South African Data Research Articles

Longevity swaps for longevity risk management in life insurance products

PurposeThe life insurance industry has been exposed to high levels of longevity risk born from the mismatch between realized mortality trends and anticipated forecast. Annuity providers are exposed to extended periods of annuity payments. There are no immediate instruments in the market to counter the risk directly. This paper aims to develop appropriate instruments for hedging longevity risk and providing an insight on how existing products can be tailor-made to effectively immunize portfolios consisting of life insurance using a cointegration vector error correction model with regime-switching (RS-VECM), which enables both short-term fluctuations, through the autoregressive structure [AR(1)] and long-run equilibria using a cointegration relationship. The authors also develop synthetic products that can be used to effectively hedge longevity risk faced by life insurance and annuity providers who actively hold portfolios of life insurance products. Models are derived using South African data. The authors also derive closed-form expressions for hedge ratios associated with synthetic products written on life insurance contracts as this will provide a natural way of immunizing the associated portfolios. The authors further show how to address the current liquidity challenges in the longevity market by devising longevity swaps and develop pricing and hedging algorithms for longevity-linked securities. The use of a cointergrating relationship improves the model fitting process, as all the VECMs and RS-VECMs yield greater criteria values than their vector autoregressive model (VAR) and regime-switching vector autoregressive model (RS-VAR) counterpart’s, even though there are accruing parameters involved.Design/methodology/approachThe market model adopted from Ngai and Sherris (2011) is a cointegration RS-VECM for this enables both short-term fluctuations, through the AR(1) and long-run equilibria using a cointegration relationship (Johansen, 1988, 1995a, 1995b), with a heteroskedasticity through the use of regime-switching. The RS-VECM is seen to have the best fit for Australian data under various model selection criteria by Sherris and Zhang (2009). Harris (1997) (Sajjad et al., 2008) also fits a regime-switching VAR model using Australian (UK and US) data to four key macroeconomic variables (market stock indices), showing that regime-switching is a significant improvement over autoregressive conditional heteroscedasticity (ARCH) and generalised autoregressive conditional heteroscedasticity (GARCH) processes in the account for volatility, evidence similar to that of Sherris and Zhang (2009) in the case of Exponential Regressive Conditional Heteroscedasticity (ERCH). Ngai and Sherris (2011) and Sherris and Zhang (2009) also fit a VAR model to Australian data with simultaneous regime-switching across many economic and financial series.FindingsThe authors develop a longevity swap using nighttime data instead of usual income measures as it yields statistically accurate results. The authors also develop longevity derivatives and annuities including variable annuities with guaranteed lifetime withdrawal benefit (GLWB) and inflation-indexed annuities. Improved market and mortality models are developed and estimated using South African data to model the underlying risks. Macroeconomic variables dependence is modeled using a cointegrating VECM as used in Ngai and Sherris (2011), which enables both short-run dependence and long-run equilibrium. Longevity swaps provide protection against longevity risk and benefit the most from hedging longevity risk. Longevity bonds are also effective as a hedging instrument in life annuities. The cost of hedging, as reflected in the price of longevity risk, has a statistically significant effect on the effectiveness of hedging options.Research limitations/implicationsThis study relied on secondary data partly reported by independent institutions and the government, which may be biased because of smoothening, interpolation or extrapolation processes.Practical implicationsAn examination of South Africa’s mortality based on industry experience in comparison to population mortality would demand confirmation of the analysis in this paper based on Belgian data as well as other less developed economies. This study shows that to provide inflation-indexed life annuities, there is a need for an active market for hedging inflation in South Africa. This would demand the South African Government through the help of Actuarial Society of South Africa (ASSA) to issue inflation-indexed securities which will help annuities and insurance providers immunize their portfolios from longevity risk.Social implicationsIn South Africa, there is an infant market for inflation hedging and no market for longevity swaps. The effect of not being able to hedge inflation is guaranteed, and longevity swaps in annuity products is revealed to be useful and significant, particularly using developing or emerging economies as a laboratory. This study has shown that government issuance or allowing issuance, of longevity swaps, can enable insurers to manage longevity risk. If the South African Government, through ASSA, is to develop a projected mortality reference index for South Africa, this would allow the development of mortality-linked securities and longevity swaps which ultimately maximize the social welfare of life assurance policy holders.Originality/valueThe paper proposes longevity swaps and static hedging because they are simple, less costly and practical with feasible applications to the South African market, an economy of over 50 million people. As the market for MLS develops further, dynamic hedging should become possible.

Non-capital calibration of bureau scorecards

Application scorecards play a critical part in determining the creditworthiness of applicants for acquisition purposes. However, the level of bad rate in a downturn period and upturn period although monotonic are different across the scores due to procyclicality (which arises from the fluctuation of financial characteristics around a trend in an economic cycle). The procyclicality effect from an acquisition perspective on a bureau scorecard is investigated with emphasis on South African retail banking data, and performance between downturn and upturn periods is compared. This paper contributes by proposing a methodology which incorporates a Bayesian calibration approach to adjust to future expected bad rates: the comparison indicates that calibration is essential to account for procyclicality.

Steep Declines in Pediatric AIDS Mortality in South Africa, Despite Poor Progress Toward Pediatric Diagnosis and Treatment Targets.

Few attempts have been made to monitor progress toward HIV diagnosis and antiretroviral treatment (ART) coverage targets in children, and the impact that ART and prevention of mother-to-child transmission (PMTCT) programs have had on pediatric HIV incidence and mortality. A multiparameter evidence synthesis approach was adopted to integrate South African pediatric HIV data sources. A previously developed model of HIV in South Africa was calibrated to household survey HIV prevalence data, routine antibody testing data, data on numbers and ages of children on ART, vital registration data and data on HIV diagnosis at death. The impact of ART and PMTCT was estimated by comparing validated model outputs against model predictions of the trends that would have been expected in the absence of ART and PMTCT. By mid-2018, the model estimated that 75.2% (95% CI: 73.9%-76.8%) of HIV-positive children were diagnosed, substantially lower than the corresponding estimates in HIV-positive adults (91.0%). ART coverage in children in 2018 (51.2%, 95% CI: 49.4%-52.7%) was also lower than that in adults (62.0%). In 2017-2018, the numbers of new cases of mother-to-child transmission and pediatric AIDS deaths were reduced by 84% and 94%, respectively, relative to what would have been expected in the absence of interventions, but reductions in mortality were driven largely by PMTCT. Although levels of AIDS mortality in children have declined dramatically in South Africa, this has mostly been due to successful PMTCT programs, and progress toward the 90-90-90 targets appears relatively poor when compared with that in adults.

Circumcised men's perceptions, understanding and experiences of voluntary medical male circumcision in KwaZulu-Natal, South Africa.

BackgroundKwaZulu-Natal, South Africa, has rolled out voluntary medical male circumcision (VMMC) in response to recommendations that regions with a high human immunodeficiency virus (HIV) prevalence adopt VMMC as an additional HIV prevention strategy. There is a paucity of South African data on the motivators, barriers and experiences of adult male candidates regarding VMMC. This study was conducted to analyse circumcised men’s perceptions, understanding and experiences of VMMC in KwaZulu-Natal, South Africa.MethodsA qualitative phenomenographic design was used. Ethical clearance was obtained from the Biomedical Research Ethics Committee of the University of KwaZulu-Natal (BE 627/18). Data were collected from 12 circumcised male candidates. Individual interviews were conducted and recorded by using an audiotape. Data were transcribed verbatim and analysed manually.ResultsParticipants’ perceptions regarding VMMC are health related and appear to be the motivators for the uptake of medical circumcision. Circumcised men in this study appeared to misunderstand VMMC in terms of healing and performance time and the nature of the procedure. Negative experiences in terms of quality of care received were reported.ConclusionThe study findings imply that practice interventions to promote demand generation for VMMC in KwaZulu-Natal, South Africa, should incorporate the perceptions and experiences of male candidates regarding the procedure. Tailored messaging to address misunderstanding related to the nature of VMMC should also be provided. Regular in-service training on standardised VMMC implementation practices should be provided to ensure the delivery of optimum quality VMMC services.

Determinants of Under-five Mortality in South Africa: Results from a Cross-Sectional Demographic and Health Survey

Under-five mortality remains a public health challenge in South Africa and other developing countries where children are likely to die before reaching five years. This paper aimed to identify factors associated with under-five mortality in South Africa taking into account clustering using the 1998 South African Demographic and Health Survey data. Survival analysis techniques were used to understand under-five mortality and its determinants. Frailty models incorporating family and community frailty effects were implemented. The results revealed that preceding birth interval, birth type, breastfeeding and dwelling unit type were significant determinants of under-five mortality. The findings further confirmed that children belonging to the same family and children belonging to the same community shared certain unobserved characteristics that put them at risk of death.

South African abortion attitudes from 2007-2016: the roles of religiosity and attitudes toward sexuality and gender equality

ABSTRACT Abortion is legal in South Africa, but negative abortion attitudes remain common and are poorly understood. We used nationally representative South African Social Attitudes Survey data to analyze abortion attitudes in the case of fetal anomaly and in the case of poverty from 2007 to 2016 (n = 20,711; ages = 16+). We measured correlations between abortion attitudes and these important predictors: religiosity, attitudes about premarital sex, attitudes about preferential hiring and promotion of women, and attitudes toward family gender roles. Abortion acceptability for poverty increased over time (b = 0.05, p < .001), but not for fetal anomaly (b = −0.008, p = .284). Highly religious South Africans reported lower abortion acceptability in both cases (Odds Ratio (OR)anomaly = 0.85, p = .015; ORpoverty = 0.84, p = .02). Premarital sex acceptability strongly and positively predicted abortion acceptability (ORanomaly = 2.63, p < .001; ORpoverty = 2.46, p < .001). Attitudes about preferential hiring and promotion of women were not associated with abortion attitudes, but favorable attitudes about working mothers were positively associated with abortion acceptability for fetal anomaly ((ORanomaly = 1.09, p = .01; ORpoverty = 1.02, p = .641)). Results suggest negative abortion attitudes remain common in South Africa and are closely tied to religiosity, traditional ideologies about sexuality, and gender role expectations about motherhood.

A population model for the 2017/18 listeriosis outbreak in South Africa

We introduce a compartmental model of ordinary differential equations for the population dynamics of listeriosis, and we derive a model for analysing a listeriosis outbreak. The model explicitly accommodates neonatal infections. Similarly as is common in cholera modeling, we include a compartment to represent the reservoir of bacteria. We also include a compartment to represent the incubation phase. For the 2017/18 listeriosis outbreak that happened in South Africa, we calculate the time pattern and intensity of the force of infection, and we determine numerical values for some of the parameters in the model. The model is calibrated using South African data, together with existing data in the open literature not necessarily from South Africa. We make projections on the future outlook of the epidemiology of the disease and the possibility of eradication.

Tax-motivated transfer mispricing in South Africa: Direct evidence using transaction data

This paper provides the first direct systematic evidence of profit shifting through transfer mispricing in a developing country. Using South African transaction-level customs data, I directly test for transfer price deviations from arm's-length pricing. I find that multinational firms in South Africa manipulate transfer prices in order to shift taxable profits to low-tax countries. The estimated tax loss relating to imported goods alone is 0.5% of corporate tax payments. My estimates do not support the common belief that transfer mispricing in South Africa is more severe than in advanced economies. I find that an OECD-recommended reform had no long-term impact on transfer mispricing but argue that the method used in this paper provides a cost-efficient way to curb transfer mispricing.

Macroeconomic implications of uncertainty in South Africa

Aim: This article explores the extent to which economic policy uncertainty (EPU) influences selected macroeconomic variables in South Africa (SA). Methods: To this end, I construct a constant parameter vector autoregressive (VAR) model and a time-varying parameter (TVP) VAR model, where the latter model evaluates if the impact of uncertainty on the macroeconomic variables has changed over time. Setting: The models are estimated using quarterly South African data over the period 1990 to 2015, which include industrial production growth, consumer price inflation, 10-year government bond yield, real effective exchange rate, and economic policy uncertainty. Cholesky ordering of the variables are imposed to recover the orthogonal shocks. Results: The results of the constant parameter VAR model suggest that an unanticipated positive shock to the uncertainty index results in a decline in industrial production and real effective exchange rate, while fostering an increase in the general price level and 10-year government bond yield. Time-varying impulse responses show that the impact of uncertainty shocks on the selected macroeconomic variables has declined systematically over time. This is perhaps intuitive as the new unanticipated information is gradually picked up by media over time and incorporated into rational agents’ decision-making. Conclusion: The transmission of a positive uncertainty shock to the real economy has time-varying implications.

Democratisation in the South African parliamentary Hansard? A study of change in modal auxiliaries

Parliaments are a primary site where political and social democratisation can be seen in action, making parliamentary discourse, as represented in the Hansard of Commonwealth countries, a particularly relevant source of linguistic evidence for the effects of democratisation on language change. South Africa offers an exemplary case of social change which may influence language use. This paper first outlines the historical trajectory of democratisation in the South African parliament. It subsequently sets out to explore patterns of mutual influence between these socio-political changes and changes in the use of English modal auxiliaries of obligation and necessity in a specialised corpus consisting of the South African parliamentary Hansard, sampled at 10-year intervals from 1900 to 2015. The South African data are compared with data from comparable diachronic corpora of the Australian and British Hansard. We interpret our findings in the frame of possible linguistic democratisation aligned with social and political democratisation. Changes in the frequencies of must, should, HAVE to, (HAVE) got to, need and NEED to across the three varieties are reported first, before turning to the semantics of the modals must, should, HAVE to and NEED to. Our findings demonstrate how ongoing language change is receptive to local contexts of use. The data from the South African, Australian and British Hansards show signs of changes similar to the overall changes observed across native varieties of English, such as the gradual decline in the frequency of all modals together, and the increase in frequency of quasi-modals. However, where the British and Australian Hansards match the global trends more closely, the South African data show more signs of deviations from these patterns, which appear to be closely associated with not only demographic changes in parliament, but also the dynamics of conciliation in the broader framework of political democratisation and new patterns of political contestation.

Analysis of Extreme Peak Loads Using Point Processes: An Application Using South African Data

Extreme value modelling of peak load process is critical to the reliable specification of power generation, distribution and maintenance purposes during both peak and off-peak periods. In this study, a frequency assessment of extreme peak electricity demand for the four seasons of the year using South African data for the period, January 1997 to December 2013 is carried out. A point process approach from extreme value theory is proposed as an ingenious extreme value theory approach. The data are made stationary by using a time-varying threshold which has a positive shift factor. The non-linear detrended datasets are then grouped into summer, spring, winter and autumn according to the calendar dates in the Southern Hemisphere. The datasets were declustered to keep the series relatively independent using Ferro and Segers automatic declustering method. A stationary point process model is then fitted to each of the cluster maxima. The modelling framework, which is easily extensible to other peak load parameters, assumes that peak power follows a Poisson point process. The parameters of the developed model are estimated using the maximum likelihood method. Empirical results show that daily peak electricity demand could be experienced approximately 27, 16, 7 and 15 days per year in winter, spring, summer and autumn, respectively. The modelling approach could assist system operators of utility companies in scheduling maintenance of generating units including long term planning.

Forecasting Hourly Global Horizontal Solar Irradiance in South Africa Using Machine Learning Models

Solar irradiance forecasting is essential in renewable energy grids amongst others for back-up programming, operational planning, and short-term power purchases. This study focuses on forecasting hourly solar irradiance using data obtained from the Southern African Universities Radiometric Network at the University of Pretoria radiometric station. The study compares the predictive performance of long short-term memory (LSTM) networks, support vector regression and feed forward neural networks (FFNN) models for forecasting short-term solar irradiance. While all the models outperform principal component regression model, a benchmark model in this study, the FFNN yields the lowest mean absolute error and root mean square error on the testing set. Empirical results show that the FFNN model produces the most accurate forecasts based on mean absolute error and root mean square error. Forecast combination of machine learning models' forecasts is done using convex combination and quantile regression averaging (QRA). The predictive performance we found is statistically significant on the Diebold Mariano and Giacomini-White tests. Based on all the forecast accuracy measures used in this study including the statistical tests, QRA is found to be the best forecast combination method. QRA was also the best forecasting model compared with the stand-alone machine learning models. The median method for combining interval limits gives the best results on prediction interval widths analysis. This is the first application of LSTM on South African and African solar irradiance data to the best of our knowledge. This study has shown that providing adequate and detailed evaluation metrics, including statistical tests in forecasting gives more insight into the developed forecasting models.

Optimized Lockdown Strategies for Curbing the Spread of COVID-19: A South African Case Study.

To curb the spread of COVID-19, many governments around the world have implemented tiered lockdowns with varying degrees of stringency. Lockdown levels are typically increased when the disease spreads and reduced when the disease abates. A predictive control approach is used to develop optimized lockdown strategies for curbing the spread of COVID-19. The strategies are then applied to South African data. The South African case is of interest as the South African government has defined five distinct levels of lockdown, which serves as a discrete control input. An epidemiological model for the spread of COVID-19 in South Africa was previously developed, and is used in conjunction with a hybrid model predictive controller to optimize lockdown management under different policy scenarios. Scenarios considered include how to flatten the curve to a level that the healthcare system can cope with, how to balance lives and livelihoods, and what impact the compliance of the population to the lockdown measures has on the spread of COVID-19. The main purpose of this article is to show what the optimal lockdown level should be given the policy that is in place, as determined by the closed-loop feedback controller.

The burden of depression and anxiety among medical students in South Africa: A cross-sectional survey at the University of Cape Town.

Depressive and anxiety disorders occur at very high rates among medical students. For instance, an international review and meta-analysis estimated the overall pooled crude prevalence of depression or depressive symptoms at 27.2%. However, South African (SA) data are very limited. To determine rates of depression and anxiety among medical students and to examine the associations with various sociodemographic variables (biological sex, gender identity, household income, ethnicity, and clinical v. pre-clinical students). We also examined whether the 'mini-semester' of 2017 resulting from the 2016 'Fees Must Fall' student protests was associated with increased depression/anxiety. The study was a cross-sectional electronic survey conducted in the Faculty of Health Sciences, University of Cape Town, using an anonymous, self-administered online questionnaire. The questionnaire included basic sociodemographic questions, the Patient Health Questionnaire-9 and the Hospital Anxiety and Depression Scale. The sample consisted of 473 medical students, 333 (70.4%) female and 140 (29.6%) male. Based on ethnic self-identification, 165 (35.6%) were black, 144 (31.1%) white, 88 (19%) coloured, 52 (11.2%) Indian and 8 (1.7%) Asian. There were 239 pre-clinical students (50.5%) and 234 clinical students (49.5%). Of the sample, 36.4% were above the cut-off for major depressive disorder and 45.9% for anxiety disorder. Reported rates of disorders diagnosed by a health professional were 25.0% for depressive disorder and 20.5% for anxiety disorder, and 28.1% of all students were receiving psychotropic medication. Female sex was associated with both depression (prevalence ratio (PR) 3.7; p&lt;0.001) and anxiety diagnoses (PR 4.7; p&lt;0.001). None of the other sociodemographic characteristics showed significant associations. Interestingly, students who undertook the 2017 mini-semester showed an increased rate of depression (PR 2.1; p&lt;0.05) and anxiety diagnoses (PR 2.1; p&lt;0.05). Nearly one in four students reported depression/anxiety diagnoses and were on psychotropic medication, significantly more than age-based expectations. Even more screened positive for risk of depression/anxiety. Our findings indicate that medical students, particularly females, are at a significantly increased risk of depression and anxiety disorders. Results suggest that the 2016 student protests may have had a direct impact on the mental state of students. Multidisciplinary efforts should be targeted at initiatives to strengthen mental wellbeing and institutional culture around mental health. These efforts may help build resilience in the next generation of health professionals in SA ahead of work in an overburdened health and health education system.

Measuring wealth inequality in South Africa: An agenda

ABSTRACTUnderstanding wealth inequality has unique significance in South Africa. The co-existence of extreme poverty and extreme wealth is starkly visible. Apartheid-era inequality has persisted despite more than 20 years of democracy. Much of the recent research focus on inequality has been on inequality of income and of opportunities, especially quantitatively. With the recent project to release South African tax administrative data for research, this paper hopes to show how use of the tax administrative data can contribute to developing a refreshed quantitative analysis of wealth inequality, especially in estimating the top shares of the wealth distribution, and so contribute to the existing literature on wealth inequality in South Africa. The first section will explore why studying wealth inequality is of fundamental importance. The second section will review international data and methods used to research wealth inequality, before laying out suggested approach to doing such studies in South Africa.

Growth and Inequality: The South African Case in International Context—The Central Role of the Labor Market

Abstract The relationship between economic growth and inequality has not been settled. Using South African time series data, the core finding of this article is that growth and inequality codetermine one another: growth lowers inequality, and falling inequality in turn serves to stimulate growth. There are additional statistically and substantively significant drivers of inequality in South Africa. Labor absorption (job creation) is the most important of these. The opening of the South African economy post 1990, the lowering of credit rationing in the economy in the 1990s, and the fiscus all prove to exert important influence on the net inequality outcome also. The findings imply that the strongest policy levers suitable for raising average welfare and lowering inequality are policies designed to stimulate growth, increase labor absorption, extend credit to entrepreneurs, ensure household credit is broad-based, and ameliorate the disruptive impacts of globalization on labor markets.

Attack the Data: Agency, Power, and Technopolitics in South African Data Activism

This article deploys a discursive–material analytical framework to trace how perceptions of data power are constructed in urban activist circles against data’s capacity to advance grassroots political goals. By framing South African data activism practices as a form of technopolitics—a concept that foregrounds the coconstitution of politics and technology through their anchoring to normative discourses—this analysis identifies how data are enrolled to substantiate a grassroots political discourse of spatial injustice yet how, through contestation by government officials, the fragility of data as objects of grassroots political power is laid bare. This empirical study of service provision social audits in Johannesburg and Cape Town shows how governments have effectively resisted their findings by singling out the quantitative data as a weak actor, exploiting this as an opportunity to advance their own political discourse of responsibility around service provision. In revealing how grassroots power was eventually strengthened through a strategic redistribution of agencies, the article then advances a nondeterministic understanding of data power and agency as relational, partial, and provisional and enacted through the coconstitution of people, technologies, and discourses, which might resonate with other examples of data activism and further urban data assemblages. These findings add empirical weight to claims of empowerment made in the emerging fields of data activism and data justice, and they raise further important questions for geographers and others interested in the ways in which data are enrolled to enact grassroots politics, as well as the discursive–material dimensions of urban technopolitics more generally. Key Words: data determinism, data imaginary, data justice, spatial justice, technopolitics.

Day Ahead Hourly Global Horizontal Irradiance Forecasting—Application to South African Data

Due to its variability, solar power generation poses challenges to grid energy management. In order to ensure an economic operation of a national grid, including its stability, it is important to have accurate forecasts of solar power. The current paper discusses probabilistic forecasting of twenty-four hours ahead of global horizontal irradiance (GHI) using data from the Tellerie radiometric station in South Africa for the period August 2009 to April 2010. Variables are selected using a least absolute shrinkage and selection operator (Lasso) via hierarchical interactions and the parameters of the developed models are estimated using the Barrodale and Roberts’s algorithm. Two forecast combination methods are used in this study. The first is a convex forecast combination algorithm where the average loss suffered by the models is based on the pinball loss function. A second forecast combination method, which is quantile regression averaging (QRA), is also used. The best set of forecasts is selected based on the prediction interval coverage probability (PICP), prediction interval normalised average width (PINAW) and prediction interval normalised average deviation (PINAD). The results demonstrate that QRA gives more robust prediction intervals than the other models. A comparative analysis is done with two machine learning methods—stochastic gradient boosting and support vector regression—which are used as benchmark models. Empirical results show that the QRA model yields the most accurate forecasts compared to the machine learning methods based on the probabilistic error measures. Results on combining prediction interval limits show that the PMis the best prediction limits combination method as it gives a hit rate of 0.955 which is very close to the target of 0.95. This modelling approach is expected to help in optimising the integration of solar power in the national grid.

A critical evaluation of copper isotopes in Precambrian Iron Formations as a paleoceanographic proxy

Trace metals in Iron Formations (IF) have been widely used as proxies for oceanic redox processes and oxygen evolution leading to the Great Oxidation Event (GOE). Copper has hitherto received comparatively little attention, with a single study reporting variation in δ65Cu between pre- and post-GOE black shales. This is attributed to postulated isotope fractionation effects in the pre-GOE ocean during widespread iron oxide deposition in IF. Here we focus on the application of Cu isotopes in two classic IF-containing sequences of the Neoarchean-Paleoproterozoic, namely the Hamersley (Australia) and Transvaal (South Africa) Supergroups. We specifically targeted the oxide-rich Joffre and Kuruman IF, the carbonate-rich Griquatown IF, and the Mn-rich Hotazel IF, which collectively record over 100 Ma of sustained IF deposition in the pre-GOE ocean. The aim was to assess the utility of Cu isotopes in IF as a paleoceanographic proxy in view of existing oxygen evolution models. Iron formation Cu concentrations are low compared to average crust and modern oceanic Fe-Mn oxide deposits, with average values between 1 and 5 ppm for all four IF data sets. Copper concentrations show no systematic variability with mineralogy, no statistical correlation with bulk Fe and Mn contents, good correlations with Ti (rCu-Ti = 0.73) for the Joffre data set and with Cr, Ni, and V for the South African data sets, and shale-like Cu/Ti ratios. Isotopic results show statistically invariant average δ65Cu values very close to 0‰ for all but the Joffre IF which has a marginally negative average δ65Cu value (−0.24 ± 0.22‰). Combined with other trace transition metal systematics, the Cu isotope data point to a Cu source that was controlled largely by inputs of fine volcanic-derived particles (ash), thus placing limitations on its utility as a paleoceanographic redox proxy during IF genesis.

Artesunate compared with quinine for the treatment of severe malaria in adult patients managed in an intensive care unit: A retrospective observational study.

There are limited South African data on the outcomes of patients with severe malaria treated with quinine compared with those treated with artesunate in the intensive care unit (ICU). To compare the outcomes of adult patients treated with artesunate against those treated with quinine in the ICU. Primary outcome variables are length of stay (LOS) in the ICU and mortality. Secondary outcomes include the incidence of hypoglycaemic episodes and neurological outcomes. This was a retrospective cohort study of patients with severe malaria treated at a multidisciplinary ICU with artesunate or quinine from 1 January 2008 to 31 December 2012. Of the 92 patients included in the study, 63 (69.2%) were male. The mean age in the quinine and artesunate groups was 36.2 years and 40.5 years, respectively (p=0.071). Most (98.6%) of the patients with a positive travel history had visited a malaria-endemic region. Of the 53 patients tested for HIV infection, 71.7% tested positive (p=0.520). The average CD4+ cell count of HIV-positive patients treated with quinine was 200 cells/µL compared with 217.17 cells/µL for those treated with artesunate (p=0.875). The mean APACHE II score at admission was 20.85 and 19.62 in the quinine group and artesunate group, respectively (p=0.380). The median LOS was 5 days (range 1 - 27). Mortality was 15.4% in the quinine group and 7.7% in the artesunate group (p=0.246). A statistically insignificant mortality difference was observed in outcomes of the two treatment groups in this retrospective, single-centre cohort study. Intravenous artesunate is currently the preferred treatment in the management of patients with severe malaria. However, there are limited local data on the outcomes of artesunate v. quinine therapy for the management of severe malaria in highly monitored clinical environments in non-endemic regions of South Africa.We describe clinical characteristics, management and outcomes of patients with severe malaria treated with quinine and those treated with artesunate in the ICU in a non-endemic region.