1
|
Tang J, Liu H, Wang Q, Gu X, Wang J, Li W, Luo Y, Li Y, Deng L, Luo Y, Du X, Tan D, Fu X, Chen X. Predictors of high SARS-CoV-2 immunoglobulin G titers in COVID-19 convalescent whole-blood donors: a cross-sectional study in China. Front Immunol 2023; 14:1191479. [PMID: 37388736 PMCID: PMC10303911 DOI: 10.3389/fimmu.2023.1191479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 06/02/2023] [Indexed: 07/01/2023] Open
Abstract
Background Demographic information has been shown to help predict high antibody titers of COVID-19 convalescent plasma (CCP) in CCP donors. However, there is no research on the Chinese population and little evidence on whole-blood donors. Therefore, we aimed to investigate these associations among Chinese blood donors after SARS-CoV-2 infection. Methods In this cross-sectional study, 5,064 qualified blood donors with confirmed or suspected SARS-CoV-2 infection completed a self-reported questionnaire and underwent tests of SARS-CoV-2 Immunoglobulin G (IgG) antibody and ABO blood type. Logistic regression models were used to calculate odds ratios (ORs) for high SARS-CoV-2 IgG titers according to each factor. Results Totally, 1,799 participants (with SARS-CoV-2 IgG titers≥1:160) had high-titer CCPs. Multivariable analysis showed that a 10-year increment in age and earlier donation were associated with higher odds of high-titer CCP, while medical personnel was associated with lower odds. The ORs (95% CIs) of high-titer CCP were 1.17 (1.10-1.23, p< 0.001) and 1.41 (1.25-1.58, p< 0.001) for each 10-year increment in age and earlier donation, respectively. The OR of high-titer CCP was 0.75 (0.60-0.95, p = 0.02) for medical personnel. Female early donors were associated with increased odds of high-titer CCP, but this association was insignificant for later donors. Donating after 8 weeks from the onset was associated with decreased odds of having high-titer CCP compared to donating within 8 weeks from the onset, and the HR was 0.38 (95% CI: 0.22-0.64, p <0.001). There was no significant association between ABO blood type or race and the odds of high-titer CCP. Discussion Older age, earlier donation, female early donors, and non-medical-related occupations are promising predictors of high-titer CCP in Chinese blood donors. Our findings highlight the importance of CCP screening at the early stage of the pandemic.
Collapse
Affiliation(s)
- Jingyun Tang
- Blood Research Laboratory, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Humin Liu
- Department of Blood Testing, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Qing Wang
- Department of Blood Collection, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Xiaobo Gu
- Department of Blood Collection, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Jia Wang
- Department of Blood Collection, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Wenjun Li
- Department of Blood Testing, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Yinglan Luo
- Department of Blood Testing, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Yan Li
- Department of Blood Collection, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Lan Deng
- Department of Blood Collection, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Yue Luo
- Blood Research Laboratory, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Xinman Du
- Blood Research Laboratory, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Donglin Tan
- Department of Blood Processing, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Xuemei Fu
- Blood Research Laboratory, Chengdu Blood Center, Chengdu, Sichuan, China
| | - Xue Chen
- Blood Research Laboratory, Chengdu Blood Center, Chengdu, Sichuan, China
| |
Collapse
|
2
|
Moyo-Gwete T, Moore PL. Leveraging on past investment in understanding the immunology of COVID-19 – the South African experience. S AFR J SCI 2022. [DOI: 10.17159/sajs.2022/13171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Thandeka Moyo-Gwete
- National Institute for Communicable Diseases (NICD), National Health Laboratory Service (NHLS), Johannesburg, South Africa
- SAMRC Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Penny L. Moore
- National Institute for Communicable Diseases (NICD), National Health Laboratory Service (NHLS), Johannesburg, South Africa
- SAMRC Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| |
Collapse
|
3
|
Bingham J, Cable R, Coleman C, Glatt TN, Grebe E, Mhlanga L, Nyano C, Pieterson N, Swanevelder R, Swarts A, Sykes W, van den Berg K, Vermeulen M, Welte A. Estimates of prevalence of anti-SARS-CoV-2 antibodies among blood donors in South Africa in March 2022. RESEARCH SQUARE 2022:rs.3.rs-1687679. [PMID: 35665020 PMCID: PMC9164518 DOI: 10.21203/rs.3.rs-1687679/v1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
In line with previous instalments of analysis from this ongoing study to monitor 'Covid Seroprevalence' among blood donors in South Africa, we report on an analysis of 3395 samples obtained in mid-March 2022 from all provinces of South Africa - a timepoint just after the fourth (primarily omicron) wave of infections. As in our previous analyses, we see no evidence of age and sex dependence of prevalence, but significant variation by race. Differences between provinces have largely disappeared, as prevalence appears to have saturated. In contrast to previous estimates from this study, which reported only prevalence of anti-nucleocapsid antibodies, this present work also reports results from testing for anti-spike antibodies. This addition allows us to categorise those donors whose only antibodies are from vaccination. Our race-weighted national extrapolation is that 98% of South Africans have some antibodies, noting that 10% have anti-spike antibodies but not anti-nucleocapsid antibodies - a reasonable proxy for having both 1) been vaccinated and 2) avoided infection.
Collapse
Affiliation(s)
- Jeremy Bingham
- South African DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University
| | | | | | | | | | | | | | | | | | | | | | | | | | - Alex Welte
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis
| |
Collapse
|
4
|
Bingham J, Cable R, Coleman C, Glatt TN, Grebe E, Mhlanga L, Nyano C, Pieterson N, Swanevelder R, Swarts A, Sykes W, van den Berg K, Vermeulen M, Welte A. Estimates of prevalence of anti-SARS-CoV-2 antibodies among blood donors in South Africa in March 2022. RESEARCH SQUARE 2022:rs.3.rs-1687679. [PMID: 36575763 PMCID: PMC9793839 DOI: 10.21203/rs.3.rs-1687679/v2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
In line with previous instalments of analysis from this ongoing study to monitor 'Covid Seroprevalence' among blood donors in South Africa, we report on an analysis of 3395 samples obtained in mid-March 2022 from all provinces of South Africa - a timepoint just after the fourth (primarily omicron) wave of infections. As in our previous analyses, we see no evidence of age and sex dependence of prevalence, but significant variation by race. Differences between provinces have largely disappeared, as prevalence appears to have saturated. In contrast to previous estimates from this study, which reported only prevalence of anti-nucleocapsid antibodies, this present work also reports results from testing for anti-spike antibodies. This addition allows us to categorise those donors whose only antibodies are from vaccination. Our race-weighted national extrapolation is that 98% of South Africans have some antibodies, noting that 10% have anti-spike antibodies but not anti-nucleocapsid antibodies - a reasonable proxy for having both 1) been vaccinated and 2) avoided infection.
Collapse
Affiliation(s)
- Jeremy Bingham
- South African DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University
| | | | | | | | | | | | | | | | | | | | | | | | | | - Alex Welte
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis
| |
Collapse
|
5
|
Cable R, Coleman C, Glatt T, Grebe E, Mhlanga L, Nyoni C, Pieterson N, Swanevelder R, Swarts A, Sykes W, van den Berg K, Vermeulen M, Welte A. Estimates of prevalence of anti-SARS-CoV-2 antibodies among blood donors in eight provinces of South Africa in November 2021. RESEARCH SQUARE 2022:rs.3.rs-1359658. [PMID: 35194594 PMCID: PMC8863147 DOI: 10.21203/rs.3.rs-1359658/v1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In line with previous instalments of analysis from this ongoing study to monitor 'Covid Seroprevalence' among blood donors in South Africa, we report on analysis of 3395 samples obtained from 8 to 12 November 2021 in all provinces of South Africa except the Western Cape. As in our previous analyses, we see no evidence of age and sex dependence of prevalence, but substantial variation by province, and by race within each province, from which we generated provincial total point estimates (EC-74%; FS-75%; GP-68%; ZN-73%; LP-66; MP-73%; NC-63%; NW-81% ) and a 'South Africa minus Western Cape' national prevalence estimate of 71% (95%CI 69-74%). We note that sample collection occurred just before the omicron variant driven wave in South Africa, but otherwise present these results without significant interpretation.
Collapse
Affiliation(s)
| | | | | | - Eduard Grebe
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University
- Vitalant Research Institute
| | - Laurette Mhlanga
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University
| | | | | | | | | | | | | | | | - Alex Welte
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University
| |
Collapse
|