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Vaccine Utilization and Timing of Administration in Pregnant Women A South African Perspective
No full textChemical analysis of low grade gold from mine tailings after size fractionation and acid digestion using reverse aqua regia
No full textThe growing interest in reprocessing mine tailings for gold recovery requires a suitable quantification
method that is accurate, rapid, and not harsh to the environment. Acid digestion is often used to
determination of gold; however, it often faces the challenge of incomplete digestion due to the
presence of minerals such as quartz, and homogeneity is compromised due to small sample masses,
which can result in low bias. This study investigated a shorter acid digestion method employing reverse
aqua regia, both in the presence and absence of hydrofluoric acid. Before digestion, the sample was
subjected to gold depot analysis, which showed that 78% was free-milling gold and that only 0.8%
was associated with pyrite, increasing the chances of accurate quantifications. Furthermore, the size
screening test showed that most of the gold could be recovered on the −38 μm screen. This proposed
method provided good linearity (5–100 µg. L−1) and low detection limits (0.139–0.183 µg.kg−1). The
concentrations obtained by the acid digestion was 0.258 g.t−1 with the recoveries ranging between
80% and 82%, which fit the criteria set. The method also worked well for the certified reference
materials (CRM), AMIS 610 (accurate value=0.068 g.t−1) and AMIS 646 (accurate value=0.166 g.t−1),
which are of a similar matrix and are also lower in grade compared to the sample. The method was also
evaluated for uncertainty (±value) using the bottom-up approach, and the expanded uncertainty (k=2)
was reported to be 0.258±0.092 g.t−1, which was comparable to that offered by the fire assay with the
ICP‒OES finish, which was 0.28±0.10 g.t−1. This implies that the acid digestion method is suitable for
quantifying gold from mine tailings without large uncertainties.National Research Foundation (South Africa).Analytical Chemistry Division at Mintek.PM202
Prevalence incidence and risk factors for rugbyrelated injuries A survey of the Safari Sevens tournament
No full textMental heAlth and wellbeing in rUgby pLayers MAUL study an online survey of diverse cohorts of rugby union players internationally
No full text
Uptake and Persistence of Safer Conception Strategies Among South African Women Planning for Pregnancy
No full textPrevalence of depressive symptoms in adolescents living with HIV in Johannesburg South Africa
No full textGroup-based trajectory modeling to describe the geographical distribution of tuberculosis notifcations
No full textBackground Tuberculosis (TB) is a major public health problem, and understanding the geographic distribution
of the disease is critical in planning and evaluating intervention strategies. This manuscript illustrates the application
of Group-Based Trajectory Modeling (GBTM), a statistical method that analyzes the evolution of an outcome over time
to identify groups with similar trajectories. Specifically, we apply GBTM to identify the evolution of the number of TB
notifications over time across various geographic locations, aiming to identify groups of locations with similar trajectories. Locations sharing the same trajectory may be considered geographic TB clusters, indicating areas with similar
TB notifications. We used data abstracted from clinic records in Limpopo province, South Africa, treating the clinics
as a proxy for the spatial location of their respective catchment areas.
Methods Data for this analysis were obtained as part of a cluster-randomized trial involving 56 clinics to evaluate two
active TB patient-funding strategies in South Africa. We utilized GBTM to identify groups of clinics with similar trajectories of the number of TB patients.
Results We identified three trajectory groups: Groups 1, comprising 57.8% of clinics; Group 2, 33.9%; and Group
3, 8.3%. These groups accounted for 30.8%, 44.4%, and 24.8% of total TB-diagnosed patients, respectively. The estimated mean number of TB-diagnosed patients was highest in trajectory group 3 followed by trajectory group 2
across the 12 months, with no overlap in the corresponding 95% confidence intervals. The estimated mean number of TB-diagnosed patients over time was fairly constant for trajectory groups 1 and 2 with exponentiated slopes
of 0.979 (95% CI: 0.950, 1.004) and 1.004 (95% CI: 0.977, 1.044), respectively. In contrast, there was a statistically
significant 3.8% decrease in the number of TB patients per month for trajectory group 3 with an exponentiated slope
of 0.962 (95% CI: 0.901, 0.985) per month.
Conclusions GBTM is a powerful tool for identifying geographic clusters of varying levels of TB notification when longitudinal data on the number of TB diagnoses are available. This analysis can inform the planning and evaluation
of intervention strategies.National Institutes of Health/National Institute of Allergy and Infectious Disease.Johns Hopkins University Center for AIDS
Research.PM202
