An HIV-1 risk assessment tool for women aged 15-49 in African countries: A pooled analysis across 15 nationally representative surveys.

BACKGROUND: Women in Africa disproportionately acquire HIV-1. Understanding which women are most likely to acquire HIV-1 can guide focused prevention with pre-exposure prophylaxis (PrEP). Our objective is to identify women at highest risk of HIV-1 and estimate PrEP efficiency at different sensitivity levels. METHODS: Nationally representative data were collected from 2015-2019 from 15 population-based household surveys. This analysis included women aged 15-49 who tested HIV-1 sero-negative or had recent HIV-1. Least absolute shrinkage and selection operator regression models were fit with 28 variables to predict recent HIV-1. Models were trained on the full population and internally cross-validated. Performance was evaluated using area under the receiver-operating-characteristic curve (AUC), sensitivity, and number needed to treat (NNT) with PrEP to avert one infection. RESULTS: Among 209,012 participants 248 had recent HIV-1 infection, representing 118 million women and 402,000 (95% CI: 309,000-495,000) new annual infections. Two variables were retained in the model: living in a subnational area with high HIV-1 viremia and having a sexual partner living outside the home. Full-population AUC was 0.80 (95% CI: 0.76-0.84); cross-validated AUC was 0.79 (95% CI: 0.75-0.84). At a sensitivity of 33%, up to 130,000 cases could be averted if 7.9 million women were perfectly adherent to PrEP; NNT would be 61. At a sensitivity of 67%, up to 260,000 cases could be averted if 25.1 million women were perfectly adherent to PrEP; the NNT would be 96. CONCLUSIONS: This risk assessment tool was generalizable, predictive, and parsimonious with tradeoffs between reach and efficiency.

Understanding the differential impacts of COVID-19 among hospitalised patients in South Africa for equitable response.

BACKGROUND: There are limited in-depth analyses of COVID-19 differential impacts, especially in resource-limited settings such as South Africa (SA). OBJECTIVES: To explore context-specific sociodemographic heterogeneities in order to understand the differential impacts of COVID-19. METHODS: Descriptive epidemiological COVID-19 hospitalisation and mortality data were drawn from daily hospital surveillance data, National Institute for Communicable Diseases (NICD) update reports (6 March 2020 - 24 January 2021) and the Eastern Cape Daily Epidemiological Report (as of 24 March 2021). We examined hospitalisations and mortality by sociodemographics (age using 10-year age bands, sex and race) using absolute numbers, proportions and ratios. The data are presented using tables received from the NICD, and charts were created to show trends and patterns. Mortality rates (per 100 000 population) were calculated using population estimates as a denominator for standardisation. Associations were determined through relative risks (RRs), 95% confidence intervals (CIs) and p-values <0.001. RESULTS: Black African females had a significantly higher rate of hospitalisation (8.7% (95% CI 8.5 - 8.9)) compared with coloureds, Indians and whites (6.7% (95% CI 6.0 - 7.4), 6.3% (95% CI 5.5 - 7.2) and 4% (95% CI 3.5 - 4.5), respectively). Similarly, black African females had the highest hospitalisation rates at a younger age category of 30 - 39 years (16.1%) compared with other race groups. Whites were hospitalised at older ages than other races, with a median age of 63 years. Black Africans were hospitalised at younger ages than other race groups, with a median age of 52 years. Whites were significantly more likely to die at older ages compared with black Africans (RR 1.07; 95% CI 1.06 - 1.08) or coloureds (RR 1.44; 95% CI 1.33 - 1.54); a similar pattern was found between Indians and whites (RR 1.59; 95% CI 1.47 - 1.73). Women died at older ages than men, although they were admitted to hospital at younger ages. Among black Africans and coloureds, females (50.9 deaths per 100 000 and 37 per 100 000, respectively) had a higher COVID-19 death rate than males (41.2 per 100 000 and 41.5 per 100 000, respectively). However, among Indians and whites, males had higher rates of deaths than females. The ratio of deaths to hospitalisations by race and gender increased with increasing age. In each age group, this ratio was highest among black Africans and lowest among whites. CONCLUSIONS: The study revealed the heterogeneous nature of COVID-19 impacts in SA. Existing socioeconomic inequalities appear to shape COVID-19 impacts, with a disproportionate effect on black Africans and marginalised and low socioeconomic groups. These differential impacts call for considered attention to mitigating the health disparities among black Africans.

Prevalence and unmet need for diabetes care across the care continuum in a national sample of South African adults: Evidence from the SANHANES-1, 2011-2012.

South Africa faces an epidemic of chronic non-communicable diseases (NCDs), yet national surveillance is limited due to the lack of recent data. We used data from the first comprehensive national survey on NCDs-the South African National Health and Nutrition Examination Survey (SANHANES-1 (2011-2012))-to evaluate the prevalence of and health system response to diabetes through a diabetes care cascade. We defined diabetes as a Hemoglobin A1c equal to or above 6.5% or currently on treatment for diabetes. We constructed a diabetes care cascade by categorizing the population with diabetes into those who were unscreened, screened but undiagnosed, diagnosed but untreated, treated but uncontrolled, and treated and controlled. We then used multivariable logistic regression models to explore factors associated with diagnosed and undiagnosed diabetes. The age-standardized prevalence of diabetes in South Africans aged 15+ was 10.1%. Prevalence rates were higher among the non-white population and among women. Among individuals with diabetes, a total of 45.4% were unscreened, 14.7% were screened but undiagnosed, 2.3% were diagnosed but untreated, 18.1% were treated but uncontrolled, and 19.4% were treated and controlled, suggesting that 80.6% of the diabetic population had unmet need for care. The diabetes care cascade revealed significant losses from lack of screening, between screening and diagnosis, and between treatment and control. These results point to significant unmet need for diabetes care in South Africa. Additionally, this analysis provides a benchmark for evaluating efforts to manage the rising burden of diabetes in South Africa.

Diabetes diagnosis and care in sub-Saharan Africa: pooled analysis of individual data from 12 countries.

BACKGROUND: Despite widespread recognition that the burden of diabetes is rapidly growing in many countries in sub-Saharan Africa, nationally representative estimates of unmet need for diabetes diagnosis and care are in short supply for the region. We use national population-based survey data to quantify diabetes prevalence and met and unmet need for diabetes diagnosis and care in 12 countries in sub-Saharan Africa. We further estimate demographic and economic gradients of met need for diabetes diagnosis and care. METHODS: We did a pooled analysis of individual-level data from nationally representative population-based surveys that met the following inclusion criteria: the data were collected during 2005-15; the data were made available at the individual level; a biomarker for diabetes was available in the dataset; and the dataset included information on use of core health services for diabetes diagnosis and care. We first quantified the population in need of diabetes diagnosis and care by estimating the prevalence of diabetes across the surveys; we also quantified the prevalence of overweight and obesity, as a major risk factor for diabetes and an indicator of need for diabetes screening. Second, we determined the level of met need for diabetes diagnosis, preventive counselling, and treatment in both the diabetic and the overweight and obese population. Finally, we did survey fixed-effects regressions to establish the demographic and economic gradients of met need for diabetes diagnosis, counselling, and treatment. FINDINGS: We pooled data from 12 nationally representative population-based surveys in sub-Saharan Africa, representing 38 311 individuals with a biomarker measurement for diabetes. Across the surveys, the median prevalence of diabetes was 5% (range 2-14) and the median prevalence of overweight or obesity was 27% (range 16-68). We estimated seven measures of met need for diabetes-related care across the 12 surveys: (1) percentage of the overweight or obese population who received a blood glucose measurement (median 22% [IQR 11-37]); and percentage of the diabetic population who reported that they (2) had ever received a blood glucose measurement (median 36% [IQR 27-63]); (3) had ever been told that they had diabetes (median 27% [IQR 22-51]); (4) had ever been counselled to lose weight (median 15% [IQR 13-23]); (5) had ever been counselled to exercise (median 15% [IQR 11-30]); (6) were using oral diabetes drugs (median 25% [IQR 18-42]); and (7) were using insulin (median 11% [IQR 6-13]). Compared with those aged 15-39 years, the adjusted odds of met need for diabetes diagnosis (measures 1-3) were 2·22 to 3·53 (40-54 years) and 3·82 to 5·01 (≥55 years) times higher. The adjusted odds of met need for diabetes diagnosis also increased consistently with educational attainment and were between 3·07 and 4·56 higher for the group with 8 years or more of education than for the group with less than 1 year of education. Finally, need for diabetes care was significantly more likely to be met (measures 4-7) in the oldest age and highest educational groups. INTERPRETATION: Diabetes has already reached high levels of prevalence in several countries in sub-Saharan Africa. Large proportions of need for diabetes diagnosis and care in the region remain unmet, but the patterns of unmet need vary widely across the countries in our sample. Novel health policies and programmes are urgently needed to increase awareness of diabetes and to expand coverage of preventive counselling, diagnosis, and linkage to diabetes care. Because the probability of met need for diabetes diagnosis and care consistently increases with age and educational attainment, policy makers should pay particular attention to improved access to diabetes services for young adults and people with low educational attainment. FUNDING: None.

Determinants of multiple sexual partnerships in South Africa.

BACKGROUND: This paper aims to examine determinants of multiple sexual partnerships (MSPs) among South African men and women using a nationally representative sample. METHODS: Quantitative and qualitative data from a 2008 population-based cross-sectional survey were used. The analysis focused on the 6990 (33.6% of total sample) who were 15 years and older and reported sexual activity in the prior 12 months. The qualitative component consisted of 15 focus group interviews investigating values underlying MSP behaviors. RESULTS: Predictors of MSP common across gender were race, having a history of STI, being in a short relationships (<1 year) and suspecting the current partner of infidelity. MSP among men enjoyed greater community acceptance and was mainly done for social status. Furthermore, men reporting MSP were mostly younger (15-24 years old) and use condom at last sex. Among women, determinants of MSP included economic vulnerability, younger age at sexual debut and living in formal urban rather than formal rural areas. CONCLUSIONS: The data presented in this paper reinforces the importance of MSP as a risk factor for HIV and outline factors that should strongly be considered in strengthening condom use promotion and of partner reduction programs messaging in South Africa.

Equity in maternal health in South Africa: analysis of health service access and health status in a national household survey.

BACKGROUND: South Africa is increasingly focused on reducing maternal mortality. Documenting variation in access to maternal health services across one of the most inequitable nations could assist in re-direction of resources. METHODS: Analysis draws on a population-based household survey that used multistage-stratified sampling. Women, who in the past two years were pregnant (1113) or had a child (1304), completed questionnaires and HIV testing. Distribution of access to maternal health services and health status across socio-economic, education and other population groups was assessed using weighted data. FINDINGS: Poorest women had near universal antenatal care coverage (ANC), but only 39.6% attended before 20 weeks gestation; this figure was 2.7-fold higher in the wealthiest quartile (95%CI adjusted odds ratio = 1.2-6.1). Women in rural-formal areas had lowest ANC coverage (89.7%), percentage completing four ANC visits (79.7%) and only 84.0% were offered HIV testing. Testing levels were highest among the poorest quartile (90.1% in past two years), but 10% of women above 40 or with low education had never tested. Skilled birth attendant coverage (overall 95.3%) was lowest in the poorest quartile (91.4%) and rural formal areas (85.6%). Around two thirds of the wealthiest quartile, of white and of formally-employed women had a doctor at childbirth, 11-fold higher than the poorest quartile. Overall, only 44.4% of pregnancies were planned, 31.7% of HIV-infected women and 68.1% of the wealthiest quartile. Self-reported health status also declined considerably with each drop in quartile, education level or age group. CONCLUSIONS: Aside from early ANC attendance and deficiencies in care in rural-formal areas, inequalities in utilisation of services were mostly small, with some measures even highest among the poorest. Considerably larger differences were noted in maternal health status across population groups. This may reflect differences between these groups in quality of care received, HIV infection and in social determinants of health.

Screening and brief interventions for hazardous and harmful alcohol use among patients with active tuberculosis attending primary public care clinics in South Africa: results from a cluster randomized controlled trial.

BACKGROUND: In 2008 the World Health Organization (WHO) reported that South Africa had the highest tuberculosis (TB) incidence in the world. This high incidence rate is linked to a number of factors, including HIV co-infection and alcohol use disorders. The diagnosis and treatment package for TB and HIV co-infection is relatively well established in South Africa. However, because alcohol use disorders may present more insidiously, making it difficult to diagnose, those patients with active TB and misusing alcohol are not easily cured from TB. With this in mind, the primary purpose of this cluster randomized controlled trial was to provide screening for alcohol misuse and to test the effectiveness of brief interventions in reducing alcohol intake in those patients with active TB found to be misusing alcohol in primary public health care clinics in three districts in South Africa. METHODS: Within each of the three provinces targeted, one district with the highest TB burden was selected. Furthermore, 14 primary health care facilities with the highest TB caseload in each district were selected. In each district, 7 of the 14 (50%) clinics were randomly assigned to a control arm and another 7 of the 14 (50%) clinics assigned to intervention arm. At the clinic level systematic sampling was used to recruit newly diagnosed and retreatment TB patients. Those consenting were screened for alcohol misuse using the Alcohol Use Disorder Identification Test (AUDIT). Patients who screened positive for alcohol misuse over a 6-month period were given either a brief intervention based on the Information-Motivation-Behavioural Skills (IMB) Model or an alcohol use health education leaflet. RESULTS: Of the 4882 tuberculosis patients screened for alcohol and agreed to participate in the trial, 1196 (24.6%) tested positive for the AUDIT. Among the 853 (71%) patients who also attended the 6-month follow-up session, the frequency of positive screening results at baseline/follow-up were 100/21.2% for the AUDIT (P < 0.001) for the control group and 100/16.8% (P < 0.001) for the intervention group. The intervention effect on the AUDIT score was statistically not significant. The intervention effect was also not significant for hazardous or harmful drinkers and alcohol dependent drinkers ( AUDIT: 7-40), alcohol dependent drinkers and heavy episodic drinking, while the control group effect was significant for hazardous drinkers ( AUDIT: 7-19) (P = 0.035). CONCLUSION: The results suggest that alcohol screening and the provision of a health education leaflet on sensible drinking performed at the beginning of anti-tuberculosis treatment in public primary care settings may be effective in reducing alcohol consumption. TRIAL REGISTRATIONS: PACTR201105000297151.

Gender and poverty in South Africa in the era of HIV/AIDS: a quantitative study.

BACKGROUND: Recent research identifies gender inequality as a driver of the HIV/AIDS epidemic. The feminization of poverty is also increasingly apparent, as is the disproportionate vulnerability of members of female-headed households. We sought to examine the relationships among sex, gender, age, HIV status, and socioeconomic characteristics, focusing on heads and nonheads of households. METHODS: We interviewed 6,338 men and 10,057 women. RESULTS: Significantly more males (51.4%) than females (34.8%) indicated that they were heads of households (p < 0.001). Female heads of households were significantly more likely to be infected with HIV than their male counterparts (17.9% vs. 13.1%). Among 15-24-year-old males, those who are often without cash are more likely to be infected with HIV than those who are never without cash (OR = 3.33, 95% CI 1.17-9.49). Similar results were observed among females, who sometimes had no cash (OR = 1.86, 95% CI 1.22-2.82), and among adults aged >or=25 years. Results confirmed that age and gender are related to HIV infection in South Africa and that poverty is a social determinant for HIV infection across all age groups. However, sex is a determinant only among the younger age groups. Young female heads of household are more likely to be poor and are more likely to be HIV positive. CONCLUSIONS: The results indicate that the HIV/AIDS epidemic in South Africa is characterized by gender inequalities. Young women are more likely to be HIV infected, especially heads of households. Young women are also more likely to live in poverty, although this study cannot establish the directionality of a causative relationship between poverty and risk of HIV. Greater attention must be paid to young women, especially those who head households, in terms of treatment, prevention, and poverty alleviation.

Epidemiology of health and vulnerability among children orphaned and made vulnerable by HIV/AIDS in sub-Saharan Africa.

The HIV/AIDS epidemic in sub-Saharan Africa has already orphaned a generation of children, and it is projected that by 2010, 18 million African children under the age of 18 are likely to be orphans from this single cause (UNICEF, 2005, The state of the Worlds Children: Childhood under threat. New York: UNICEF). Results from a Kellogg funded OVC project (Skinner et al., 2004, Definition of orphaned and vulnerable children. Cape Town: HSRC) supported the construct that the loss of either or both parents would indicate a situation of likely vulnerability of children. A key problem in the literature on the impact of orphanhood on the well-being of children, families and communities, is that the focus of assertions and predictions is often on the negative impact on 'AIDS orphans', or households. There are hardly any studies that compare the experiences of orphans with non-orphans. This paper thus attempts to fill that gap. It uses epidemiological data to explore the epidemiology of health and vulnerability of children within the context of AIDS in sub-Saharan Africa. Because of data limitations, only the following aspects are examined: (i) orphan status; (ii) household structure (in particular, grandparent headedness and female-headedness); (iii) illness of parents; (iv) poverty; and (v) access to services, especially schooling, health, social services. While recognizing the limitations of the analysis, data presented in this paper indicates that orphans in sub-Saharan Africa are more vulnerable than non-orphans. The authors conclude with some suggestions for policy makers and programme implementers, highlighting the importance of focusing on interventions that will have maximum impact on the health and well-being of children.