{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T19:25:06Z","timestamp":1790364306265,"version":"4.1.0"},"reference-count":41,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Vox Sanguinis"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background and Objectives<\/jats:title><jats:p>Confirmed COVID\u201019 diagnoses underestimate the total number of infections. Blood donors can provide representative seroprevalence estimates, which can be leveraged into reasonable estimates of total infection counts and infection fatality rate (IFR).<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>Blood donors who donated after each of three epidemic waves (Beta, Delta and first Omicron waves) were tested for anti\u2010SARS\u2010CoV\u20102 nucleocapsid antibodies using the Roche Elecsys anti\u2010SARS\u2010CoV\u20102 total immunoglobulin assay. Roche Elecsys anti\u2010spike antibody testing was done for the post\u2010Omicron sampling. Prevalence of antibodies was estimated by age, sex, race and province and compared to official case reporting. Province and age group\u2010specific IFRs were estimated using external excess mortality estimates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The nationally weighted anti\u2010nucleocapsid seroprevalence estimates after the Beta, Delta and Omicron waves were 47% (46.2%\u201348.6%), 71% (68.8%\u201373.5%) and 87% (85.5%\u201388.4%), respectively. There was no variation by age and sex, but there were statistically and epidemiologically significant differences by province (except at the latest time point) and race. There was a 13\u2010fold higher seroprevalence than confirmed case counts at the first time point. Age\u2010dependent IFR roughly doubled for every 10\u2009years of age increase over 6 decades from 0.014% in children to 6.793% in octogenarians.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Discrepancies were found between seroprevalence and confirmed case counts. High seroprevalence rates found among Black African donors can be ascribed to historical inequities. Our IFR estimates were useful in refining previous large disagreements about the severity of the epidemic in South Africa. Blood donor\u2010based serosurveys provided a valuable and efficient way to provide near real\u2010time monitoring of the ongoing SARS\u2010CoV\u20102 outbreak.<\/jats:p><\/jats:sec>","DOI":"10.1111\/vox.13571","type":"journal-article","created":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T05:24:16Z","timestamp":1703827456000},"page":"242-251","source":"Crossref","is-referenced-by-count":5,"title":["The evolution and interpretation of seroprevalence of <scp>SARS\u2010CoV<\/scp>\u20102 antibodies among <scp>South African<\/scp> blood donors from the <scp>Beta<\/scp> to <scp>Omicron<\/scp> variant\u2010driven waves"],"prefix":"10.1111","volume":"119","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4383-4526","authenticated-orcid":false,"given":"Marion","family":"Vermeulen","sequence":"first","affiliation":[{"name":"South African National Blood Service  Johannesburg South Africa"},{"name":"University of the Free State  Bloemfontein South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurette","family":"Mhlanga","sequence":"additional","affiliation":[{"name":"DSI\u2010NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA) Stellenbosch University  Stellenbosch South Africa"},{"name":"Northwestern University  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wendy","family":"Sykes","sequence":"additional","affiliation":[{"name":"South African National Blood Service  Johannesburg South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Russell","family":"Cable","sequence":"additional","affiliation":[{"name":"Western Cape Blood Service  Cape Town South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charl","family":"Coleman","sequence":"additional","affiliation":[{"name":"South African National Blood Service  Johannesburg South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nadia","family":"Pietersen","sequence":"additional","affiliation":[{"name":"Western Cape Blood Service  Cape Town South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronel","family":"Swanevelder","sequence":"additional","affiliation":[{"name":"South African National Blood Service  Johannesburg South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5458-5791","authenticated-orcid":false,"given":"Tanya Nadia","family":"Glatt","sequence":"additional","affiliation":[{"name":"South African National Blood Service  Johannesburg South Africa"},{"name":"University of Johannesburg  Johannesburg South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeremy","family":"Bingham","sequence":"additional","affiliation":[{"name":"DSI\u2010NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA) Stellenbosch University  Stellenbosch South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9805-8013","authenticated-orcid":false,"given":"Karin","family":"van den Berg","sequence":"additional","affiliation":[{"name":"South African National Blood Service  Johannesburg South Africa"},{"name":"University of the Free State  Bloemfontein South Africa"},{"name":"University of Cape Town  Rondebosch South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eduard","family":"Grebe","sequence":"additional","affiliation":[{"name":"DSI\u2010NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA) Stellenbosch University  Stellenbosch South Africa"},{"name":"Vitalant Research Institute  San Francisco California USA"},{"name":"University of California San Francisco  San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Welte","sequence":"additional","affiliation":[{"name":"DSI\u2010NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA) Stellenbosch University  Stellenbosch South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"Department of Health SA.Department of Health COVID\u201019 Online Resource and News Portal. 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