Roche -N assay which demonstrated slow waning of the nucleoprotein antibody.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAssay Sensitivity with Time Post Symptom Onset\u003c/strong\u003e \u003cp\u003eThe existing published test performance for all assays undertaken is provided in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The sensitivity of all assays (at least 14 days from symptom onset) at 50, 100 and 150 days is provided in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All assays demonstrated a reasonable sensitivity at 50 days following infection. As time passed following infection, the Abbott-N assay rapidly became seronegative, with a median survival time inferred at 175 days (95% CI 168-185 days), whereas the survival probability at 150 days was inferred to be 95% for the Roche-N (95% CI 0.92 - 0.97), and 91% for the MSD-N assay (95% CI 0.87 - 0.94). The Roche-S and MSD-S assays remained seropositive for the duration of the study. The MSD-RBD assay showed some evidence of waning seropositivity over time (90% Survival probability at 150 days, 95% CI 0.88 - 0.94).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eA total of 45% (159/329) of the individuals had a negative result using the Abbott-N assay during the course of the study. For the MSD test, 16% (52/329) of participants had a negative test for the N antigen, 11% (36/329) for RBD, and 3% (11/329) for the S antigen. For the Roche platform, 5.5% (18/329) of the individuals had a negative result with the Roche-N assay, while only 4.8% (16/329) of them had a negative result for the S antigen over the course of the study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eA summary of the existing published data for the commercially available tests in this comparison.\u003c/b\u003e The corresponding antigen target and published sensitivity, specificity, positive predictive value and negative predictive value (if available).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTests\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManufacturer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTarget Antigen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSens\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpec\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e# Samples/Patients\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDays post symptom onset\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbbott-N [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbbott-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNucleoprotein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCLMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0% (day 17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e689/125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ge;21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoche-N [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoche Cobas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNucleoprotein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eECLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e496/102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ge;14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoche-S [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoche Cobas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpike protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eECLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1485\u003csup\u003e\u0026Dagger;\u003c/sup\u003e/331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ge;15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMSD [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMeso Scale Discovery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNucleoprotein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eECLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e196/196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ge;21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpike protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47/47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ge;21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRBD (receptor binding domain)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47/47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ge;21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eECLIA: Electro Chemiluminescent Immunoassay, CLMIA: Chemiluminescent Microparticle Immuno Assay PPV: Positive Predictive Value, NPV: Negative Predictive Value, Sens: Sensitivity, Spec: Specificity, ELISA: Enzyme Linked Immunosorbent Assay\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eThe highest reported sensitivity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u0026Dagger;233 of these samples were tested at \u0026ge;15 days post PCR diagnosis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003eFor Sensitivity Testing\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity of compared assays at 50, 100 and 150 days from symptom onset.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSurvival probability (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e50-day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100-day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e150-day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAbbott-N\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.985 (0.97;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.919 (0.89;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.655 (0.6;0.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRoche-N\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.988 (0.98;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.963 (0.94;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.949 (0.92;0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRoche-S\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.991 (0.98;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.966 (0.95;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.952 (0.93;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMSD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e-N\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.988 (0.98;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.972 (0.95;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.907 (0.87;0.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e-S\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.997 (0.99;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.978 (0.96;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.968 (0.95;0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e-RBD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.994 (0.99;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.969 (0.95;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.909 (0.88;0.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMathematical Model Fits to Estimate Long-Term Antibody Decay\u003c/strong\u003e \u003cp\u003eTo estimate the decay rate for each antibody and assay studied, a generalized linear mixed model was fitted to the trajectory of antibody decay after 21 days from symptom onset, where the decay rate was estimated as the slope of the antibody titer through time. Under the most sensitive and quantitative Roche -S assay the spike antibody demonstrated no decay at all and rather a slow rate of increased titres over time from symptom onset (0.0031, 95% CI 0.0018 \u0026mdash; 0.0044, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). In accordance with the raw observed data, all nucleoprotein antibodies under the mathematical model decayed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). This was most pronounced in the Abbott-N assay (-0.022, 95% CI -0.023 \u0026mdash; -0.02) and least pronounced in the Roche -N assay (-0.0025, 95% CI -0.0039 \u0026mdash; -0.0012, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Roche-S assay target the spike antibody, the Abbott-N and the Roche-N assays target the N-antibody while the MSD assay targets the N-, the S- and the antibody to the Receptor Binding Domain (RBD) of the spike protein in parallel. (a) Kaplan-Meier curve and numbers at risk (the number of participants under follow up with serological tests available for analysis at that time point) for different serological tests. Y-axis represents the probability of remaining seropositive, while the X-axis shows days after symptom onset with numbers of participants under follow up shown in the table below. (b) Inferred posterior density distributions of the decay rate in a generalized linear mixed model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDecay rate for each serological assay (log arbitrary units per day) estimated in a generalized linear mixed model.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSD-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.0121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0134;-0.0107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSD-RBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.0068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008;-0.0055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSD-S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.0035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0048;-0.0023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbbott-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.0216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0229;-0.0204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoche-S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0018;0.0044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoche-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.0025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0039;-0.0012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe lower performance of the Abbott-N assay can be explained by a lower detection of titer values as their concentration wanes over time. When compared to the quantitative MSD-N, 26% (222/860) of all positive samples by the MSD-N were negative for the Abbott-N test (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A total of 75% of samples (137/ 183) positive by the MSD-N with an MSD arbitrary titer value lower than 403 were negative for the Abbott-N assay.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe quantitative results for the MSD-N assay were compared to those of the Abbot-N test for each sample taken. Colours divide the samples depending on whether it was positive (green) or negative (red) for the MSD-N assay. Dotted red lines represent the seropositivity threshold for the Abbott-N assay (horizontal) and the MSD-N test (vertical).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSensitive measurement of SARS-CoV-2 seropositivity is key to evaluate who has been infected or exposed to SARS-CoV-2, to determine the correlates of protection from future disease, stratify those that need booster vaccination and target the use of anti-SARS-CoV-2 antibodies to those that are seronegative. To our knowledge no other study has evaluated the sensitivity of multiple diagnostic tests in parallel on longitudinally collected serological samples. This study demonstrates that as time elapses after infection, the sensitivity of serological testing varies widely depending on the test used. Although serological tests may be demonstrated to perform well 14-21 days after infection, this initial test performance often diminishes as time passes. In order to evaluate whether or not the population maintains SARS-CoV-2 antibodies it is vital that we utilize serological tests that remain sensitive over time.\u003c/p\u003e \u003cp\u003eInitial published baseline test performance reports concluded that the Abbott-N assay was a high-performance test and a key tool in SARS-CoV-2 surveillance [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Our data demonstrate that as time passes following infection the sensitivity of this assay declines rapidly until at \u0026lt;6 months following infection it is no more than 50% sensitive. Our findings support the concerns raised by others regarding the poor performance of some nucleoprotein based assays [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, the Roche assays, particularly the Roche Elecsys Anti-SARS-CoV-2 Spike assay maintained high sensitivity for the 200-day duration of the study. Although there remains no single correlate of sterilizing or protective immunity following SARS-CoV-2 infection or vaccination, it is clear that natural infection and the presence of neutralizing spike antibodies decreases the possibility of re-infection and the severity of disease upon re-exposure to currently circulating strains [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our finding that neutralizing spike antibodies remained at high titres 200 days after infection adds to our previous study on this topic [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and provides further evidence in support of long-lasting protection against severe disease from currently circulating strains. Fitting mathematical models to the raw data of the Roche spike assay demonstrated that spike antibody titres did not decay but rather increased slightly over the duration of the study. The Roche nucleoprotein assay also maintained sensitivity for the duration of the study with a low rate of decay. Although this assay is semi-quantitative, our findings suggest that this could be used to sensitively identify those that have been vaccinated from those that have been both vaccinated and infected. This has relevance for the diagnosis of long covid, MIS-C and COVID infection post vaccination.\u003c/p\u003e \u003cp\u003eMany studies have evaluated the impact of time on test sensitivity over the first 3 weeks following symptom onset [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, we found no other study that had examined the sensitivity of antibody testing on parallel longitudinal samples collected between 1-6 months after infection or exposure. Assays with a higher titer cut-off for detection may perform well in the initial period after infection, but fail to detect seropositivity as antibody levels wane over time. We show that the Abbott-N test failed to detect 75% of samples positive for the MSD-N with a titer value lower than 403, which makes the Abbott-N assay less suitable for seroprevalence studies. Barzin et al [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] used Abbott-N testing alone to determine SARS-CoV-2 seroprevalence in 2,973 asymptomatic out-patients in North Carolina estimating a seroprevalence of 0.8%. Similarly, Wilkins et al [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] used Abbott-N on 6510 healthcare workers up to 150 days after symptom onset and estimated a seroprevalence of 4.8%. Our findings suggest that previously published surveys of SARS-CoV-2 seroprevalence such as these could have significantly underestimated the true prevalence of SARS-CoV-2 humoral immunity.\u003c/p\u003e \u003cp\u003eMemory T-cell interferon gamma release or proliferation assays in response to SARS-CoV-2 antigens provide an alternative means of assessing prior exposure to infection. However, these assays are limited by cross reactive immunity to the seasonal coronaviruses decreasing specificity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough all serological tests used in the study demonstrated a high initial specificity, one limitation of this study is that only 38% of participants had a confirmatory SARS-CoV-2 PCR result. Our data may therefore be influenced by an unknown proportion of falsely positive serological tests. However, at entry to the study, all seropositive participants had both a screening EDI nucleoprotein assay and an MSD assay performed which limited the chances of a falsely positive result due to a single erroneous test. Not all samples were processed at the same time; the Roche and Abbott-N assays were processed 3 months after the MSD assays. Despite this, we believe that sample storage and freeze-thawing cycles are unlikely to have influenced our findings as the Roche quantitative spike assay was performed last and demonstrated the highest prolonged levels of spike antibody of all tests used.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, although serological tests may demonstrate high sensitivity 3-weeks after SARS-CoV-2 infection, this is far from the case with some tests 6-months after infection. The Abbott-N assay performed poorly at this time, whereas the Roche and MSD tests maintained a high sensitivity for the 200 days of the study. Tests that perform poorly over time will lead to spurious estimates in population level seroprevalence studies and findings from these studies should be adjusted to account for sensitivity of the test used and the time since infection. Test performance as time passes post infection should be considered before evaluating who is a candidate for booster vaccination or anti-SARS-CoV-2 antibody therapy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARS-CoV-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSevere acute respiratory syndrome coronavirus 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMeso Scale Discovery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRoche-N\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRoche Elecsys-Nucleoprotein assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRoche-S\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRoche Elecsys-Spike assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAbbott-N\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAbbott Nucleoprotein assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCo-STARs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCOVID-19 Staff Testing of Antibody Responses Study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnzyme Linked Immunosorbent Assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDI assay\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEpitope Diagnostics, Inc.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCLMIA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChemiluminescent Microparticle Immunoassay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceptor binding domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNTD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-terminal domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECLIA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectro Chemiluminescent Immunoassay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMIS-C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultisystem inflammatory syndrome in children\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study had national Integrated Research Application System (IRAS) approval and all participants in the study provided informed consent. All methods were carried out in accordance with relevant guidelines and regulations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the Health Data Research Innovation UK (HDRUK) repository, https://web.www.healthdatagateway.org/dataset/435bfcda-f378-44f6-9387-042d959eb945.\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLG was supported by the Wellcome Trust (201470/Z/16/Z), the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award number 1R01AI146338, the GOSH Charity (VC0921) and the GOSH/ICH Biomedical Research Centre (www.nihr.ac.uk). AS was supported by the Wellcome Trust (220565/Z/20/Z). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe first draft of the manuscript was prepared by: ATO, FFT, AT, JH, RD, ALM, DG, RS, KG and LG. The study was designed and implemented by: LG, ATO, JH, RD, RS, DG and KG. Testing for SARS-CoV-2 RNA and antibody was conducted by: LG, FFT, ALM, KG, JH, RD, RS and DG. Data analysis was carried out by ATO and LG.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to dedicate this article to the staff members who died of COVID-19 at Great Ormond Street Hospital during the first wave of the pandemic. We would also like to thank all the staff at Great Ormond Street Hospital who have taken part in the study. In addition, we are very grateful for all the hard work undertaken by the Great Ormond Street rapid response and microbiology laboratory staff and the staff in the immunology laboratories both in the Camelia Botnar Laboratory and the Great Ormond Street Institute of Child Health who ensured that all the PCR tests and serological assays were completed in a timely manner. The authors would also like to thank the biomedical scientists and colleagues in the affiliated laboratories for their hard work in running the samples and collating the results. RD would like to thanks Linda Tyson and Jon Evans of the Wales National Virology Centre, PHW Microbiology Cardiff. RS would like to thank Non Gwynn, Jenna Walters, James Murphy and colleagues in Laboratory Medicine, Morriston Hospital, Swansea.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBastos ML, Tavaziva G, Abidi SK, Campbell JR, Haraoui L-P, Johnston JC, et al. Diagnostic accuracy of serological tests for covid-19: systematic review and meta-analysis. BMJ. 2020;370:m2516.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKubina R, Dziedzic A. Molecular and Serological Tests for COVID-19. A Comparative Review of SARS-CoV-2 Coronavirus Laboratory and Point-of-Care Diagnostics. Diagnostics (Basel). 2020;10:434.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLa Marca A, Capuzzo M, Paglia T, Roli L, Trenti T, Nelson SM. Testing for SARS-CoV-2 (COVID-19): a systematic review and clinical guide to molecular and serological in-vitro diagnostic assays. Reprod Biomed Online. 2020;41:483\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng MP, Yansouni CP, Basta NE, Desjardins M, Kanjilal S, Paquette K, et al. Serodiagnostics for Severe Acute Respiratory Syndrome\u0026ndash;Related Coronavirus-2. Ann Intern Med. 2020;:M20-2854.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvaluation_of_Abbott_SARS_CoV_2_IgG_PHE.pdf.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvaluation_of_Roche_Elecsys_anti_SARS_CoV_2_PHE_200610_v8.1_FINAL.pdf.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoste AT, Jaton K, Papadimitriou-Olivgeris M, Greub G, Croxatto A. Comparison of SARS-CoV-2 serological tests with different antigen targets. J Clin Virol. 2021;134:104690.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAinsworth M, Andersson M, Auckland K, Baillie JK, Barnes E, Beer S, et al. Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison. The Lancet Infectious Diseases. 2020;20:1390\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoll\u0026aacute;n M, P\u0026eacute;rez-G\u0026oacute;mez B, Pastor-Barriuso R, Oteo J, Hern\u0026aacute;n MA, P\u0026eacute;rez-Olmeda M, et al. Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study. The Lancet. 2020;:S0140673620314835.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrandjean L, Saso A, Ortiz AT, Lam T, Hatcher J, Thistlethwayte R, et al. Long-Term Persistence of Spike Antibody and Predictive Modeling of Antibody Dynamics Following Infection with SARS-CoV-2. Clinical Infectious Diseases. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/cid/ciab607\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBauer G, Struck F, Schreiner P, Staschik E, Soutschek E, Motz M. The challenge of avidity determination in SARS-CoV-2 serology. Journal of Medical Virology. 2021;93:3092\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreat Ormond Street Hospital for Children NHS Foundation Trust. COVID-19 Staff Testing of Antibody Responses Study (CO-STARS). Clinical trial registration. clinicaltrials.gov; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson M, Wagstaffe HR, Gilmour KC, Mai AL, Lewis J, Hunt A, et al. Evaluation of a novel multiplexed assay for determining IgG levels and functional activity to SARS-CoV-2. J Clin Virol. 2020;130:104572.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR: The R Project for Statistical Computing. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003c/span\u003e. Accessed 16 Dec 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTherneau TM, Grambsch PM. The Cox Model. In: Therneau TM, Grambsch PM, editors. Modeling Survival Data: Extending the Cox Model. New York, NY: Springer; 2000. p.\u0026nbsp;39\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBryan A, Pepper G, Wener MH, Fink SL, Morishima C, Chaudhary A, et al. Performance Characteristics of the Abbott Architect SARS-CoV-2 IgG Assay and Seroprevalence in Boise, Idaho. Journal of Clinical Microbiology. 58:e00941-20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuench P, Jochum S, Wenderoth V, Ofenloch-Haehnle B, Hombach M, Strobl M, et al. Development and Validation of the Elecsys Anti-SARS-CoV-2 Immunoassay as a Highly Specific Tool for Determining Past Exposure to SARS-CoV-2. Journal of Clinical Microbiology. 58:e01694-20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElecsys Anti-SARS-CoV-2 S - Instructions for Use | FDA. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/media/144037\u003c/span\u003e\u003c/span\u003e. Accessed 9 Sep 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosadas C, Randell P, Khan M, McClure MO, Tedder RS. Testing for responses to the wrong SARS-CoV-2 antigen? The Lancet. 2020;396:e23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolotin S, Tran V, Osman S, Brown KA, Buchan SA, Joh E, et al. SARS-CoV-2 seroprevalence survey estimates are affected by anti-nucleocapsid antibody decline. J Infect Dis. 2021;:jiaa796.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHall VJ, Foulkes S, Charlett A, Atti A, Monk EJM, Simmons R, et al. SARS-CoV-2 infection rates of antibody-positive compared with antibody-negative health-care workers in England: a large, multicentre, prospective cohort study (SIREN). The Lancet. 2021;397:1459\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitman JD, Hiatt J, Mowery CT, Shy BR, Yu R, Yamamoto TN, et al. Evaluation of SARS-CoV-2 serology assays reveals a range of test performance. Nat Biotechnol. 2020;38:1174\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePiec I, English E, Thomas MA, Dervisevic S, Fraser WD, John WG. Performance of SARS-CoV-2 serology tests: Are they good enough? PLOS ONE. 2021;16:e0245914.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Ai J, Loeffelholz MJ, Tang Y-W, Zhang W. Meta-analysis of diagnostic performance of serology tests for COVID-19: impact of assay design and post-symptom-onset intervals. Emerg Microbes Infect. 9:2200\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarzin A, Schmitz JL, Rosin S, Sirpal R, Almond M, Robinette C, et al. SARS-CoV-2 Seroprevalence among a Southern U.S. Population Indicates Limited Asymptomatic Spread under Physical Distancing Measures. mBio. 2020;11:e02426-20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilkins JT, Gray EL, Wallia A, Hirschhorn LR, Zembower TR, Ho J, et al. Seroprevalence and Correlates of SARS-CoV-2 Antibodies in Health Care Workers in Chicago. Open Forum Infectious Diseases. 2021;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe Bert N, Tan AT, Kunasegaran K, Tham CYL, Hafezi M, Chia A, et al. SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 2020;584:457\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipsitch M, Grad YH, Sette A, Crotty S. Cross-reactive memory T cells and herd immunity to SARS-CoV-2. Nat Rev Immunol. 2020;20:709\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, COVID-19, virus, nucleoprotein, spike protein, antibody, assay, serology.","lastPublishedDoi":"10.21203/rs.3.rs-1286644/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1286644/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Serological testing is used to quantify SARS-CoV-2 seroprevalence, guide booster vaccination and select patients for anti-SARS-CoV-2 antibodies therapy. However, our understanding of how serological tests perform as time passes after infection is limited.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Four assays were compared in parallel: 1) the multiplexed spike, nucleoprotein and receptor binding domain Meso Scale Discovery (MSD) assay 2) the Roche Elecsys-Nucleoprotein assay (Roche-N) 3) the Roche Spike assay (Roche-S) and 4) the Abbott Nucleoprotein assay (Abbott-N) on serial positive monthly samples from hospital staff up to 200 days following infection as part of the Co-Stars study.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe demonstrate that 50% of the Abbott-N assays give a negative result after 175 days (median survival time 95% CI 168-185 days) while the Roche-N assay (93% survival probability at 200 days, 95% CI 88-97%) maintained seropositivity. The MSD spike (97% survival probability at 200 days, 95% CI 95-99%) and the Roche-S assay (95% survival probability at 200 days, 95% CI 93-97%) also remained seropositive. The best performing quantitative Roche-S assay showed no evidence of waning Spike antibody titres over 200-days.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe Abbott-N assay fails to detect SARS-CoV-2 antibodies as time passes since infection. In contrast the Roche and the MSD assays maintained high sensitivity. The limitations of the Abbott assay must be considered in clinical decision making. The long duration of detectable neutralizing spike antibody titres by the quantitative Roche-S assay provides further evidence in support of long-lasting SARS-CoV-2 protection to pre-existing strains of SARS-CoV-2 following natural infection.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e: Co-STARs study was registered with ClinicalTrials.gov on May 8th, 2020, with trial number NCT04380896 (www.clinicaltrials.gov, NCT04380896)\u003c/p\u003e","manuscriptTitle":"The Influence of Time on the Sensitivity of SARS-CoV-2 Serological Testing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-02-17 14:58:21","doi":"10.21203/rs.3.rs-1286644/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-04-11T15:38:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-10T19:40:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-05T06:43:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"066db536-f533-4a84-8945-8d1ad00c7073","date":"2022-03-30T22:24:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3289b14d-d0fc-43e0-8dc7-b863fd443037","date":"2022-03-21T08:36:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-03-21T08:07:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-03-10T19:44:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-02-15T17:43:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-02-15T12:35:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2022-01-22T14:16:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05c4af7f-c7a4-4945-8069-dd7f3c0f4ac1","owner":[],"postedDate":"February 17th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-06-06T07:14:15+00:00","versionOfRecord":[],"versionCreatedAt":"2022-02-17 14:58:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1286644","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1286644","identity":"rs-1286644","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}