South Africa’s maternal mortality rate (625 deaths/100,000 live births) is high for a middle-income country, although over 90% of pregnant women utilize maternal health services. Alongside HIV/AIDS, barriers to Comprehensive Emergency Obstetric Care currently impede the country’s Millenium Development Goals (MDGs) of reducing child mortality and improving maternal health. While health system barriers to obstetric care have been well documented, “patient-oriented” barriers have been neglected. This article explores affordability, availability and acceptability barriers to obstetric care in South Africa from the perspectives of women who had recently used, or attempted to use, these services. A mixed-method study design combined 1,231 quantitative exit interviews with sixteen qualitative in-depth interviews with women (over 18) in two urban and two rural health sub-districts in South Africa. Between June 2008 and September 2009, information was collected on use of, and access to, obstetric services, and socioeconomic and demographic details. Regression analysis was used to test associations between descriptors of the affordability, availability and acceptability of services, and demographic and socioeconomic predictor variables. Qualitative interviews were coded deductively and inductively using ATLAS ti.6. Quantitative and qualitative data were integrated into an analysis of access to obstetric services and related barriers. Access to obstetric services was impeded by affordability, availability and acceptability barriers. These were unequally distributed, with differences between socioeconomic groups and geographic areas being most important. Rural women faced the greatest barriers, including longest travel times, highest costs associated with delivery, and lowest levels of service acceptability, relative to urban residents. Negative provider-patient interactions, including staff inattentiveness, turning away women in early-labour, shouting at patients, and insensitivity towards those who had experienced stillbirths, also inhibited access and compromised quality of care. To move towards achieving its MDGs, South Africa cannot just focus on increasing levels of obstetric coverage, but must systematically address the access constraints facing women during pregnancy and delivery. More needs to be done to respond to these “patient-oriented” barriers by improving how and where services are provided, particularly in rural areas and for poor women, as well as altering the attitudes and actions of health care providers.

Ghana is classified as being in the malaria control phase, according to the global malaria elimination program. With many years of policy development and control interventions, malaria specific mortality among children less than 5 years old has declined from 14.4% in 2000 to 0.6% in 2012. However, the same level of success has not been achieved with malaria morbidity. The recently adopted 2015–2020 Ghana strategic action plan aims to reduce the burden of malaria by 75.0%. Planning and policy development has always been guided by evidence from field studies, and mathematical models that are able to investigate malaria transmission dynamics have not played a significant role in supporting policy development. The objectives of this study are to describe the malaria situation in Ghana and give a brief account of how mathematical modelling techniques could support a more informed malaria control effort in the Ghanaian context. A review is carried out of some mathematical models investigating the dynamics of malaria transmission in sub-Saharan African countries, including Ghana. The applications of these models are then discussed, considering the gaps that still remain in Ghana for which further mathematical model development could be supportive. Because of the collaborative approach adopted in their development, some model examples Ghana could benefit from are also discussed. Collaboration between malaria control experts and modellers will allow for more appropriate mathematical models to be developed. Packaging these models with user-friendly interfaces and making them available at various levels of malaria control management could help provide the decision making tools needed for planning and a platform for monitoring and evaluation of interventions in Ghana.

South Africa is committed to eliminating malaria with a goal of zero local transmission by 2018. Malaria elimination strategies may be unsuccessful if they focus only on vector biology, and ignore the mobility patterns of humans, particularly where the majority of infections are imported. In the first study in Mpumalanga Province in South Africa designed for this purpose, a metapopulation model is developed to assess the impact of their proposed elimination-focused policy interventions. A stochastic, non-linear, ordinary-differential equation model is fitted to malaria data from Mpumalanga and neighbouring Maputo Province in Mozambique. Further scaling-up of vector control is predicted to lead to a minimal reduction in local infections, while mass drug administration and focal screening and treatment at the Mpumalanga-Maputo border are predicted to have only a short-lived impact. Source reduction in Maputo Province is predicted to generate large reductions in local infections through stemming imported infections. The mathematical model predicts malaria elimination to be possible only when imported infections are treated before entry or eliminated at the source suggesting that a regionally focused strategy appears needed, for achieving malaria elimination in Mpumalanga and South Africa.

A new SARS-CoV-2 variant of concern, Omicron (B.1.1.529), has been identified based on genomic sequencing and epidemiological data in South Africa. Presumptive Omicron cases in South Africa have grown extremely rapidly, despite high prior exposure and moderate vaccination coverage. The available evidence suggests that Omicron spread is at least in part due to evasion of this immune protection, though Omicron may also exhibit higher intrinsic transmissibility. Using detailed laboratory and epidemiological data from South Africa, we estimate the constraints on these two characteristics of the new variant and their relationship. Our estimates and associated uncertainties provide essential information to inform projection and scenario modeling analyses, which are crucial planning tools for governments around the world. One Sentence Summary We report a region of plausibility for the relative transmissibility and immune escape characteristics of the SARS-CoV-2 Omicron variant estimated by integrating laboratory and epidemiological data from South Africa.

South Africa is one of many countries committed to malaria elimination with a target of 2018 and all malaria-endemic provinces, including Mpumalanga, are increasing efforts towards this ambitious goal. The reduction of imported infections is a vital element of an elimination strategy, particularly if a country is already experiencing high levels of imported infections. Border control of malaria is one tool that may be considered. A metapopulation, non-linear stochastic ordinary differential equation model is used to simulate malaria transmission in Mpumalanga and Maputo province, Mozambique (the source of the majority of imported infections) to predict the impact of a focal screen and treat campaign at the Mpumalanga–Maputo border. This campaign is simulated by nesting an individual-based model for the focal screen and treat campaign within the metapopulation transmission model. The model predicts that such a campaign, simulated for different levels of resources, coverage and take-up rates with a variety of screening tools, will not eliminate malaria on its own, but will reduce transmission substantially. Making the campaign mandatory decreases transmission further though sub-patent infections are likely to remain undetected if the diagnostic tool is not adequately sensitive. Replacing screening and treating with mass drug administration results in substantially larger decreases as all (including sub-patent) infections are treated before movement into Mpumalanga. The reduction of imported cases will be vital to any future malaria control or elimination strategy. This simulation predicts that FSAT at the Mpumalanga–Maputo border will be unable to eliminate local malaria on its own, but may still play a key role in detecting and treating imported infections before they enter the country. Thus FSAT may form part of an integrated elimination strategy where a variety of interventions are employed together to achieve malaria elimination.