This community situational analysis determined factors impacting the utilization of maternal health services in South Africa. Quantitative and qualitative research methods were used, including semistructured household interviews, case studies of women with no antenatal care and/or home birth, and verbal/social autopsies of maternal and infant deaths, conducted in three diverse sites across the country. Data analysis used quantitative statistics for the semistructured interviews and a qualitative thematic content approach for the case studies and verbal/social autopsies. Each component was analyzed separately and then triangulated. The following themes emerged: 1) transport and distance to care were the biggest problems, particularly in rural areas; 2) providers' communication with families was very poor; 3) health-seeking behavior was better than anticipated; 4) treatment by health providers and quality of care showed mixed results; 5) HIV/AIDS is a major issue; however, basic maternity and neonatal service quality cannot be overlooked; and 6) families and communities are an untapped resource for improving maternal and neonatal health. Implications for maternal and infant health care in developing countries are discussed, with a particular focus on barriers to utilization and involvement of communities and families in maternity care.

Background. South Africa (SA) is experiencing an epidemiological transition as a result of sociodemographic and lifestyle changes. This process is leading to an increase in non-communicable diseases, which in turn may result in an upswing of stroke cases. Stroke is among the top 10 leading causes of disability in SA, and accounts for ~25 000 deaths annually and 95 000 years lived with disability (YLD). This huge burden of stroke hampers socioeconomic development as a result of YLD. Objectives. To investigate the seasonality and trend of stroke cases in SA, and determine the risk factors associated with stroke. Methods. Using recent hospital-based data (January 2014-December 2017 inclusive) from SA private and public hospitals (33% private and 67% public), a sample of 14 645 suspected stroke cases was drawn. Associations between suspected stroke cases and potential predictors were assessed using χ 2 tests and bivariate analysis. Time series analysis tools for trend and seasonality components included both time domain and frequency domain techniques. A Poisson generalised linear model was used, as there was no over-dispersion inherent in the data. Multiple logistic regression analysis was used to assess the effect of several predictors on stroke cases. Results. Of the 14 645 suspected cases of stroke, 51.5% were confirmed. Seasonality analysis gave an approximate seasonal change of 120 cases, the highest seasonal peak occurring in midwinter and the lowest dip in midsummer. Both upward trend and seasonality parameters were found to be statistically significant. Predictors significantly associated with an increased likelihood of stroke were heart problems (odds ratio (OR) 8.86; 95% confidence interval (CI) 8.23-9.55; p<0.0001), diabetes (OR 14.53; 95% CI 13.36-15.79; p<0.0001), female sex (OR 18.23; 95% CI 16.75-19.85; p<0.0001), age 59-77 years (OR 1.37; 95% CI 1.24-1.50; p<0.0001) and 78-98 years (OR 1.25; 95% CI 1.16-1.35; p<0.0001) and white ethnic group (OR 2.00; 95% CI 1.86-2.15; p<0.0001), compared with the respective reference groups. The prevalence ratios of stroke cases as measured by Poisson regression were in agreement with logistic regression results. Conclusions. The increasing trend of stroke in SA should be arrested urgently, taking into account both the associated risk factors and seasonality.

Background In South Africa (SA), stroke is the second highest cause of mortality and disability. Apart from being the main killer and cause of disability, stroke is an expensive disease to live with. Stroke costs include death and medical costs. Little is known about the stroke burden, particularly the stroke direct costs in SA. Identification of stroke costs predictors using appropriate statistical methods can help formulate appropriate health programs and policies aimed at reducing the stroke burden. Analysis of stroke costs have in the main, concentrated on mean regression, yet modelling with quantile regression (QR) is more appropriate than using mean regression. This is because the QR provides flexibility to analyse the stroke costs predictors corresponding to quantiles of interest. This study aims to estimate stroke direct costs, identify and quantify its predictors through QR analysis. Methods Hospital-based data from 35,730 stroke cases were retrieved from selected private and public hospitals between January 2014 and December 2018. The model used, QR provides richer information about the predictors on costs. The prevalence-based approach was used to estimate the total stroke costs. Thus, stroke direct costs were estimated by taking into account the costs of all stroke patients admitted during the study period. QR analysis was used to assess the effect of each predictor on stroke costs distribution. Quantiles of stroke direct costs, with a focus on predictors, were modelled and the impact of predictors determined. QR plots of slopes were developed to visually examine the impact of the predictors across selected quantiles. Results Of the 35,730 stroke cases, 22,183 were diabetic. The estimated total direct costs over five years were R7.3 trillion, with R2.6 billion from inpatient care. The economic stroke burden was found to increase in people with hypertension, heart problems, and diabetes. The age group 55–75 years had a bigger effect on costs distribution at the lower than upper quantiles. Conclusions The identified predictors can be used to raise awareness on modifiable predictors and promote campaigns for healthy dietary choices. Modelling costs predictors using multivariate QR models could be beneficial for addressing the stroke burden in SA.

BackgroundTuberculin skin tests (TSTs) are long-established screening methods for tuberculosis (TB). We aimed to compare agreement between the intradermal Mantoux and multipuncture percutaneous Tine methods and to quantify risk factors for a positive test result.Methodology/Principal Findings1512 South African children younger than 5 years of age who were investigated for tuberculosis (TB) during a Bacille Calmette Guerin (BCG) trial were included in this analysis. Children underwent both Mantoux and Tine tests. A positive test was defined as Mantoux ≥15 mm or Tine ≥ Grade 3 for the binary comparison. Agreement was evaluated using kappa (binary) and weighted kappa (hierarchical). Multivariate regression models identified independent risk factors for TST positivity. The Mantoux test was positive in 430 children (28.4%) and the Tine test in 496 children (32.8%, p<0.0001), with observed binary agreement 87.3% (kappa 0.70) and hierarchical agreement 85.0% (weighted kappa 0.66). Among 173 children culture-positive for Mycobacterium tuberculosis, Mantoux was positive in 49.1% and Tine in 54.9%, p<0.0001 (kappa 0.70). Evidence of digit preference was noted for Mantoux readings at 5 mm threshold intervals. After adjustment for confounders, a positive culture, suggestive chest radiograph, and proximity of TB contact were risk factors for a positive test using both TST methods. There were no independent associations between ethnicity, gender, age, or over-crowding, and TST result.Conclusions/SignificanceThe Tine test demonstrated a higher positive test rate than the Mantoux, with substantial agreement between TST methods among young BCG-vaccinated children. TB disease and exposure factors, but not demographic variables, were independent risk factors for a positive result using either test method. These findings suggest that the Tine might be a useful screening tool for childhood TB in resource-limited countries.