Bolehsaja jika kamu merasa perlu melakukan cek antibodi IgG SRBD/ SARS COV-2 Quantitative Test setelah mendapat vaksin. Cek antibodi bisa dilakukan untuk memantau dan mengetahui kadar antibodi yang dimiliki tubuh. Biar lebih mudah, pakai aplikasi Halodoc untuk mencari tahu rumah sakit atau fasilitas kesehatan yang menunjang pemeriksaan ini. PemeriksaanAnti Sars Cov2 Kuantitatif RBD, Apa Itu? Tahukah Anda? Pemeriksaan RBD (Receptor Binding Domain) ini bertujuan untuk mengukur kemampuan Antibodi melawan SARS COV-2 dan sampel darah Read More. 2021-03-29 04:12:36; Kegiatan Health Talk Bersama PT. Catur Mitra Sejati (Mitra 10) Pemeriksaanini berfungsi sebagai baseline kuantitatif antibody terhadap SARS COV-2 untuk mengevaluasi respons imun individu terhadap virus SARS CoV-2, sehingga memungkinkan dokter menilai UjianPantas Kendiri SARS-CoV-2 S-RBD IgG Antibodi (Darah Dari Jari) adalah immunoassay kromatografi pantas yang bertujuan untuk mengesan kualitatif antibodi IgG terhadap SARS-CoV-2 spike (S) Receptor Binding Domain (RBD) pada manusia melalui darah dari jari selepas 10 hari jangkitan dan / atau vaksinasi SARS-CoV-2. Ujian ini digunakan sebagai Mengevaluasiatau mengukur secara Kuantitatif antibodi terhadap protein S-RBD yang mempunyai daya netralisasi virus SARS-CoV-2 pada : 1.Penyintas COVID-19 ( orang yang pernah terinfeksi COVID-19) 2.Pasien pasca vaksinasi COVID-19 3.Donor plasma konvalesen Anti SARS-CoV-2 • Anti SARS-CoV-2 Kuantitatif Pemeriksaan Gen dan Antigen: • SARS-CoV-2 RNA • Antigen SARS-CoV-2. Expanded Lipid Profile (ELP) Prodia.co.id. FRAMINGHAM RISK SCORE •Sex •Age •Diabetes •Total cholesterol (mg/dL) •Cigarette smoker •HDL cholesterol . . 2021 Oct;2710 doi Epub 2021 Jun 7. Sheila F Lumley 2 , Jia Wei 3 , Stuart Cox 4 , Tim James 4 , Anita Justice 4 , Gerald Jesuthasan 4 , Denise O'Donnell 3 , Alison Howarth 3 , Stephanie B Hatch 3 , Brian D Marsden 5 , E Yvonne Jones 3 , David I Stuart 3 , Daniel Ebner 6 , Sarah Hoosdally 7 , Derrick W Crook 2 , Tim E A Peto 2 , Timothy M Walker 8 , Nicole E Stoesser 2 , Philippa C Matthews 2 , Koen B Pouwels 9 , A Sarah Walker 7 , Katie Jeffery 4 Affiliations PMID 34111577 PMCID PMC8180449 DOI Free PMC article Quantitative SARS-CoV-2 anti-spike responses to Pfizer-BioNTech and Oxford-AstraZeneca vaccines by previous infection status David W Eyre et al. Clin Microbiol Infect. 2021 Oct. Free PMC article Abstract Objectives We investigated determinants of severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 anti-spike IgG responses in healthcare workers HCWs following one or two doses of Pfizer-BioNTech or Oxford-AstraZeneca vaccines. Methods HCWs participating in regular SARS-CoV-2 PCR and antibody testing were invited for serological testing prior to first and second vaccination, and 4 weeks post-vaccination if receiving a 12-week dosing interval. Quantitative post-vaccination anti-spike antibody responses were measured using the Abbott SARS-CoV-2 IgG II Quant assay detection threshold ≥50 AU/mL. We used multivariable logistic regression to identify predictors of seropositivity and generalized additive models to track antibody responses over time. Results 3570/3610 HCWs were seropositive >14 days post first vaccination and prior to second vaccination 2706/2720 were seropositive after the Pfizer-BioNTech and 864/890 following the Oxford-AstraZeneca vaccines. Previously infected and younger HCWs were more likely to test seropositive post first vaccination, with no evidence of differences by sex or ethnicity. All 470 HCWs tested >14 days after the second vaccination were seropositive. Quantitative antibody responses were higher after previous infection median IQR >21 days post first Pfizer-BioNTech 14 604 7644-22 291 AU/mL versus 1028 564-1985 AU/mL without prior infection p 21 days post second Pfizer vaccination in those not previously infected, 10 058 6408-15 582 AU/mL, were similar to those after prior infection followed by one vaccine dose. Conclusions SARS-CoV-2 vaccination leads to detectable anti-spike antibodies in nearly all adult HCWs. Whether differences in response impact vaccine efficacy needs further study. Keywords Antibody; Quantitative anti-spike antibody; SARS-CoV-2; Serology; Vaccine. Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved. Figures Fig. 1 Anti-spike IgG-positive results by days since first vaccination, by prior infection status and vaccine received. Tests performed after a second dose of vaccine are not included. The number of tests performed and positive and the resulting percentage is shown under each bar. Fig. 2 The relationship between vaccine, age and probability of testing anti-spike IgG seropositive >14 days post first vaccination. Model predictions are shown using reference categories for sex and ethnicity white, female, respectively and in those without prior evidence of infection. Fig. 3 Modelled quantitative anti-spike IgG responses following first vaccination by vaccine and previous infection status. Panels A and B show responses in previously infected healthcare workers HCWs and panels C and D HCWs without evidence of previous infection. Panels A and C show data for those receiving Pfizer–BioNTech vaccine and panels B and D Oxford–AstraZeneca vaccine. Model predictions are shown at three example ages 30, 45, and 60 years. The shaded ribbon shows the 95% confidence interval. Values are plotted from 7 days prior to vaccination to illustrate baseline values models are fitted using data from 28 days prior to vaccination onwards. Fig. 4 Modelled quantitative anti-spike IgG titres following second Pfizer–BioNTech vaccination by previous infection status. Panel A shows those who were previous infected including those previously infected at baseline or testing PCR-positive between vaccines and panel B those who had no evidence of previous infection. Model predictions are shown at three example ages 30, 45, and 60 years. The shaded ribbon shows the 95% confidence interval. Data were included in each model from 7 days before the second vaccination to allow pre-vaccination levels to be fitted correctly. Similar articles Low immunogenicity to SARS-CoV-2 vaccination among liver transplant recipients. Rabinowich L, Grupper A, Baruch R, Ben-Yehoyada M, Halperin T, Turner D, Katchman E, Levi S, Houri I, Lubezky N, Shibolet O, Katchman H. Rabinowich L, et al. J Hepatol. 2021 Aug;752435-438. doi Epub 2021 Apr 21. J Hepatol. 2021. PMID 33892006 Free PMC article. Immunogenicity of COVID-19 Tozinameran Vaccination in Patients on Chronic Dialysis. Schrezenmeier E, Bergfeld L, Hillus D, Lippert JD, Weber U, Tober-Lau P, Landgraf I, Schwarz T, Kappert K, Stefanski AL, Sattler A, Kotsch K, Dörner T, Sander LE, Budde K, Halleck F, Kurth F, Corman VM, Choi M. Schrezenmeier E, et al. Front Immunol. 2021 Jun 30;12690698. doi eCollection 2021. Front Immunol. 2021. PMID 34276681 Free PMC article. Immunogenicity of the BNT162b2 COVID-19 mRNA vaccine and early clinical outcomes in patients with haematological malignancies in Lithuania a national prospective cohort study. 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Infect Drug Resist. 2022. PMID 36600955 Free PMC article. References Folegatti Ewer Aley Angus B., Becker S., Belij-Rammerstorfer S. Safety and immunogenicity of the ChAdOx1 nCoV-19 vaccine against SARS-CoV-2 a preliminary report of a phase 1/2, single-blind, randomised controlled trial. Lancet. 2020;396467–478. - PMC - PubMed Wajnberg A., Amanat F., Firpo A., Altman Bailey Mansour M. Robust neutralizing antibodies to SARS-CoV-2 infection persist for months. Science. 2020;3701227–1230. - PMC - PubMed GeurtsvanKessel Okba Igloi Z., Bogers S., Embregts Laksono An evaluation of COVID-19 serological assays informs future diagnostics and exposure assessment. Nat Commun. 2020;113436. - PMC - PubMed Medicines and Healthcare products Regulatory Agency . 2020. MHRA guidance on coronavirus COVID-19 Walsh Frenck Falsey Kitchin N., Absalon J., Gurtman A. Safety and immunogenicity of two RNA-based Covid-19 vaccine candidates. N Engl J Med. 2020;3832439–2450. - PMC - PubMed MeSH terms Substances LinkOut - more resources Full Text Sources Elsevier Science Europe PubMed Central PubMed Central Medical Genetic Alliance MedlinePlus Health Information Miscellaneous NCI CPTAC Assay Portal Ao longo da pandemia de Covid-19, muitos nomes que não costumavam fazer parte da nossa vida se tornaram comuns. Boa parte dessas palavras novas são semelhantes e até parecem sinônimos, mas se referem a conceitos diferentes. Entender exatamente o que quer dizer cada novo termo da pandemia é importante para evitar a propagação de informações falsas ou incompletas. A diretora do Laboratório de Biotecnologia Viral do Instituto Butantan, Soraia Attie Calil Jorge, explica alguns desses conceitos e mostra por que é tão importante entendê-los. Vírus x Bactérias Vírus seres que dependem de outros para se reproduzir, ou seja, que precisam infectar células humanas, de plantas e até de bactérias para dar origem a seus descendentes. Não possuem células por isso se discute se são seres vivos ou não, apenas material genético e proteína. Às vezes, levam consigo parte da membrana da célula que infectaram; por isso, existem vírus envelopados e vírus não-envelopados, sendo que o envelopado é aquele que passou a ter em sua formação parte da membrana da célula invadida. Quando entram em nosso corpo, rompendo a membrana para se multiplicar, geralmente estouram nossas células, causando sua lise dissolução. Bactéria organismos mais independentes do que os vírus. São células que possuem material genético e diversos mecanismos para se desenvolver e multiplicar, sem precisar de outra célula. Por mais que algumas sejam prejudiciais ao nosso corpo, existem certas bactérias em nosso organismo que são benéficas e não causam doença alguma, geralmente fornecem substâncias importantes ou regulam parte do nosso metabolismo. Coronavírus X SARS-CoV-2 X Covid-19 Coronavírus nome dado a uma extensa família de vírus que se assemelham. Muitos deles já nos infectaram diversas vezes ao longo da história da humanidade. Dentro dessa família há vários tipos de coronavírus, inclusive os chamados SARS-CoVs a síndrome respiratória aguda grave, conhecida pela sigla SARS, que há alguns anos começou na China e se espalhou para países da Ásia, também é causada por um coronavírus. SARS-CoV-2 vírus da família dos coronavírus que, ao infectar humanos, causa uma doença chamada Covid-19. Por ser um microrganismo que até pouco tempo não era transmitido entre humanos, ele ficou conhecido, no início da pandemia, como “novo coronavírus”. Covid-19 doença que se manifesta em nós, seres humanos, após a infecção causada pelo vírus SARS-CoV-2. Prevalência x Incidência Prevalência visão geral de uma doença, ou seja, quantos casos ou mortes aquela doença provocou em sua totalidade. No Brasil, já temos mais de 21 milhões de casos e mais de 588 mil mortes por Covid-19, então esse número equivale à prevalência da doença. Incidência é um indicador mais fechado, que não olha em âmbito geral para uma doença, mas traça um recorte em determinado período de tempo. Em agosto, o Brasil registrou a menor incidência mensal de mortes por Covid-19 em 2021, com pouco mais de 24 mil óbitos. Mortalidade x Letalidade Mortalidade É o tanto de pessoas que adoeceram e morreram em relação a toda a população de uma região. Tem relação com um cenário geral, como a totalidade de mortos por determinada doença em uma população inteira durante uma pandemia, epidemia ou surto. Letalidade está ligada ao patógeno o vírus SARS-CoV-2, no caso e avalia o número de mortes em relação às pessoas que apresentam a doença ativa, e não em relação à população toda. Em outras palavras, mede a porcentagem de pessoas infectadas que evoluem para óbito. O SARS-CoV-2 não tem uma alta letalidade 2,9%, pois muitas pessoas que contraem o vírus ficam assintomáticas, às vezes sem nem mesmo saber que estão infectadas. IntroductionIt has been more than one year since the first reported case of the novel coronavirus disease 2019 COVID-19, which has already cost more than 2 million lives Fortunately, vaccines against severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 have been developed with record-breaking speed and vaccine programs are ongoing worldwide to take the pandemic under During this expansion of research focus from treatment to prevention of COVID-19, the immune evasion mechanism and immunopathogenic nature of SARS-CoV-2 adds uncertainty to the efficacy of this global vaccination During natural infection, SARS-CoV-2 could avoid the innate antiviral response mediated by interferons IFNs via an array of possible strategies,4,5 which not only leads to viral replication and spreading but also could delay or impair the adaptive immune response including T cell and antibody The significant prevalence of SARS-CoV-2 RNA re-positive cases among discharged patients further raises the concern about the effectiveness and persistency of immune responses after natural Recent long-term follow-up surveys report significant decrease of SARS-CoV-2 antibody titers 5 to 8 months after infection,10,11,12 but its correlation with reduced capacity of SARS-CoV-2 neutralization and immune memory is still vaccination, equally important is the recovery and rehabilitation of COVID-19 Mild cases usually do not require hospitalization but may share similar long-lasting symptoms or discomforts with severe cases, which may reduce life quality after recovery from Also, cardiac magnet resonance imaging cMRI screening revealed surprisingly high prevalence of subclinical myocardial inflammation and fibrosis in recently recovered Due to the overloading of medical systems and the fear of in-hospital transmission, long-term follow-up studies of the structural and functional recovery of COVID-19-involved organs are still this prospective cohort study of recovered COVID-19 patients from Xiangyang, China, we aimed to assess long-term antibody response at 12 months after infection and comprehensively evaluate the structural and functional recovery of the lung and cardiovascular systems. We also attempted to identify potential risk factors associated with those long-term January 15 through 31 March 2020, a total of 307 patients were diagnosed with COVID-19 at Xiangyang Central Hospital, which represented of 549 cases in the downtown and of 1175 cases city-wide. During hospitalization, 12 patients succumbed to COVID-19-induced respiratory distress or lethal infection, which translated to a mortality rate of in line with the citywide mortality rate of 40/1175. All 295 survivors were invited to participate in this study and the final cohort consisted of 121 survivors including 19 recovered from severe COVID-19 Supplementary Fig. 1. Clinical procedures were performed at Xiangyang Central Hospital between 25 December 2020 and 29 January and clinical features of participantsDemographic-wise, this cohort consisted of middle-aged Chinese population with an overall comorbidity prevalence of including hypertension and diabetes as the most common preexisting conditions, which was typical for the local agricultural and industrial population with a preference of high-salt diets Table 1. The participants of this study were among the earliest confirmed COVID-19 patients with virological confirmation dates as early as January 19, 2020. Standard of care consisted of antivirals, antibiotics, immunomodulants and supplemental oxygen was given to participants following CDC guidelines Supplementary Table 1. Only 1 in this cohort received invasive ventilation Supplementary Table 1, which reflected the dismal mortality rate among critically ill patients relying on respiratory Of note, the basic characteristics of this cohort were comparable with the entire population of COVID-19 survivors treated at this hospital Supplementary Table 2.Table 1 Characteristics of participants by COVID-19 severityFull size tableAfter stratifying the cohort by severity graded according to the guideline,21 severe groups had higher ages, less females, and more comorbidities Table 1. Severe group also presented more symptoms at admission, and received more aggressive immunomodulatory therapies, supplemental oxygen, and ICU care during hospitalization Supplementary Table 1. Both severe and non-severe groups share similar lengths since symptom onset, while the severe group had shorter periods since recovery because of longer hospitalization Table 1.Long-lasting SARS-CoV-2 antibody response 1-year after infectionFirst, blood samples were screened by colloidal gold-based immunochromatographic assays GICA separately detecting IgM and IgG against At a median of 11 months post- infection, only 4% 95% CI, 2–10% participants returned positive IgM results, which included both positive and weakly positive results, while 62% 95% CI, 54–71% were IgG positive Table 1, comparing to prevalence of IgM among pre-discharge samples from the same Severe group showed higher prevalence of IgG, while the prevalence of IgM was equally low in both groups Table 1.Next, the concentration of total antibodies against the receptor-binding domain of SARS-CoV-2 spike protein RBD was quantitatively measured by chemiluminescence microparticle immunoassays CMIA.24 Although signal/cutoff S/CO ratios were lower in non-severe group, all but 1 of the results were above the positive diagnostic threshold of S/CO = when all 100 samples of unexposed individuals, which were randomly chosen from sera of in-hospital patients who had negative results from multiple PCR and serological tests for SARS-CoV-2 before and after the date of serum collection, had S/CO values participants were exposed to SARS-CoV-2 and diagnosed with COVID-19 during January to March 2020. During their COVID-19 disease courses, they have received combinations of therapies including antivirals, immunomodulatory agents, antibiotics, supplemental oxygen, and ICU outcomes of this study were immunity against SARS-CoV-2 and functional recovery of the lung and other involved organs. Immunity against SARS-CoV-2 was assessed by multiple antibody assays. The colloidal gold-based test kit gave positive, weak positive, and negative readout of anti-SARS-CoV-2 IgM and IgG separately. The quantitative chemiluminescence microparticle immunoassay for antibodies against SARS-CoV-2 RBD was performed according to manufacturer’s protocol and previous publication,24 and the results were deemed positive if the signal/cutoff S/CO ratio ≥1. For ELISA tests, results were recorded and analyzed as continuous variables and the limit of sensitivity was calculated as mean + 2 × SD of 20 serum samples negative for SARS-CoV-2 antibodies in chemiluminescence assays. Functional recovery of the lung was assessed based on 1 current CT images comparing to images taken before discharge and during earlier follow-ups, 2 pulmonary function test results, and 3 six-minute walk test results. Recovery of the heart was assessed based on ECG, echocardiogram, and cardiac MRI scans. Recovery of other potentially involved organs were assessed by laboratory tests Roche Diagnostics.Sample sizeAn initial target sample size of 108 was determined based on the assumption of a 15 ratio of severe and non-severe COVID-19 patient enrollment and α = This sample size was calculated to have 90% power to detect a 10% difference of antibody concentrations. The final sample size exceeded the target in both analysisQuantitative data were presented in violin plots with all data points shown. Patient characteristics and clinical data were summarized as incidence with prevalence or median with IQR and were assessed with Fisher’s exact test dichotomous variables or χ2 test variables with more than two categories for categorical variables and Mann–Whitney U test for continuous variables. Antibody concentrations were log-transformed before being analyzed as continuous variables. The difference of antibody concentrations between groups were assessed by the Mann–Whitney U test two groups or Kruskal–Wallis test with post hoc comparisons more than two groups. Special tests were mentioned in figure legends. Correlation was assessed by Spearman’s ρ test. Linearity between two factors was assessed by simple linear regression. Generalized linear models were used to assess factors associated with antibody titers. Analyses were performed using SPSS 26 IBM or Prism 9 GraphPad. Missing data were excluded pairwise from analyses. 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This work was supported by Xiangyang Science and Technology Bureau 2020YL10, 2020YL14, 2020YL17, and 2020YL39, National Natural Science Foundation of China 31501116, Shenzhen Science and Technology Innovation Commission JCYJ20190809100005672, Shenzhen Sanming Project of Medicine SZSM201911013, and US Department of Veterans Affairs 5I01BX001353.Author informationAuthor notesThese authors contributed equally Yan Zhan, Yufang Zhu, Shanshan Wang, Shijun Jia, Yunling Gao, Yingying LuAuthors and AffiliationsDepartment of Rehabilitation Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, ChinaYan Zhan, Shanshan Wang, Peng Du, Hao Yu, Chang Liu & Peijun LiuDepartment of Laboratory Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, ChinaYufang Zhu, Caili Zhou & Ran LiangDepartment of Radiology and Medical Imaging, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, ChinaShijun Jia & Feng WuDepartment of Research Affairs, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, ChinaYunling Gao & Jin ChengDepartment of Nephrology, Center of Nephrology and Urology, Sun Yat-sen University Seventh Hospital, Shenzhen, Guangdong, 518107, ChinaYingying Lu, Zhihua Zheng & Peng HongDepartment of Biomedical Science, Shenzhen Research Institute, City University of Hong Kong, Kowloon Tong, Hong Kong, ChinaYingying LuDepartment of Rehabilitation Medicine, Xiangzhou District People’s Hospital, Xiangyang, Hubei, 441000, ChinaDingwen SunDepartment of Rehabilitation Medicine, Gucheng People’s Hospital, Affiliated Gucheng Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441700, ChinaXiaobo WangDivision of Quality Control, Xiangyang Central Blood Station, Xiangyang, Hubei, 441000, ChinaZhibing HouDepartment of Respiratory and Critical Care Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, ChinaQiaoqiao Hu & Yulan ZhengDepartment of Pathology, Mount Sinai St. Luke’s Roosevelt Hospital Center, New York, NY, 10025, USAMiao CuiDepartment of Oncology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, 518036, ChinaGangling TongDepartment of Dermatology, Sun Yat-sen University Seventh Hospital, Shenzhen, Guangdong, 518107, ChinaYunsheng Xu & Linyu ZhuDivision of Research and Development, US Department of Veterans Affairs New York Harbor Healthcare System, Brooklyn, NY, 11209, USAPeng HongDepartment of Cell Biology, State University of New York Downstate Health Sciences University, Brooklyn, NY, 11203, USAPeng HongAuthorsYan ZhanYou can also search for this author in PubMed Google ScholarYufang ZhuYou can also search for this author in PubMed Google ScholarShanshan WangYou can also search for this author in PubMed Google ScholarShijun JiaYou can also search for this author in PubMed Google ScholarYunling GaoYou can also search for this author in PubMed Google ScholarYingying LuYou can also search for this author in PubMed Google ScholarCaili ZhouYou can also search for this author in PubMed Google ScholarRan LiangYou can also search for this author in PubMed Google ScholarDingwen SunYou can also search for this author in PubMed Google ScholarXiaobo WangYou can also search for this author in PubMed Google ScholarZhibing HouYou can also search for this author in PubMed Google ScholarQiaoqiao HuYou can also search for this author in PubMed Google ScholarPeng DuYou can also search for this author in PubMed Google ScholarHao YuYou can also search for this author in PubMed Google ScholarChang LiuYou can also search for this author in PubMed Google ScholarMiao CuiYou can also search for this author in PubMed Google ScholarGangling TongYou can also search for this author in PubMed Google ScholarZhihua ZhengYou can also search for this author in PubMed Google ScholarYunsheng XuYou can also search for this author in PubMed Google ScholarLinyu ZhuYou can also search for this author in PubMed Google ScholarJin ChengYou can also search for this author in PubMed Google ScholarFeng WuYou can also search for this author in PubMed Google ScholarYulan ZhengYou can also search for this author in PubMed Google ScholarPeijun LiuYou can also search for this author in PubMed Google ScholarPeng HongYou can also search for this author in PubMed Google ScholarContributionsY. Zhan and conceptualized the study; Y. Zhan, and recruited patients, performed physical examinations, and abstracted historic data; Y. Zhu, and performed laboratory tests and interpreted results; and conducted sonographic and radiological examinations and interpreted results; and Y. Zheng conducted PFT and interpreted results; Y. Zhan, and conducted functional tests, assessed rehabilitation status and interpreted data; and interpreted metabolic and immunological findings; Y. Zhan, and conducted data quality checks and performed statistical analyses; Y. Zhan and wrote the manuscript. All authors read and approved the final authorsCorrespondence to Feng Wu, Yulan Zheng, Peijun Liu or Peng declarations Competing interests The authors declare no competing interests. Supplementary informationRights and permissions Open Access This article is licensed under a Creative Commons Attribution International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Reprints and PermissionsAbout this articleCite this articleZhan, Y., Zhu, Y., Wang, S. et al. SARS-CoV-2 immunity and functional recovery of COVID-19 patients 1-year after infection. Sig Transduct Target Ther 6, 368 2021. citationReceived 06 March 2021Revised 16 September 2021Accepted 20 September 2021Published 13 October 2021DOI Evaluation of Three Quantitative Anti-SARS-CoV-2 Antibody Immunoassays Sabine Chapuy-Regaud et al. Microbiol Spectr. 2021. Free PMC article Abstract The severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 emerged in December 2019 and caused a dramatic pandemic. Serological assays are used to check for immunization and assess herd immunity. We evaluated commercially available assays designed to quantify antibodies directed to the SARS-CoV-2 Spike S antigen, either total Wantaï SARS-CoV-2 Ab ELISA or IgG SARS-CoV-2 IgG II Quant on Alinity, Abbott, and Liaison SARS-CoV-2 TrimericS IgG, Diasorin. The specificities of the Wantaï, Alinity, and Liaison assays were evaluated using 100 prepandemic sera and were 98, 99, and 97%, respectively. The sensitivities of all three were around 100% when tested on 35 samples taken 15 to 35 days postinfection. They were less sensitive for 150 sera from late infections >180 days. Using the first WHO international standard NIBSC, we showed that the Wantai results were concordant with the NIBSC values, while Liaison and Alinity showed a proportional bias of and 7, respectively. The results of the 3 immunoassays were significantly globally pairwise correlated and for late infection sera P < They were correlated for recent infection sera measured with Alinity and Liaison P < However, the Wantai results of recent infections were not correlated with those from Alinity or Liaison. All the immunoassay results were significantly correlated with the neutralizing antibody titers obtained using a live virus neutralization assay with the SARS-CoV-2 strain. These assays will be useful once the protective anti-SARS-CoV-2 antibody titer has been determined. IMPORTANCE Standardization and correlation with virus neutralization assays are critical points to compare the performance of serological assays designed to quantify anti-SARS-CoV-2 antibodies in order to identify their optimal use. We have evaluated three serological immunoassays based on the virus spike antigen that detect anti-SARS-CoV-2 antibodies a microplate assay and two chemiluminescent assays performed with Alinity Abbott and Liaison Diasorin analysers. We used an in-house live virus neutralization assay and the first WHO international standard to assess the comparison. This study could be useful to determine guidelines on the use of serological results to manage vaccination and treatment with convalescent plasma or monoclonal antibodies. Keywords COVID; SARS-CoV-2; binding antibodies; immunoassay; neutralizing antibodies. Conflict of interest statement The authors declare no conflict of interest. Figures FIG 1 Distribution of the results. A Wantaï, B Liaison, and C Alinity assays according to patient groups. Black lines = median of each group. Red lines = manufacturer’s negative/positive threshold. Zero 0 values in the Liaison negative group n = 92, the Liaison late infection group n = 15, the Alinity negative group n = 14, and the Alinity late infection group n = 7 are not shown. FIG 2 ROC curves for Wantaï black line, Liaison green line and Alinity red line. Gray line y = x. The AUROCs were Wantaï 95% CI to Liaison 95% CI to and Alinity 95% CI to indicating their capacity to accurately detect anti-SARS-CoV-2 antibodies. FIG 3 Quantification of anti-SARS-CoV-2 antibodies relative to the NIBSC international standard. Serial dilutions of the NIBSC 20/136 standard were assayed with the A Wantaï, B Liaison, and C Alinity assay. Neutralizing antibodies NAb were also determined with a live method D. The black line represents the regression line and the dashed lines its 95% CI. The dashed red line represents the y = x line. AU arbitrary units. BAU binding antibody unit. The equations were y = x − slope 95% CI to y-intercept 95% CI − to for Wantaï; y = x − slope 95% CI to y-intercept 95% CI − to for Liaison; y = x - slope 95% CI to y-intercept 95% CI − to for Alinity and y = x + slope 95% CI to y-intercept 95% CI − to for NAb titers. FIG 4 Correlation between the immunoassay results. Pairwise distribution of the Wantaï, Liaison, and Alinity assays values for all positive results A to C, recent infections D to F, and late infections G to I. When the Spearman rank coefficient r indicated a significant correlation, the regression line was drawn. Dashed lines 95% CI limits. FIG 5 Immunoassays results and neutralizing antibody titers. Distribution of the Wantaï, Liaison, and Alinity assay values and the NAb titers for all positive results A to C The NAb titers were determined in a live virus neutralization assay using the B strain. Spearman’s rank coefficients r and their P value are indicated. The box extends from the 25th to 75th percentiles and whiskers from minimal to maximal values. Similar articles Performance evaluation of three automated quantitative immunoassays and their correlation with a surrogate virus neutralization test in coronavirus disease 19 patients and pre-pandemic controls. Jung K, Shin S, Nam M, Hong YJ, Roh EY, Park KU, Song EY. Jung K, et al. J Clin Lab Anal. 2021 Sep;359e23921. doi Epub 2021 Aug 8. J Clin Lab Anal. 2021. PMID 34369009 Free PMC article. Inference of SARS-CoV-2 spike-binding neutralizing antibody titers in sera from hospitalized COVID-19 patients by using commercial enzyme and chemiluminescent immunoassays. Valdivia A, Torres I, Latorre V, Francés-Gómez C, Albert E, Gozalbo-Rovira R, Alcaraz MJ, Buesa J, Rodríguez-Díaz J, Geller R, Navarro D. Valdivia A, et al. Eur J Clin Microbiol Infect Dis. 2021 Mar;403485-494. doi Epub 2021 Jan 6. Eur J Clin Microbiol Infect Dis. 2021. PMID 33404891 Free PMC article. 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J Clin Microbiol 58e00461-20. doi - DOI - PMC - PubMed Publication types MeSH terms Substances LinkOut - more resources Full Text Sources Atypon Europe PubMed Central PubMed Central Medical Genetic Alliance MedlinePlus Health Information Miscellaneous NCI CPTAC Assay Portal Estimates of SARS-CoV-2 Seroprevalence and Incidence of Primary SARS-CoV-2 Infections Among Blood Donors, by COVID-19 Vaccination Status — United States, April 2021–September 2022 Jefferson M. Jones, MD1; Irene Molina Manrique, MS2; Mars S. Stone, PhD3; Eduard Grebe, PhD3; Paula Saa, PhD4; Clara D. Germanio, PhD3; Bryan R. Spencer, PhD4; Edward Notari, MPH4; Marjorie Bravo, MD3; Marion C. Lanteri, PhD5; Valerie Green, MS5; Melissa Briggs-Hagen, MD1; Melissa M. Coughlin, PhD1; Susan L. Stramer, PhD4; Jean Opsomer, PhD2; Michael P. Busch, MD, PhD3 View author affiliations View suggested citationSummary What is already known about this topic? SARS-CoV-2 hybrid immunity immunity derived from both previous infection and vaccination has been reported to provide better protection than that from infection or vaccination alone. What is added by this report? By the third quarter of 2022, an estimated of persons aged ≥16 years in a longitudinal blood donor cohort had SARS-CoV-2 antibodies from previous infection or vaccination, including from infection alone and from vaccination alone; had hybrid immunity. Hybrid immunity prevalence was lowest among adults aged ≥65 years. What are the implications for public health practice? Low prevalence of infection-induced and hybrid immunity among older adults, who are at increased risk for severe disease if infected, reflects the success of public health infection prevention efforts while also highlighting the importance of this group staying up to date with recommended COVID-19 vaccination, including at least 1 bivalent dose. Altmetric Citations Views Views equals page views plus PDF downloads Changes in testing behaviors and reporting requirements have hampered the ability to estimate the SARS-CoV-2 incidence 1. Hybrid immunity immunity derived from both previous infection and vaccination has been reported to provide better protection than that from infection or vaccination alone 2. To estimate the incidence of infection and the prevalence of infection- or vaccination-induced antibodies or both, data from a nationwide, longitudinal cohort of blood donors were analyzed. During the second quarter of 2021 April–June, an estimated of persons aged ≥16 years had infection- or vaccination-induced SARS-CoV-2 antibodies, including from vaccination alone, from infection alone, and from both. By the third quarter of 2022 July–September, had SARS-CoV-2 antibodies from previous infection or vaccination, including from infection alone and from vaccination alone; had hybrid immunity. Prevalence of hybrid immunity was lowest among persons aged ≥65 years the group with the highest risk for severe disease if infected, and was highest among those aged 16–29 years Low prevalence of infection-induced and hybrid immunity among older adults reflects the success of public health infection prevention efforts while also highlighting the importance of older adults staying up to date with recommended COVID-19 vaccination, including at least 1 bivalent dose.*,† Since July 2020, SARS-CoV-2 seroprevalence in the United States has been estimated by testing blood donations 3. CDC, in collaboration with Vitalant, American Red Cross, Creative Testing Solutions, and Westat, established a nationwide cohort of 142,758 blood donors in July 2021; the cohort included persons who had donated blood two or more times in the preceding year.§ All blood donations collected during April–June 2021 were tested for antibodies against the spike S and nucleocapsid N proteins. Beginning in 2022, up to one blood donation sample per donor was randomly selected each quarter and tested using the Ortho VITROS SARS-CoV-2 Quantitative S immunoglobulin G¶ and total N antibody** tests. Both SARS-CoV-2 infection and COVID-19 vaccination result in production of anti-S antibodies, whereas anti-N antibodies only result from infection. At each donation, blood donors were asked if they had received a COVID-19 vaccine. Using vaccination history and results of antibody testing, the prevalence of the population aged ≥16 years with vaccine-induced, infection-induced, or hybrid immunity was estimated for four 3-month periods April–June 2021, January–March 2022, April–June 2022, and July–September 2022; in addition, the proportion of persons who transitioned from one immune status to another by quarter was estimated. Analysis was limited to 72,748 donors for whom it was possible to ascertain immune status during each period using their prior classification previously infected or vaccinated, antibody testing results, and their vaccination status at the time of each donation.†† The sample data were weighted to account for selection into the study cohort, for nonresponse during the four analysis periods, and for demographic differences between the blood donor population and the overall population. The weights were obtained through a combination of stratification and raking, an iterative weighting adjustment procedure 4. Rates of infection among those previously uninfected were estimated for each period by determining the percentage of anti-N–negative persons seroconverting to anti-N–positive from one 3-month period included in the study to the next. Estimates were stratified by age group 16–29, 30–49, 50–64, and ≥65 years and race and ethnicity§§ Asian, Black or African American [Black], White, Hispanic or Latino [Hispanic], and other. SAS version SAS Institute was used to compute the final weights, and R version R Foundation was used to calculate all the estimates and create the plots.¶¶ Seroprevalence and infection rates were estimated as weighted means and compared by demographic group and vaccination status using two-sided t-tests with a significance level of α = This activity was reviewed by CDC and conducted consistent with applicable federal law and CDC policy.*** During the first quarter examined April–June 2021, an estimated 95% CI = of persons aged ≥16 years had SARS-CoV-2 antibodies from previous infection or vaccination, including 95% CI = from vaccination alone, 95% CI = from infection alone, and 95% CI = from both Figure 1 Supplementary Figure 1, During January–March 2022, 95% CI = of persons aged ≥16 years had antibodies from previous infection or vaccination, including 95% CI = from vaccination alone, 95% CI = from infection alone, and 95% CI = from both. During July–September 2022, 95% CI = of persons had antibodies from previous infection or vaccination, including 95% CI = with vaccine-induced immunity alone, 95% CI = with infection-induced immunity alone, and 95% CI = with hybrid immunity. During July–September 2022, the prevalence of infection-induced immunity was 95% CI = among unvaccinated persons and 95% CI = among vaccinated persons. During July–September 2022, the lowest prevalence of hybrid immunity, 95% CI = was observed in persons aged ≥65 years, and the highest, 95% CI = in adolescents and young adults aged 16–29 years Figure 2 Supplementary Figure 2, During all periods, higher prevalences of hybrid immunity were observed among Black and Hispanic populations than among White and Asian populations Supplementary Figure 3, Among persons with no previous infection, the incidence of first infections during the study period conversion from anti-N–negative to anti-N–positive was higher among unvaccinated persons Table. From April–June 2021 through January–March 2022, the incidence of first SARS-CoV-2 infections among unvaccinated persons was compared with among vaccinated persons p< From January–March 2022 through April–June 2022, the incidence among unvaccinated persons was and was among vaccinated persons. Between April–June 2022 and July–September 2022, the incidence among unvaccinated persons was compared with among vaccinated persons p< Incidence of first SARS-CoV-2 infections was higher among younger than among older persons and was lower among Asian persons than among other racial and ethnic populations, but the differences among groups narrowed over time. Discussion Both infection-induced and hybrid immunity increased during the study period. By the third quarter of 2022, approximately two thirds of persons aged ≥16 years had been infected with SARS-CoV-2 and one half of all persons had hybrid immunity. Compared with vaccine effectiveness against any infection and against severe disease or hospitalization, the effectiveness of hybrid immunity against these outcomes has been shown to be higher and wane more slowly 2. This increase in seroprevalence, including hybrid immunity, is likely contributing to lower rates of severe disease and death from COVID-19 in 2022–2023 than during the early pandemic.††† The prevalence of hybrid immunity is lowest in adults aged ≥65 years, likely due to higher vaccination coverage and earlier availability of COVID-19 vaccines for this age group, as well as to higher prevalences of behavioral practices to avoid infection 5. However, lower prevalences of infection-induced and hybrid immunity could further increase the risk for severe disease in this group, highlighting the importance for adults aged ≥65 years to stay up to date with COVID-19 vaccination and have easy access to antiviral medications. COVID-19 vaccine efficacy studies have reported reduced effectiveness against SARS-CoV-2 infection during the Omicron-predominant period compared with earlier periods and have shown that protection against infection wanes more rapidly than does protection against severe disease 6,7. In this study, unvaccinated persons had higher rates of infection as evidenced by N antibody seroconversion than did vaccinated persons, indicating that vaccination provides some protection against infection. The differences in incidence could also be due to systematic differences between vaccinated and unvaccinated persons in terms of the prevalence of practicing prevention behaviors such as masking and physical distancing. The relative difference in infection rates narrowed during the most recent months, possibly because of waning of vaccine-induced protection against infection in the setting of increased time after vaccination or immune evasion by the SARS-CoV-2 Omicron variant. The narrowing of difference in infection rates might also be attributable to increasing similarities in behavior among vaccinated and unvaccinated persons during late 2022 8. The findings in this report are subject to at least six limitations. First, although COVID-19 booster vaccine doses and reinfections can strengthen immunity 9,10, this analysis did not account for these effects because blood donor vaccination history did not include the number of doses received, and data on reinfections were not captured. Second, immunity wanes over time, but time since vaccination or infection was not included in the analysis 2. Third, vaccination status was self-reported, potentially leading to misclassification. Fourth, although the results were adjusted based on differences in blood donor and general population demographics, estimates from blood donors might not be representative of the general population; thus, these results might not be generalizable. Fifth, vaccinated and unvaccinated persons might differ in other ways not captured by this analysis 8, nor can causality be inferred from the results on relative infection incidence. Finally, if both vaccination and infection occurred between blood donations included in the study, the order of occurrence could not be determined, and some unvaccinated donors might have been vaccinated before infection and thus misclassified; in 2022, this was uncommon and occurred in < of donors during any 3-month period. This report found that the incidence of first-time SARS-CoV-2 infection was lower among persons who had received COVID-19 vaccine than among unvaccinated persons and that infection-induced and hybrid immunity have increased but remain lowest in adults aged ≥65 years. These adults have consistently had a higher risk for severe disease compared with younger age groups, underscoring the importance of older adults staying up to date with recommended COVID-19 vaccination, including at least 1 bivalent dose. Acknowledgments Brad Biggerstaff, Matthew McCullough, CDC; Roberta Bruhn, Brian Custer, Xu Deng, Zhanna Kaidarova, Kathleen Kelly, Anh Nguyen, Graham Simmons, Hasan Sulaeman, Elaine Yu, Karla Zurita-Gutierrez, Vitalant Research Institute; Akintunde Akinseye, Jewel Bernard-Hunte, Robyn Ferg, Rebecca Fink, Caitlyn Floyd, Isaac Lartey, Sunitha Mathews, David Wright, Westat; Jamel Groves, James Haynes, David Krysztof, American Red Cross; Ralph Vassallo, Vitalant; Sherri Cyrus, Phillip Williamson, Creative Testing Solutions; Paul Contestable, QuidelOrtho; Steve Kleinman, University of British Columbia; CDC, Vitalant Research Institute, Westat, American Red Cross, and Creative Testing Solutions staff members; blood donors whose samples were analyzed and who responded to surveys for this study. Corresponding author Jefferson M. Jones, ioe8 Center for Immunization and Respiratory Diseases, CDC; 2Westat, Rockville, Maryland; 3Vitalant Research Institute, San Francisco, California; 4American Red Cross, Washington, DC; 5Creative Testing Solutions, Tempe, authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed. * † § Blood donors who donated at least twice during the year before July 2021 were included in the cohort, because they might represent persons who were more likely to donate frequently. Among donors who donated more than once during a quarter, one sample was selected at random for testing. ¶ ** †† §§ Persons of Hispanic origin might be of any race but are categorized as Hispanic; all racial groups are non-Hispanic. ¶¶ Jackknife replication was used to compute replicate weights. Weights were adjusted for nonresponse using adjustment cells created by age category, vaccination and previous infection status, and blood collection organization Vitalant or American Red Cross. Raking was used to further adjust the weights to account for demographic differences between the blood donor population and population. The demographic variables used for raking were sex female and male, age group 16–24, 25–34, 35–44, 45–54, 55–64, and ≥65 years, and race and ethnicity Asian, Black, White, Hispanic, and other. *** 45 part 46, 21 part 56; 42 Sect. 241d; 5 Sect. 552a; 44 Sect. 3501 et seq. ††† Accessed May 25, 2023. References Rader B, Gertz A, Iuliano AD, et al. Use of at-home COVID-19 tests—United States, August 23, 2021–March 12, 2022. MMWR Morb Mortal Wkly Rep 2022;71489–94. PMID35358168 Bobrovitz N, Ware H, Ma X, et al. Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the Omicron variant and severe disease a systematic review and meta-regression. Lancet Infect Dis 2023;23556–67. PMID36681084 Jones JM, Stone M, Sulaeman H, et al. Estimated US infection- and vaccine-induced SARS-CoV-2 seroprevalence based on blood donations, July 2020–May 2021. JAMA 2021;3261400–9. PMID34473201 Deville J-C, Särndal C-E, Sautory O. Generalized raking procedures in survey sampling. J Am Stat Assoc 1993;881013–20. Steele MK, Couture A, Reed C, et al. Estimated number of COVID-19 infections, hospitalizations, and deaths prevented among vaccinated persons in the US, December 2020 to September 2021. JAMA Netw Open 2022;5e2220385. PMID35793085 Higdon MM, Wahl B, Jones CB, et al. A systematic review of coronavirus disease 2019 vaccine efficacy and effectiveness against severe acute respiratory syndrome coronavirus 2 infection and disease. Open Forum Infect Dis 2022;9ofac138. PMID35611346 Feikin DR, Higdon MM, Abu-Raddad LJ, et al. Duration of effectiveness of vaccines against SARS-CoV-2 infection and COVID-19 disease results of a systematic review and meta-regression. Lancet 2022;399924–44. PMID35202601 Thorpe A, Fagerlin A, Drews FA, Shoemaker H, Scherer LD. Self-reported health behaviors and risk perceptions following the COVID-19 vaccination rollout in the USA an online survey study. Public Health 2022;20868–71. PMID35717747 Sette A, Crotty S. Immunological memory to SARS-CoV-2 infection and COVID-19 vaccines. Immunol Rev 2022;31027–46. PMID35733376 Atti A, Insalata F, Carr EJ, et al.; SIREN Study Group and the Crick COVID Immunity Pipeline Consortium. Antibody correlates of protection from SARS-CoV-2 reinfection prior to vaccination a nested case-control within the SIREN study. J Infect 2022;85545–56. PMID36089104 FIGURE 1. Prevalences of vaccine-induced, infection-induced, and hybrid* immunity† against SARS-CoV-2 among blood donors aged ≥16 years — United States, April 2021–September 2022 * Immunity derived from a combination of vaccination and infection. † Ascertained by the presence of anti-spike antibodies present in both COVID-19–vaccinated and SARS-CoV-2–infected persons and anti-nucleocapsid antibodies present only in previously infected persons and self-reported history of vaccination. FIGURE 2. Prevalences of vaccine-induced, infection-induced, and hybrid* immunity† against SARS-CoV-2 among blood donors aged ≥16 years, by age group — United States, April 2021–September 2022 * Immunity derived from a combination of vaccination and infection. † Ascertained by the presence of anti-spike antibodies present in both COVID-19–vaccinated and SARS-CoV-2–infected persons and anti-nucleocapsid antibodies present only in previously infected persons and self-reported history of vaccination. TABLE. Estimated percentage* of persons infected with SARS-CoV-2 for the first time among blood donors, by analysis quarter, sociodemographic characteristics, and vaccination status — United States, April 2021–September 2022 Characteristic Period, % 95% CI Apr–Jun 2021 to Jan–Mar 2022 Jan–Mar 2022 to Apr–Jun 2022 Apr–Jun 2022 to Jul–Sep 2022 Overall Total Unvaccinated Vaccinated Age group, yrs 16–29 Total Unvaccinated Vaccinated 30–49 Total Unvaccinated Vaccinated 50–64 Total Unvaccinated Vaccinated ≥65 Total Unvaccinated Vaccinated Race and ethnicity§ Asian Total Unvaccinated Vaccinated Black or African American Total Unvaccinated Vaccinated White Total Unvaccinated Vaccinated Hispanic or Latino Total Unvaccinated Vaccinated Other and multiple races¶ Total Unvaccinated Vaccinated * Percentage of uninfected persons anti-nucleocapsid–negative in the previous 3-month period seroconverting to anti-nucleocapsid–positive. If both vaccination and infection occurred between donations included in the study, the order could not be determined, and some unvaccinated donors might have been vaccinated before infection and thus misclassified. † If donors who transitioned from no antibodies to hybrid immunity between April–June 2021 and January–March 2022 were excluded, an estimated 95% CI = of unvaccinated donors were infected. For other periods, exclusion did not substantially change results. Between January–March and April–June 2022, of persons shifted from no antibodies to hybrid immunity. Between April–June and July–September 2022, of persons shifted from no antibodies to hybrid immunity. § Persons of Hispanic or Latino Hispanic origin might be of any race but are categorized as Hispanic; all racial groups are non-Hispanic. ¶ Includes American Indian or Alaska Native and non-Hispanic persons of other races. Suggested citation for this article Jones JM, Manrique IM, Stone MS, et al. Estimates of SARS-CoV-2 Seroprevalence and Incidence of Primary SARS-CoV-2 Infections Among Blood Donors, by COVID-19 Vaccination Status — United States, April 2021–September 2022. MMWR Morb Mortal Wkly Rep 2023;72601–605. DOI MMWR and Morbidity and Mortality Weekly Report are service marks of the Department of Health and Human Services. Use of trade names and commercial sources is for identification only and does not imply endorsement by the Department of Health and Human Services. References to non-CDC sites on the Internet are provided as a service to MMWR readers and do not constitute or imply endorsement of these organizations or their programs by CDC or the Department of Health and Human Services. CDC is not responsible for the content of pages found at these sites. URL addresses listed in MMWR were current as of the date of publication. All HTML versions of MMWR articles are generated from final proofs through an automated process. This conversion might result in character translation or format errors in the HTML version. Users are referred to the electronic PDF version and/or the original MMWR paper copy for printable versions of official text, figures, and tables. Questions or messages regarding errors in formatting should be addressed to mmwrq

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