Explore the vast range of titles available.

In regions without complete-coverage civil registration and vital statistics systems there is uncertainty about even the most basic demographic indicators. In such regions, the majority of deaths occur outside hospitals and are not recorded. Worldwide, fewer than one-third of deaths are assigned a cause, with the least information available from the most impoverished nations. In populations like this, verbal autopsy (VA) is a commonly used tool to assess cause of death and estimate cause-specific mortality rates and the distribution of deaths by cause. VA uses an interview with caregivers of the decedent to elicit data describing the signs and symptoms leading up to the death. This article develops a new statistical tool known as InSilicoVA to classify cause of death using information acquired through VA. InSilicoVA shares uncertainty between cause of death assignments for specific individuals and the distribution of deaths by cause across the population. Using side-by-side comparisons with both observed and simulated data, we demonstrate that InSilicoVA has distinct advantages compared to currently available methods. Supplementary materials for this article are available online.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections may be underestimated because of limited access to testing. We measured SARS-CoV-2 seroprevalence in South Africa every 2 months during July 2020-March 2021 in randomly selected household cohorts in 2 communities. We compared seroprevalence to reported laboratory-confirmed infections, hospitalizations, and deaths to calculate infection-case, infection-hospitalization, and infection-fatality ratios in 2 waves of infection. Post-second wave seroprevalence ranged from 18% in the rural community children <5 years of age, to 59% in urban community adults 35-59 years of age. The second wave saw a shift in age distribution of case-patients in the urban community (from persons 35-59 years of age to persons at the extremes of age), higher attack rates in the rural community, and a higher infection-fatality ratio in the urban community. Approximately 95% of SARS-CoV-2 infections were not reported to national surveillance.

Understanding the distribution of socioeconomic status (SES) and its temporal dynamics within a population is critical to ensure that policies and interventions adequately and equitably contribute to the well-being and life chances of all individuals. This study assesses the dynamics of SES in a typical rural South African setting over the period 2001–2013 using data on household assets from the Agincourt Health and Demographic Surveillance System. Three SES indices, an absolute index, principal component analysis index and multiple correspondence analysis index, are constructed from the household asset indicators. Relative distribution methods are then applied to the indices to assess changes over time in the distribution of SES with special focus on location and shape shifts. Results show that the proportion of households that own assets associated with greater modern wealth has substantially increased over time. In addition, relative distributions in all three indices show that the median SES index value has shifted up and the distribution has become less polarized and is converging towards the middle. However, the convergence is larger from the upper tail than from the lower tail, which suggests that the improvement in SES has been slower for poorer households. The results also show persistent ethnic differences in SES with households of former Mozambican refugees being at a disadvantage. From a methodological perspective, the study findings demonstrate the comparability of the easy-to-compute absolute index to other SES indices constructed using more advanced statistical techniques in assessing household SES.

Background Verbal autopsy is an increasingly important methodology for assigning causes to otherwise uncertified deaths, which amount to around 50% of global mortality and cause much uncertainty for health planning. The World Health Organization sets international standards for the structure of verbal autopsy interviews and for cause categories that can reasonably be derived from verbal autopsy data. In addition, computer models are needed to efficiently process large quantities of verbal autopsy interviews to assign causes of death in a standardised manner. Here, we present the InterVA-5 model, developed to align with the WHO-2016 verbal autopsy standard. This is a harmonising model that can process input data from WHO-2016, as well as earlier WHO-2012 and Tariff-2 formats, to generate standardised cause-specific mortality profiles for diverse contexts. The software development involved building on the earlier InterVA-4 model, and the expanded knowledge base required for InterVA-5 was informed by analyses from a training dataset drawn from the Population Health Metrics Research Collaboration verbal autopsy reference dataset, as well as expert input. Results The new model was evaluated against a test dataset of 6130 cases from the Population Health Metrics Research Collaboration and 4009 cases from the Afghanistan National Mortality Survey dataset. Both of these sources contained around three quarters of the input items from the WHO-2016, WHO-2012 and Tariff-2 formats. Cause-specific mortality fractions across all applicable WHO cause categories were compared between causes assigned in participating tertiary hospitals and InterVA-5 in the test dataset, with concordance correlation coefficients of 0.92 for children and 0.86 for adults. The InterVA-5 model’s capacity to handle different input formats was evaluated in the Afghanistan dataset, with concordance correlation coefficients of 0.97 and 0.96 between the WHO-2016 and the WHO-2012 format for children and adults respectively, and 0.92 and 0.87 between the WHO-2016 and the Tariff-2 format respectively. Conclusions Despite the inherent difficulties of determining “truth” in assigning cause of death, these findings suggest that the InterVA-5 model performs well and succeeds in harmonising across a range of input formats. As more primary data collected under WHO-2016 become available, it is likely that InterVA-5 will undergo minor re-versioning in the light of practical experience. The model is an important resource for measuring and evaluating cause-specific mortality globally.

Data on respiratory syncytial virus (RSV) incidence and household transmission are limited. To describe RSV incidence and transmission, we conducted a prospective cohort study in rural and urban communities in South Africa over two seasons during 2017-2018. Nasopharyngeal swabs were collected twice-weekly for 10 months annually and tested for RSV using PCR. We tested 81,430 samples from 1,116 participants in 225 households (follow-up 90%). 32% (359/1116) of individuals had ≥1 RSV infection; 10% (37/359) had repeat infection during the same season, 33% (132/396) of infections were symptomatic, and 2% (9/396) sought medical care. Incidence was 47.2 infections/100 person-years and highest in children <5 years (78.3). Symptoms were commonest in individuals aged <12 and ≥65 years. Individuals 1-12 years accounted for 55% (134/242) of index cases. Household cumulative infection risk was 11%. On multivariable analysis, index cases with ≥2 symptoms and shedding duration >10 days were more likely to transmit; household contacts aged 1-4 years vs. ≥65 years were more likely to acquire infection. Within two South African communities, RSV attack rate was high, and most infections asymptomatic. Young children were more likely to introduce RSV into the home, and to be infected. Future studies should examine whether vaccines targeting children aged <12 years could reduce community transmission. Respiratory syncytial virus (RSV) causes a high burden of disease in children, particularly in lower- and middle-income countries. In this prospective household-based observational cohort study in South Africa, the authors estimate the incidence of RSV and identify risk factors for transmission.

Background Evidence shows that HIV prevalence among young women in sub-Saharan Africa increases almost five-fold between ages 15 and 24, with almost a quarter of young women infected by their early-to mid-20s. Transactional sex or material exchange for sex is a relationship dynamic that has been shown to have an association with HIV infection. Methods Using five focus group discussions and 19 in-depth interviews with young women enrolled in the HPTN 068 conditional cash transfer trial (2011–2015), this qualitative study explores young women’s perceptions of transactional sex within the structural and cultural context of rural South Africa. The analysis also considers the degree to which young women perceive themselves as active agents in such relationships and whether they recognise a link between transactional sex and HIV risk. Results Young women believe that securing their own financial resources will ultimately improve their bargaining position in their sexual relationships, and open doors to a more financially independent future. Findings suggest there is a nuanced relationship between sex, love and gifts: money has symbolic meaning, and money transfers, when framed as gifts, indicates a young woman’s value and commitment from the man. This illustrates the complexity of transactional sex; the way it is positioned in the HIV literature ignores that “exchanges” serve as fulcrums around which romantic relationships are organised. Finally, young women express agency in their choice of partner, but their agency weakens once they are in a relationship characterised by exchange, which may undermine their ability to translate perceived agency into STI and HIV risk reduction efforts. Conclusions This research underscores the need to recognise that transactional sex is embedded in adolescent romantic relationships, but that certain aspects make young women particularly vulnerable to HIV. This is especially true in situations of restricted choice and circumscribed employment opportunities. HIV prevention educational programmes could be coupled with income generation trainings, in order to leverage youth resilience and protective skills within the confines of difficult economic and social circumstances. This would provide young women with the knowledge and means to more successfully navigate safer sexual relationships.

South Africa was among the first countries to detect the SARS-CoV-2 Omicron variant. However, the size of its Omicron BA.1 and BA.2 subvariants (BA.1/2) wave remains poorly understood. We analyzed sequential serum samples collected through a prospective cohort study before, during, and after the Omicron BA.1/2 wave to infer infection rates and monitor changes in the immune histories of participants over time. We found that the Omicron BA.1/2 wave infected more than half of the cohort population, with reinfections and vaccine breakthroughs accounting for > 60% of all infections in both rural and urban sites. After the Omicron BA.1/2 wave, we found few (< 6%) remained naïve to SARS-CoV-2 and the population immunologic landscape is fragmented with diverse infection/immunization histories. Prior infection with the ancestral strain, Beta, and Delta variants provided 13%, 34%, and 51% protection against Omicron BA.1/2 infection, respectively. Hybrid immunity and repeated prior infections reduced the risks of Omicron BA.1/2 infection by 60% and 85% respectively. Our study sheds light on a rapidly shifting landscape of population immunity in the Omicron era and provides context for anticipating the long-term circulation of SARS-CoV-2 in populations no longer naïve to the virus. Emergence of the Omicron BA.1/2 SARS-CoV-2 subvariants led to a wave of infection South Africa. Here, the authors use serological data from a prospective household study to characterise infection rates in the context of diverse immune histories following vaccination and exposure to different variants.

Globally, as of December 2023, over 700 million cases of COVID-19 were confirmed since the initial outbreak late in 2019, claiming around 7 million lives and fuelling widespread fear and anxiety. However, prospective patient-data are unavailable to assess individuals' perceptions of risk of severe COVID-19 illness, which may imply actual disease severity and inform risk perception for future epidemics. We surveyed 1701 adults about their concern for severe COVID-19 disease using a population-based survey of rural South Africans. The initial telephonic survey was conducted between August-October 2020 with a follow-up survey conducted between August-October 2021. Multinomial logistic regression was used to investigate predictors of perceived COVID-19 illness severity (low, medium, or high) controlling for measured confounders. The prevalence of concern for COVID-19 illness severity in 2020 was 28.7% low, 26.8% moderate and 44.5% severe, with corresponding levels in 2021 of 42%, 31.8% and 29.2%, respectively. Although older age was associated with a lower odds of COVID-19 concern [50-59 years (aOR=0.54, 95% CI: 0.38-0.75)], [≥60 years (aOR=0.41,95% CI: 0.41-0.57)], adults having ≥1 chronic conditions (aOR=1.38,1.00-1.89) or residing outside of the study community (aOR=1.29,1.01-1.65) were more likely to experience moderate and high concern for illness severity, respectively. Understanding presumptive COVID-19 disease severity may help disentangle various underlying mechanisms behind personal risk assessment. This may inform current thinking and practice of public health emergency medicine in managing emerging and re-emerging respiratory diseases with pandemic potential such as hPMV.

Background South Africa faces a complex dual burden of chronic communicable and non-communicable diseases (NCDs). In response, the Integrated Chronic Disease Management (ICDM) model was initiated in primary health care (PHC) facilities in 2011 to leverage the HIV/ART programme to scale-up services for NCDs, achieve optimal patient health outcomes and improve the quality of medical care. However, little is known about the quality of care in the ICDM model. The objectives of this study were to: i) assess patients’ and operational managers’ satisfaction with the dimensions of ICDM services; and ii) evaluate the quality of care in the ICDM model using Avedis Donabedian’s theory of relationships between structure (resources), process (clinical activities) and outcome (desired result of healthcare) constructs as a measure of quality of care. Methods A cross-sectional study was conducted in 2013 in seven PHC facilities in the Bushbuckridge municipality of Mpumalanga Province, north-east South Africa - an area underpinned by a robust Health and Demographic Surveillance System (HDSS). The patient satisfaction questionnaire (PSQ-18), with measures reflecting structure/process/outcome (SPO) constructs, was adapted and administered to 435 chronic disease patients and the operational managers of all seven PHC facilities. The adapted questionnaire contained 17 dimensions of care, including eight dimensions identified as priority areas in the ICDM model - critical drugs, equipment, referral, defaulter tracing, prepacking of medicines, clinic appointments, waiting time, and coherence. A structural equation model was fit to operationalise Donabedian’s theory, using unidirectional, mediation, and reciprocal pathways. Results The mediation pathway showed that the relationships between structure, process and outcome represented quality systems in the ICDM model. Structure correlated with process (0.40) and outcome (0.75). Given structure, process correlated with outcome (0.88). Of the 17 dimensions of care in the ICDM model, three structure (equipment, critical drugs, accessibility), three process (professionalism, friendliness and attendance to patients) and three outcome (competence, confidence and coherence) dimensions reflected their intended constructs. Conclusion Of the priority dimensions, referrals, defaulter tracing, prepacking of medicines, appointments, and patient waiting time did not reflect their intended constructs. Donabedian’s theoretical framework can be used to provide evidence of quality systems in the ICDM model.

Cash transfers are a promising but understudied intervention that may protect cognitive function in adults. Although South Africa has a rapidly ageing population, little is known about the nature of association between cash transfers and cognitive function in this setting. We leveraged age-eligibility expansions to South Africa's Child Support Grant (CSG) to investigate the association between duration of CSG eligibility and cognitive function of biological mothers of child beneficiaries in South Africa. We analysed 2014/2015 baseline data from 944 women, aged 40-59 years with at least one CSG-eligible child, enrolled in the population-representative HAALSI cohort in Agincourt, South Africa. Duration of CSG eligibility for each mother was calculated based on the birth dates of all their children and the CSG age-eligibility expansion years (2003-2012). Cognitive function was measured using a cognitive battery administered at the HAALSI baseline interview. Linear regression was used to estimate the association between duration of CSG eligibility, dichotomized as low (≤10 years) and high (>10 years) eligibility, and cognitive function z-scores of the mothers. High vs. low duration of CSG eligibility, was associated with higher cognitive function z-scores in the full sample [β: 0.15 SD units; 95% CI: 0.04, 0.26; p-value = 0.01]. In mothers with one to four lifetime children, but not five or more, high vs. low duration of CSG eligibility, was associated with higher cognitive function z-scores [β: 0.19 SD units; 95% CI: 0.05, 0.34, p-value = 0.02]. Government cash transfers given to support raising children may confer substantial protective effects on the subsequent cognitive function of mothers. Further studies are needed to understand how parity may influence this relationship. Our findings bring evidence to policymakers for designing income supplementation programmes to promote healthy cognitive ageing in low-income settings.