Despite its leading role in the urban transport system, paratransit is accused of being unsustainable and hostile to modernity. The reform of the sector is necessary in the context of the modernization of the transport system of African cities. It requires the formalization of actors through technical and financial support such as fleet renewal projects. This article attempts to analyze the financing process and the level of formalism of the operators constituted within the AFTU in the context of the financing operation of paratransit operators in Dakar, Senegal. The methodological approach adopted is based on the analysis of qualitative data from questionnaire surveys carried out in the AFTU network in Dakar; official documents¹ were also used. The results show that the Dakar financing model put in place has made it possible to make significant progress in the reorganization of paratransit professionals. In addition to the concessioned lines, a salaried system was introduced, pricing is now official and the standardized ticketing system has been put in place. Nevertheless, improvements are expected on the working conditions of employees, the capacity building of actors and the evolution of the legal status of companies.

The Human Development Index, which accounts for both net foreign income and the total value of goods and services generated domestically, illustrates how income becomes less significant as Gross National Income (GNI) rises by using the logarithm of income. South Africa ranks 109th out of 189 countries in the Human Development Index (HDI) within the Brazil, Russia, India, China and South Africa (BRICS) economic bloc, raising long-term sustainability concerns. The study explores the relationship between economic, demography, policy indicators and human development in South Africa. South Africa’s unique status as a developing country within the BRICS economic group, alongside its lengthy history of racial discrimination, calls for a sophisticated approach to understanding Human Development. Existing research considered economic, demography, policy indicators independently; the gap of understanding their interconnection and long-term effects in the South African contexts exists. The study addresses the gap by using Autoregressive-Distributed Lag (ARDL) approach to investigate the short-term and the long-term relationship between economic, demography, policy indicators and human development in South Africa. By discovering these links, the study hopes to provide useful insights for policymakers seeking to promote sustainable human development in South Africa. The findings indicate that growth in GDP is a key factor in the HDI since it shows that there are more financial resources available for human development. By discovering these links, the study hopes to provide useful insights for policymakers seeking to promote sustainable human development in South Africa.

The failure to achieve sustainable development in South Africa is due to the inability to deliver quality and adequate health services that would lead to the achievement of sustainable human security. As we live in an era of digital technology, Machine Learning (ML) has not yet permeated the healthcare sector in South Africa. Its effects on promoting quality health services for sustainable human security have not attracted much academic attention in South Africa and across the African continent. Hospitals still face numerous challenges that have hindered achieving adequate health services. For this reason, the healthcare sector in South Africa continues to suffer from numerous challenges, including inadequate finances, poor governance, long waiting times, shortages of medical staff, and poor medical record keeping. These challenges have affected health services provision and thus pose threats to the achievement of sustainable security. The paper found that ML technology enables adequate health services that alleviate disease burden and thus lead to sustainable human security. It speeds up medical treatment, enabling medical workers to deliver health services accurately and reducing the financial cost of medical treatments. ML assists in the prevention of pandemic outbreaks and as well as monitoring their potential epidemic outbreaks. It protects and keeps medical records and makes them readily available when patients visit any hospital. The paper used a qualitative research design that used an exploratory approach to collect and analyse data.

Adolescent childbearing is a crucial problem challenging policymakers in sub-Saharan African countries. The objective of this study is to show how teenage pregnancy and motherhood is related to social determinants like place of residence, education level and wealth quintiles, and consequently to suggest pragmatic actions susceptible to control the burden of teenage pregnancy. Disaggregated data were analyzed using data covering the decade 2012–2022 and provided by Demographic Health Surveys. In each country considered, the index of dissimilarity (ID) was computed to illustrate the variation of teenage pregnancy and motherhood according to the level of education, the rural-urban residence and the income quintiles. Recent statistics were also used for a comparison between countries. This study showed that childbearing affected 22.7% of African adolescents (15–19 years). However, the rate of adolescent childbearing varied from 40.4% in Nigeria to 5.2% in Ruanda. Moreover, huge differences were found in each country. Teenage girls living in rural areas, illiterate or with low level of education and suffering from poverty are more likely to be early married and to be exposed to pregnancy. The rate of adolescent childbearing is higher in Sub-Saharan African countries compared with countries from Latin America and World Health Organization Eastern Mediterranean. Most of the 31 countries considered in this study suffer from high rate of adolescent childbearing and large iniquities by place of residence and/or education level and/or wealth quintiles. Consequently, policymakers should adopt urgent and efficient strategies to reduce (and ideally to end) early marriage and teenage pregnancy by developing a policy that targets disadvantaged girls living in remote areas, having low or no decent income and suffering from illiteracy or low level of education.

Studies show that Fourth Industrial Revolution (4IR) technologies can enhance compliance with COVID-19 guidelines within the parties in the construction industry in the future and mitigate job loss. It implies that mitigating job loss improves the achievement of Sustainable Development Goal 1 (SDG 1) (eliminate poverty). There is a paucity of literature concerning 4IR technologies application and COVID-19 impact on South Africa’s construction industry. Thus, this paper investigates the impacts of the pandemic on the sector and the roles of digital technologies in mitigating job loss in future pandemics. Data were collected via virtual semi-structured interviews. The participants proffered unexplored insights into the impact of the pandemic on the sector and the possible roles that 4IR technology can play in mitigating the spread of the virus within the sector. Findings show that the sector was hit, especially the low-income earners, threatens to achieve Goal 1, despite government institutions’ intervention, such as economic support programmes, health and safety guidelines awareness, and medical facilities. Findings group the emerged impacts into health and safety, environmental, economic, productivity, social, and legal and insurance issues in South Africa. The study shows that technology can be advantageous to improving achieving Goal 1 in a pandemic era due to limited job loss.

Earnings disparities in South Africa, and specifically the Eastern Cape region are influenced by a complex interplay of historical, socio-economic, and demographic factors. Despite significant progress since the end of apartheid, persistent disparities in earnings continue to raise questions about the effectiveness of policies aimed at reducing inequality and promoting equitable social system. Individual-level dataset from the 2021 South African general household survey were subjected to exploratory analysis, while Heckman selection model was used to investigate the determinants of earnings disparities in the study area. The results showed that majority of the population are not working for a wage, commission or salary, which also pointed to the gravity of unemployment situation in the area of study. Most of the working population (both male and female) are lowest earners (R ≤ 10,000), and this also cuts across all age-group categories. Majority of working population have no formal education, are drop out, or have less than grade-12 certificate, and very few working populations with higher education status were found in the moderate and relatively high earnings categories. While many of the working population are engaged in the informal sector, those in the formal sector are in the lowest earners group. Compared to any other race, the Black African group constituted the majority of non-wage earners, and most in this group were found in the lowest earners group. Some of the working population who were beneficiaries of social grants and medical aids scheme were found in the lowest, low, and moderate earnings categories. The findings significantly isolated the earnings-effect of age, marital status, gender, race, education, geographic indicators, employment sector, and index of health conditions and disabilities. The study recommends interventions addressing racial, gender, and geographic wage gaps, while also emphasizing the importance of equitable access to education, health infrastructure, and skills development.