The WHO Unity Studies initiative engaged low- and middle-income countries in the implementation of standardised SARS-CoV-2 sero-epidemiological investigation protocols and timely sharing of comparable results for evidence-based action. To gain a deeper understanding of the methodological challenges faced when conducting seroprevalence studies in the African region, we conducted unstructured interviews with key study teams in five countries. We discuss the challenges identified: participant recruitment and retention, sampling, sample and data management, data analysis and presentation. Potential solutions to aid future implementation include preparedness actions such as the development of new tools, robust planning and practice.
Human immunodeficiency virus (HIV) infected adults are at a higher risk of pneumococcal colonisation and disease, even while receiving antiretroviral therapy (ART). To help evaluate potential indirect effects of vaccination of HIV-infected adults, we assessed whether HIV-infected adults disproportionately contribute to household transmission of pneumococci. We constructed a hidden Markov model to capture the dynamics of pneumococcal carriage acquisition and clearance observed during a longitudinal household-based nasopharyngeal swabbing study, while accounting for sample misclassifications. Households were followed-up twice weekly for approximately 10 months each year during a three-year study period for nasopharyngeal carriage detection via real-time PCR. We estimated the effect of participant’s age, HIV status, presence of a HIV-infected adult within the household and other covariates on pneumococcal acquisition and clearance probabilities. Of 1,684 individuals enrolled, 279 (16.6%) were younger children (<5 years-old) of whom 4 (1.5%) were HIV-infected and 726 (43.1%) were adults (≥18 years-old) of whom 214 (30.4%) were HIV-infected, most (173, 81.2%) with high CD4+ count. The observed range of pneumococcal carriage prevalence across visits was substantially higher in younger children (56.9–80.5%) than older children (5–17 years-old) (31.7–50.0%) or adults (11.5–23.5%). We estimate that 14.4% (95% Confidence Interval [CI]: 13.7–15.0) of pneumococcal-negative swabs were false negatives. Daily carriage acquisition probabilities among HIV-uninfected younger children were similar in households with and without HIV-infected adults (hazard ratio: 0.95, 95%CI: 0.91–1.01). Longer average carriage duration (11.4 days, 95%CI: 10.2–12.8 vs 6.0 days, 95%CI: 5.6–6.3) and higher median carriage density (622 genome equivalents per millilitre, 95%CI: 507–714 vs 389, 95%CI: 311.1–435.5) were estimated in HIV-infected vs HIV-uninfected adults. The use of ART and antibiotics substantially reduced carriage duration in all age groups, and acquisition rates increased with household size. Although South African HIV-infected adults on ART have longer carriage duration and density than their HIV-uninfected counterparts, they show similar patterns of pneumococcal acquisition and onward transmission.
Background: Seroprevalence studies are important for quantifying the burden of SARS-CoV-2 infections in resource-constrained countries.Methods: We conducted a cross-sectional household survey spanning the second pandemic wave (November 2020 – April 2021) in three communities. Blood was collected for SARS-CoV-2 antibody (two ELISA assays targeting spike and nucleocapsid) and HIV testing. An individual was considered seropositive if testing positive on ≥1 assay. Factors associated with infection, and the age-standardised infection to case detection rate (ICR), infection hospitalisation rate (IHR) and infection fatality rate (IFR) were calculated.Findings: Overall 7959 participants were enrolled, with a median age of 34 years and HIV prevalence of 22.7%. SARS-CoV-2 seroprevalence was 45.2% (95% confidence interval 43.7% - 46.7%), and increased from 26.9% among individuals enrolled in December 2020 to 47.1% among individuals in April 2021. On multivariable analysis, seropositivity was associated with age, sex, race, being overweight/obese, having respiratory symptoms, and low socioeconomic status. Persons living with HIV (PLWH) with high viral load were less likely to be seropositive compared to HIV-uninfected individuals. The site-specific ICR, IHR and IFR ranged across sites from 4.4% to 8.2%, 1.2% to 2.5% and 0.3% to 0.6%, respectively.Interpretation: South Africa has experienced a large burden of SARS-CoV-2 infections, with <10% of infections diagnosed. Lower seroprevalence among non-virally suppressed PLWH, likely as a result of inadequate antibody production, highlights the need to prioritise this group for intervention.Funding Information: This study was supported by the South African MRC, Wellcome Trust and UK Foreign, Commonwealth and Development Office, and US CDC.Declaration of Interests: C. Cohen has received grant support from Sanofi Pasteur, Advanced Vaccine Initiative, and payment of travel costs from Parexel. NW and AvG have received grant support from Sanofi Pasteur. All other authors declare no conflict of interest.Ethics Approval Statement: This study was approved by the University of the Witwatersrand (M200861) and by the respective community and provincial research committees.
Introduction . Shiga toxin-producing Escherichia coli (STEC) are foodborne pathogens that may cause diarrhoeal outbreaks and occasionally are associated with haemolytic-uraemic syndrome (HUS). We report on STEC O26:H11 associated with a cluster of four HUS cases in South Africa in 2017. Methodology . All case-patients were female and aged 5 years and under. Standard microbiological tests were performed for culture and identification of STEC from specimens (human stool and food samples). Further analysis of genomic DNA extracted from bacterial cultures and specimens included PCR for specific virulence genes, whole-genome sequencing and shotgun metagenomic sequencing. Results . For 2/4 cases, stool specimens revealed STEC O26:H11 containing eae , stx2a and stx2b virulence genes. All food samples were found to be negative for STEC. No epidemiological links could be established between the HUS cases. Dried meat products were the leading food item suspected to be the vehicle of transmission for these cases, as 3/4 case-patients reported they had eaten this. However, testing of dried meat products could not confirm this. Conclusion . Since STEC infection does not always lead to severe symptoms, it is possible that many more cases were associated with this cluster and largely went unrecognized.
Introduction: we investigated an outbreak of influenza-like illness (ILI) at a boarding school in Eastern Cape Province, South Africa. We aimed to confirm the etiological agent, estimate attack rates and identify risk factors for illness.
ABSTRACT Background SARS-CoV-2 infections may be underestimated due to limited testing access, particularly in sub-Saharan Africa. South Africa experienced two SARS-CoV-2 waves, the second associated with emergence of variant 501Y.V2. In this study, we report longitudinal SARS-CoV-2 seroprevalence in cohorts in two communities in South Africa. Methods We measured SARS-CoV-2 seroprevalence two monthly in randomly selected household cohorts in a rural and an urban community (July 2020-March 2021). We compared seroprevalence to laboratory-confirmed infections, hospitalisations and deaths reported in the districts to calculate infection-case (ICR), infection-hospitalisation (IHR) and infection-fatality ratio (IFR) in the two waves of infection. Findings Seroprevalence after the second wave ranged from 18% (95%CrI 10-26%) and 28% (95%CrI 17-41%) in children <5 years to 37% (95%CrI 28-47%) in adults aged 19-34 years and 59% (95%CrI 49-68%) in adults aged 35-59 years in the rural and urban community respectively. Individuals infected in the second wave were more likely to be from the rural site (aOR 4.7, 95%CI 2.9-7.6), and 5-12 years (aOR 2.1, 95%CI 1.1-4.2) or ≥60 years (aOR 2.8, 95%CI 1.1-7.0), compared to 35-59 years. The in-hospital IFR in the urban site was significantly increased in the second wave 0.36% (95%CI 0.28-0.57%) compared to the first wave 0.17% (95%CI 0.15-0.20%). ICR ranged from 3.69% (95%CI 2.59-6.40%) in second wave at urban community, to 5.55% (95%CI 3.40-11.23%) in first wave in rural community. Interpretation The second wave was associated with a shift in age distribution of cases from individuals aged to 35-59 to individuals at the extremes of age, higher attack rates in the rural community and a higher IFR in the urban community. Approximately 95% of SARS-CoV-2 infections in these two communities were not reported to the national surveillance system, which has implications for contact tracing and infection containment. Funding US Centers for Disease Control and Prevention Research in context Evidence before this study Seroprevalence studies provide better estimates of SARS-CoV-2 burden than laboratory-confirmed cases because many infections may be missed due to restricted access to care and testing, or differences in disease severity and health-care seeking behaviour. This underestimation may be amplified in African countries, where testing access may be limited. Seroprevalence data from sub-Saharan Africa are limited, and comparing seroprevalence estimates between countries can be challenging because populations studied and timing of the study relative to country-specific epidemics differs. During the first wave of infections in each country, seroprevalence was estimated at 4% in Kenya and 11% in Zambia. Seroprevalence estimates in South African blood donors is estimated to range between 32% to 63%. South Africa has experienced two waves of infection, with the emergence of the B.1.351/501Y.V2 variant of concern after the first wave. Reported SARS-CoV-2 cases may not be a true reflection of SARS-CoV-2 burden and specifically the differential impact of the first and second waves of infection. Added value of this study We collected longitudinal blood samples from prospectively followed rural and urban communities, randomly selected, household cohorts in South Africa between July 2020 and March 2021. From 668 and 598 individuals included from the rural and urban communities, respectively, seroprevalence was found to be 7% (95%CrI 5-9%) and 27% (95%CrI 23-31%), after the first wave of infection, and 26% (95%CrI 22-29%) and 41% (95%CrI 37-45%) after the second wave, in rural and urban study districts, respectively. After standardising for age, we estimated that only 5% of SARS-CoV-2 infections were laboratory-confirmed and reported. Infection-hospitalisation ratios in the urban community were higher in the first (2.01%, 95%CI 1.57-2.57%) and second (2.29%, 95%CI 1.63-3.94%) wave than the rural community where there was a 0.75% (95%CI 0.49-1.41%) and 0.66% (95%CI 0.50-0.98%) infection-hospitalisation ratio in the first and second wave, respectively. When comparing the infection fatality ratios for the first and second SARS-CoV-2 waves, at the urban site, the ratios for both in-hospital and excess deaths to cases were significantly higher in the second wave (0.36%, 95%CI 0.28-0.57% in-hospital and 0.51%, 95%CI 0.34-0.93% excess deaths), compared to the first wave in-hospital (0.17%, 95%CI 0.15-0.20%) and excess (0.13%, 95%CI 0.10-0.17%) fatality ratios, p<0.001 and p<0.001, respectively). In the rural community, the point estimates for infection-fatality ratios also increased in the second wave compared to the first wave for in-hospital deaths, 0.13% (95%CI 0.10-0.23%) first wave vs 0.20% (95%CI 0.13%-0.28%) second wave, and excess deaths (0.51%, 95%CI 0.30-1.06% vs 0.70%, 95%CI 0.49-1.12%), although neither change was statistically significant. Implications of all the available evidence In South Africa, the overall prevalence of SARS-CoV-2 infections is substantially underestimated, resulting in many cases being undiagnosed and without the necessary public health action to isolate and trace contacts to prevent further transmission. There were more infections during the first wave in the urban community, and the second wave in the rural community. Although there were less infections during the second wave in the urban community, the infection-fatality ratios were significantly higher compared to the first wave. The lower infection-hospitalisation ratio and higher excess infection-fatality ratio in the rural community likely reflect differences in access to care or prevalence of risk factors for progression to severe disease in these two communities. In-hospital infection-fatality ratios for both communities during the first wave were comparable with what was experienced during the first wave in India (0.15%) for SARS-CoV-2 confirmed deaths. To our knowledge, these are the first longitudinal seroprevalence data from a sub-Saharan Africa cohort, and provide a more accurate understanding of the pandemic, allowing for serial comparisons of antibody responses in relation to reported laboratory-confirmed SARS-CoV-2 infections within diverse communities.
Background Data on the national-level impact of pneumococcal conjugate vaccine (PCV) introduction on mortality are lacking from Africa. PCV was introduced in South Africa in 2009. We estimated the impact of PCV introduction on all-cause pneumonia mortality in South Africa, while controlling for changes in mortality due to other interventions. Methods and findings We used national death registration data in South Africa from 1999 to 2016 to assess the impact of PCV introduction on all-cause pneumonia mortality in all ages, with the exclusion of infants aged <1 month. We created a composite (synthetic) control using Bayesian variable selection of nondiarrheal, nonpneumonia, and nonpneumococcal deaths to estimate the number of expected all-cause pneumonia deaths in the absence of PCV introduction post 2009. We compared all-cause pneumonia deaths from the death registry to the expected deaths in 2012 to 2016. We also estimated the number of prevented deaths during 2009 to 2016. Of the 9,324,638 deaths reported in South Africa from 1999 to 2016, 12·6% were pneumonia-related. Compared to number of deaths expected, we estimated a 33% (95% credible interval (CrI) 26% to 43%), 23% (95%CrI 17% to 29%), 25% (95%CrI 19% to 32%), and 23% (95%CrI 11% to 32%) reduction in pneumonia mortality in children aged 1 to 11 months, 1 to 4 years, 5 to 7 years, and 8 to 18 years in 2012 to 2016, respectively. In total, an estimated 18,422 (95%CrI 12,388 to 26,978) pneumonia-related deaths were prevented from 2009 to 2016 in children aged <19 years. No declines were estimated observed among adults following PCV introduction. This study was mainly limited by coding errors in original data that could have led to a lower impact estimate, and unmeasured factors could also have confounded estimates. Conclusions This study found that the introduction of PCV was associated with substantial reduction in all-cause pneumonia deaths in children aged 1 month to <19 years. The model predicted an effect of PCV in age groups who were eligible for vaccination (1 months to 4 years), and an indirect effect in those too old (8 to 18 years) to be vaccinated. These findings support sustaining pneumococcal vaccination to reduce pneumonia-related mortality in children.
Abstract Background Data on the characteristics of individuals with mild and asymptomatic infections with different SARS-CoV-2 variants are limited. We therefore compared the characteristics of individuals infected with ancestral, Beta and Delta SARS-CoV-2 variants in South Africa. Methods We conducted a prospective cohort study in a rural and an urban site during July 2020-August 2021. Mid-turbinate nasal swabs were collected twice-weekly from household members irrespective of symptoms and tested for SARS-CoV-2 using real-time reverse transcription polymerase chain reaction (rRT-PCR). Differences by variant were evaluated using multinomial regression. Results We included 1200 individuals from 222 households and 648 rRT-PCR-confirmed infection episodes (66, 10%ancestral, 260, 40% Beta, 322, 50%Delta). Symptomatic proportion was similar for ancestral (7, 11%), Beta (44, 17%), and Delta (46, 14%) infections (p=0.4). After accounting for previous infection, peak incidence shifted to younger age groups in successive waves (40-59 years ancestral, 19-39 years Beta, 13-18 years Delta). On multivariable analysis, compared to ancestral, Beta infection was more common in individuals aged 5-12 years (vs 19-39)(adjusted odds ratio (aOR) 2.6, 95% confidence interval (CI)1.1-6.6) and PCR cycle threshold (Ct) value <30 (vs >35)(aOR 3.2, 95%CI 1.3-7.9), while Delta was more common in individuals aged <5 (aOR 6.7, 95%CI1.4-31.2) and 5-12 years (aOR 6.6 95%CI2.6-16.7)(vs 19-39) and Ct value <30 (aOR 4.5, 95%CI 1.3-15.5) and 30-35 (aOR 6.0, 95%CI 2.3-15.7)(vs >35). Conclusions Consecutive SARS-CoV-2 waves with Beta and Delta variants were associated with a shift to younger individuals. Beta and Delta infections were associated with higher viral loads potentially increasing infectiousness.
Streptococcus pneumoniae serotype 1 (ST1) was an important cause of invasive pneumococcal disease (IPD) globally before the introduction of pneumococcal conjugate vaccines (PCVs) containing ST1 antigen. The Pneumococcal Serotype Replacement and Distribution Estimation (PSERENADE) project gathered ST1 IPD surveillance data from sites globally and aimed to estimate PCV10/13 impact on ST1 IPD incidence. We estimated ST1 IPD incidence rate ratios (IRRs) comparing the pre-PCV10/13 period to each post-PCV10/13 year by site using a Bayesian multi-level, mixed-effects Poisson regression and all-site IRRs using a linear mixed-effects regression (N = 45 sites). Following PCV10/13 introduction, the incidence rate (IR) of ST1 IPD declined among all ages. After six years of PCV10/13 use, the all-site IRR was 0.05 (95% credibility interval 0.04–0.06) for all ages, 0.05 (0.04–0.05) for <5 years of age, 0.08 (0.06–0.09) for 5–17 years, 0.06 (0.05–0.08) for 18–49 years, 0.06 (0.05–0.07) for 50–64 years, and 0.05 (0.04–0.06) for ≥65 years. PCV10/13 use in infant immunization programs was followed by a 95% reduction in ST1 IPD in all ages after approximately 6 years. Limited data availability from the highest ST1 disease burden countries using a 3 + 0 schedule constrains generalizability and data from these settings are needed.
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