Background: Population-level estimates of prevalence of anti-SARS-CoV-2 antibody positivity (seroprevalence) is a crucial epidemiological indicator for tracking the Covid-19 epidemic. Such data are in short supply, both internationally and in South Africa. The South African blood services (the South African National Blood Service, SANBS and the Western Cape Blood Service, WCBS) are coordinating a nationally representative survey of blood donors, which it is hoped can become a cost-effective surveillance method with validity for community-level seroprevalence estimation.Methods: Leveraging existing arrangements, SANBS human research ethics committee permission was obtained to test blood donations collected on predefined days (7th, 10th ,12th ,15th ,20th ,23th and 25th January) for anti-SARS-CoV-2 antibodies, using the Roche Elecsys Anti-SARS-CoV-2 assay on the cobas e411 platform currently available in the blood services’ donation testing laboratories. Using standard methods, prevalence analysis was done by province, age and race, allowing age to be regarded as either a continuous or categorical variable. Testing was performed in the Eastern Cape (EC), Free State (FS), KwaZulu Natal (ZN) and Northern Cape (NC) provinces.Results: We report on data from 4858 donors - 1457 in EC; 463 in NC; 831 in FS and 2107 in ZN. Prevalence varied substantially across race groups and between provinces, with seroprevalence among Black donors consistently several times higher than among White donors, and the other main population groups (Coloured and Asian) not consistently represented in all provinces. There is no clear evidence that seroprevalence among donors varies by age. Weighted net estimates of prevalence (in the core age range 15-69) by province (compared with official clinically-confirmed COVID-19 case rates in mid-January 2021) are: EC-63%(2.8%), NC-32%(2.2%), FS-46%(2.4%), and ZN-52%(2.4%).Conclusions: Our study demonstrates substantial differences in dissemination of SARS-CoV-2 infection between different race groups, most likely explained by historically based differences in socio-economic status and housing conditions. As has been seen in other areas, even such high seroprevalence does not guarantee population-level immunity against new outbreaks – probably due to viral evolution and waning of antibody neutralization. Despite its limitations, notably a ‘healthy donor’ effect, it seems plausible that these estimates are reasonably generalisable to actual population level anti-SARS-CoV-2 seroprevalence, but should be further verified.

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.

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.

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.

Background:Population-level estimates of the prevalence of anti-SARS-CoV-2 antibody positivity (seroprevalence) are crucial epidemiological indicators for tracking the Covid-19 epidemic. Such data are in short supply, both internationally and in South Africa. The South African blood services (the South African National Blood Service, SANBS and the Western Cape Blood Service, WCBS) are coordinating nationwide surveillance of blood donors.Methods:Leveraging existing arrangements, SANBS human research ethics committee permission was obtained to test blood donations collected on predefined days (in January and May 2021) for anti-SARS-CoV-2 antibodies, using the Roche Elecsys Anti-SARS-CoV-2 assay on the cobas e411 and e801 platforms currently available in the blood services’ donation testing laboratories. Using standard methods, prevalence analysis was done by province, age, time, sex and race.Results:We report on data from 16762 donations. Prevalence varied substantially across race groups and between provinces, with seroprevalence among Black donors consistently several times higher than among White donors, with the other main population groups (Coloured and Asian) not well represented in all provinces. There is no clear evidence that seroprevalence among donors varies by age or sex. The weighted national estimate of prevalence (in the core age range 15-69 years) is 47.4% (95% CI 46.2-48.6). From January to May, we noted a slight but statistically insignificant increase in seroprevalence in those provinces (Gauteng and Free State) where sufficient data were available to make such an estimate.Conclusions:Our study demonstrates substantial differences in dissemination of SARS-CoV-2 infection between different race groups and provinces, in patterns consistent with known differences in historically entrenched socio-economic status and housing conditions. As has been seen in other contexts, even such high seroprevalence does not guarantee population-level immunity against new outbreaks, as evidenced by a substantial third wave that has emerged almost contemporaneously with the end of sampling in this study. The relative importance of various contributions to this resurgence (notably viral evolution, waning of antibody neutralization efficacy, and infection control fatigue) are unclear. Despite its limitations, notably a ‘healthy donor’ effect and the possible waning of detectable antibodies over the time scale of the COVID-19 pandemic, it seems plausible that these estimates are reasonably generalisable to actual population level anti-SARS-CoV-2 seroprevalence. The interpretation of occasional seroprevalence surveys as a proxy for total attack rates, over the ever-lengthening pandemic time scale is likely to become ever more complex. More frequent sampling, including linked repeat observations of frequent donors, could substantially improve the utility of blood donor surveillance.

Background: Population-level estimates of the prevalence of anti-SARS-CoV-2 antibody positivity (seroprevalence) are crucial epidemiological indicators for tracking the Covid-19 epidemic. Such data are in short supply, both internationally and in South Africa. The South African blood services (the South African National Blood Service, SANBS and the Western Cape Blood Service, WCBS) are coordinating nationwide surveillance of blood donors. Methods: Leveraging existing arrangements, SANBS human research ethics committee permission was obtained to test blood donations collected on predefined days (in January and May 2021) for anti-SARS-CoV-2 antibodies, using the Roche Elecsys Anti-SARS-CoV-2 assay on the cobas e411 and e801 platforms currently available in the blood services’ donation testing laboratories. Using standard methods, prevalence analysis was done by province, age, time, sex and race. Results: We report on data from 16762 donations. Prevalence varied substantially across race groups and between provinces, with seroprevalence among Black donors consistently several times higher than among White donors, with the other main population groups (Coloured and Asian) not well represented in all provinces. There is no clear evidence that seroprevalence among donors varies by age or sex. The weighted national estimate of prevalence (in the core age range 15-69 years) is 47.4% (95% CI 46.2-48.6). From January to May, we noted a slight but statistically insignificant increase in seroprevalence in those provinces (Gauteng and Free State) where sufficient data were available to make such an estimate. Conclusions: Our study demonstrates substantial differences in dissemination of SARS-CoV-2 infection between different race groups and provinces, in patterns consistent with known differences in historically entrenched socio-economic status and housing conditions. As has been seen in other contexts, even such high seroprevalence does not guarantee population-level immunity against new outbreaks, as evidenced by a substantial third wave that has emerged almost contemporaneously with the end of sampling in this study. The relative importance of various contributions to this resurgence (notably viral evolution, waning of antibody neutralization efficacy, and infection control fatigue) are unclear. Despite its limitations, notably a ‘healthy donor’ effect and the possible waning of detectable antibodies over the time scale of the COVID-19 pandemic, it seems plausible that these estimates are reasonably generalisable to actual population level antiSARS-CoV-2 seroprevalence. The interpretation of occasional seroprevalence surveys as a proxy for total attack rates, over the ever-lengthening pandemic time scale is likely to become ever more complex. More frequent sampling, including linked repeat observations of frequent donors, could substantially improve the utility of blood donor surveillance.

This is a brief report. The intention is simply to communicate findings and thereby trigger discussion and further work – not to provide a substantial contextual, comparative, or interpretive narrative.

Population-based surveys which ascertain HIV status are conducted in heavily affected countries, with the estimation of incidence being a primary goal. Numerous methods exist under the umbrella of ‘synthetic cohort analysis’, by which we mean estimating incidence from the age/time structure of prevalence (given knowledge on mortality). However, not enough attention has been given to how serostatus data is ‘smoothed’ into a time/age-dependent prevalence, so as to optimise the estimation of incidence.To support this and other related investigations, we developed a comprehensive simulation environment in which we simulate age/time structured SI type epidemics and surveys. Scenarios are flexibly defined by demographic rates (fertility, incidence and mortality – dependent, as appropriate, on age, time, and time-since-infection) without any reference to underlying causative processes/parameters. Primarily using 1) a simulated epidemiological scenario inspired by what is seen in the hyper-endemic HIV affected regions, and 2) pairs of cross-sectional surveys, we explored A) options for extracting the age/time structure of prevalence so as to optimise the use of the formal incidence estimation framework of Mahiane et al, and B) aspects of survey design such as the interaction of epidemic details, sample-size/sampling-density and inter-survey interval.Much as in our companion piece which crucially investigated the use of ‘recent infection’ (whereas the present analysis hinges fundamentally on the estimation of the prevalence gradient) we propose a ‘one size fits most’ process for conducting ‘synthetic cohort’ analyses of large population survey data sets, for HIV incidence estimation: fitting a generalised linear model for prevalence, separately for each age/time point where an incidence estimate is desired, using a ‘moving window’ data inclusion rule. Overall, even in very high incidence settings, sampling density requirements are onerous.The general default approach we propose for fitting HIV prevalence to data as a function of age and time appears to be broadly stable over various epidemiological stages. Particular scenarios of interest, and the applicable options for survey design and analysis, can readily be more closely investigated using our approach. We note that it is often unrealistic to expect even large household based surveys to provide meaningful incidence estimates outside of priority groups like young women, where incidence is often particularly high.