Modelling the Electricity Value of Mauritius’ Sugarcane Industrial Ecosystem Using Systems Dynamics Approach

Sugar cane, grown widely in African countries, is known to be one of the most productive species in terms of its conversion of solar energy to chemical potential energy. However, the deployment and diffusion of this technology option on large scale basis is hindered by the complexity in bio-electricity generation. The conversion pathways across bio-electricity production involve water, energy, and land-use planning decision and policy making often occurs in separate and disconnected institutional entities. As such the analytical tools used in support of the decision making process are equally fragmented. In addition the supply of feedstock for electricity generation is limited to the crop harvest season. Let alone the supply is threatened by a wide range of factors among which includes declining sugar prices, competing priorities for land and water which hinder growth of this sector. The complexity warrants the need for decision support tools that can be used not only to broaden the understanding of electricity generation but provide ways of enhancing the energy value of sugarcane production systems in an integrated manner. Using Mauritius as an example this study applied Spatial Systems Dynamics Model (SSDM) that provides a platform for multi-disciplinary simulation. The model integrates the spatial complexity in biomass production, socio-technical complexities in electricity production, and environmental implications in terms of emission avoidance. The model provides multiple scenarios of bio-electricity generation projected from 2012 to 2035. The model highlights the significance of good policy interventions required to optimize electricity production, the potential environmental benefits, and technological improvements that are critical for decision-making especially to a small developing island like Mauritius, which depends heavily on imported fossil fuels to meet its energy demand

Hierarchical Bayesian geostatistics for C stock prediction in disturbed plantation forest in Zimbabwe

We develop and present a novel Bayesian hierarchical geostatistical model for the prediction of plantation forest carbon stock (C stock) in the eastern highlands of Zimbabwe using multispectral Landsat-8 and Sentinel-2 remotely sensed data. Specifically, we adopt a Bayesian hierarchical methodology encompassing a model based inferential framework making use of efficient Markov Chain Monte Carlo (MCMC) techniques for assessing model input parameters. Our proposed hierarchical modelling framework evaluates the influence of two but related covariate information sources in C stock prediction in order to build sustainable capacity on carbon reporting and monitoring. The perceived improvements in the spectral and spatial properties of Landsat-8 and Sentinel-2 data and their potential to predict C stock with shorter uncertainty bounds is tested in the developed hierarchical Bayesian model

The ‘New Normal’ in Higher Education: Innovative teaching and learning technologies and practices during a crisis

Purpose The purpose of this paper is to analyze the effectiveness of innovative technologies and practices adopted to enhance teaching and learning in higher education settings during a crisis e.g. the COVID-19 pandemic in developing countries. We seek to highlight the need for digital and technological transformation in the teaching and learning practices in response to crisis for adaptation to the ‘new normal’. Design /Methodology approach Using a qualitative research approach, data was collected through an online questionnaire and online interviews with lecturers who conducted teaching during the COVID-19 pandemic in developing countries. The countries from where data was collected are Egypt, Zimbabwe, South Africa, Tanzania, Namibia and Botswana. The aim was to highlight transformational processes required for to remote learning during the COVID-19 pandemic. In doing so, we note the adaptable approaches that are useful in times of crisis to promote learning. Findings, contributions and implications The results highlight measures adopted to promote remote learning during a crisis, such as, COVID-19. The contributions include a conceptual model for innovative technologies and practices to the rapid shift to remote learning and ensuring qualities of learning. In developing countries’ context, making use of existing infrastructure, system and organizations is necessary to promote learning in higher education

Implementation of water energy food-health nexus in a climate constrained world: a review for South Africa

In recent years, the Water-Energy-Food (WEF) nexus has gained significant attention in global research. Spatial inequality in water-energy-food security (WEF) and its impact on public health and how this is affected by climate change remains a grand adaptation challenge. South Africa is extremely vulnerable and exposed to the impacts of climate change due to its socio-economic and environmental context. While alternative nexus types have garnered interest, this paper pioneers an extension of the conventional WEF framework to encompass health, giving rise to the Water-Energy-Food-Health (WEF-H) nexus. Despite a plethora of WEF nexus studies focused on South Africa, a substantial knowledge gap persists due to the lack of a comprehensive overview of the enablers and barriers to realizing the WEF-H nexus. South Africa boasts diverse policies related to water, energy, food, and health; however, their alignment remains an ongoing challenge. This study seeks to bridge this critical gap by conducting an exhaustive review of existing literature. Its primary aim is to delve into the intricate mechanisms that either facilitate or impede the actualization of the WEF-H nexus in South Africa. By synthesizing insights from a wide array of literature sources, this research strives to illuminate the challenges and opportunities stemming from the integration of health considerations into the established WEF nexus framework. This exploration holds immense significance, not only for unraveling the multifaceted interactions between these pivotal sectors but also for guiding policy development and decision-making processes in South Africa towards a more holistic and sustainable approach to resource management

The unmet needs and health priorities of the urban poor: Generating the evidence base for urban community health worker programmes in South Africa

Background. There is a growing interest in involving community health workers (CHWs) into the formal healthcare system in South Africa (SA).Objectives. To generate evidence for defining CHW tasks in urban SA.Methods. A cross-sectional survey of residents of Diepsloot, northern Johannesburg, was performed using geographically weighted random sampling, with home-based health assessment and a questionnaire on sociodemographics, medical history, experience of violence, health-seeking behaviour and perceived health priorities.Results. Between May 2013 and March 2014, 1 230 adults participated. Self-reported medical conditions included hypertension (12%), HIV (10%), diabetes (3%), cancer (1%) and mental illness (1%). Health assessments identified a high prevalence of undiagnosed conditions: hypertension (26%), obesity or overweight (46%), mild to severe depression (23%), HIV infection (5.8%) and tuberculosis (TB) (0.4%). Among women, 18% had unmet family planning needs and 77% had never had a Pap smear. Sexually transmitted infection symptoms were reported by 7% of participants. Physical violence was widespread, with 13% having experienced and 16% witnessing violence in the past year, with women mostly experiencing violence at home and men in the community. Participants’ top health concerns were crime, safety and violence (49%) and HIV (18%); healthy living/weight control was listed by only 8% of participants.Conclusions. Alignment of CHW roles to unmet health needs and perceived health priorities will be important for optimal impact of CHW programmes in urban communities. Our data suggest that the CHW role should expand from a traditional focus on HIV, TB and maternal health to include non-communicable diseases, healthy lifestyle, and the intersection of violence and health.

The unmet needs and health priorities of the urban poor: Generating the evidence base for urban community health worker programmes in South Africa

Background. There is a growing interest in involving community health workers (CHWs) into the formal healthcare system in South Africa (SA).Objectives. To generate evidence for defining CHW tasks in urban SA.Methods. A cross-sectional survey of residents of Diepsloot, northern Johannesburg, was performed using geographically weighted random sampling, with home-based health assessment and a questionnaire on sociodemographics, medical history, experience of violence, health-seeking behaviour and perceived health priorities.Results. Between May 2013 and March 2014, 1 230 adults participated. Self-reported medical conditions included hypertension (12%), HIV (10%), diabetes (3%), cancer (1%) and mental illness (1%). Health assessments identified a high prevalence of undiagnosed conditions: hypertension (26%), obesity or overweight (46%), mild to severe depression (23%), HIV infection (5.8%) and tuberculosis (TB) (0.4%). Among women, 18% had unmet family planning needs and 77% had never had a Pap smear. Sexually transmitted infection symptoms were reported by 7% of participants. Physical violence was widespread, with 13% having experienced and 16% witnessing violence in the past year, with women mostly experiencing violence at home and men in the community. Participants’ top health concerns were crime, safety and violence (49%) and HIV (18%); healthy living/weight control was listed by only 8% of participants.Conclusions. Alignment of CHW roles to unmet health needs and perceived health priorities will be important for optimal impact of CHW programmes in urban communities. Our data suggest that the CHW role should expand from a traditional focus on HIV, TB and maternal health to include non-communicable diseases, healthy lifestyle, and the intersection of violence and health.Â

Local people and conservation officials’ perceptions on relationships and conflicts in South African protected areas

Protected areas (PAs) are often conflict-ridden, but conflict resolution mechanisms are often constrained by little appreciation of the perceptions of the principal agents (PA managers and local communities) about such conflicts. Getting local people’s support in PA management efforts is considered important for achieving conservation and livelihood goals. Using data from 13 nature reserves in South Africa, this study explores the perceptions of reserve managers and local communities about their relationships and the existence and underlying causes of conflicts. The findings showed sharp contrasts in perceptions between reserve managers and local communities. Reserve managers generally perceived that there were no conflicts with local communities and that their relationship with them was positive while local communities thought otherwise, claiming conflicts were centred around restricted access to PAs, lack of benefits from PAs and communication problems. These findings have profound implications for conservation, especially considering the importance of getting local people’s support in PA management

Remote sensing hail damage on maize crops in smallholder farms using data acquired by remotely piloted aircraft system

Smallholder farmers reside in marginal environments typified by dryland maize-based farming systems. Despite the significant contribution of smallholder farmers to food production, they are vulnerable to extreme weather events such as hailstorms, floods and drought. Extreme weather events are expected to increase in frequency and intensity under climate change, threatening the sustainability of smallholder farming systems. Access to climate services and information, as well as digital advisories such as Robust spatially explicit monitoring techniques from remotely piloted aircraft systems (RPAS), could be instrumental in understanding the impact and extent of crop damage. It could assist in providing adequate response mechanisms suitable for bolstering crop productivity in a spatially explicit manner. This study, therefore, sought to evaluate the utility of drone-derived multispectral data in estimating crop productivity elements (Equivalent water thickness (EWT), Chlorophyll content, and leaf area index (LAI)) in maize smallholder croplands based on the random forest regression algorithm. A hailstorm occurred in the study area during the reproductive stages 2 to 3 and 3 to 4. EWT, Chlorophyll content, and LAI were measured before and after the storm. Results of this study showed that EWT, Chlorophyll content, and LAI could be optimally estimated based on the red edge and its spectral derivatives. Specifically, EWT was estimated to a rRMEs 2.7% and 59%, RMSEs of 5.31 gm−2 and 27.35 gm-2, R2 of 0.88 and 0.77, while chlorophyll exhibited rRMSE of 28% and 25%, RMSEs of 87.4 µmol m−2 and 76.2 µmol m−2 and R2 of 0.89 and 0.80 and LAI yielded a rRMSE of 10.9% and 15.2%, RMSEs of 0.6 m2/m2 and 0.19 m2/m2 before and after the hail damage, respectively. Overall, the study underscores the potential of RPAS-based remote sensing as a valuable resource for assessing crop damage and responding to the impact of hailstorms on crop productivity in smallholder croplands. This offers a means to enhance agricultural resilience and adaptability under climate change

Institutionalizing Provider-Initiated HIV Testing and Counselling for Children: An Observational Case Study from Zambia

Background: Provider-initiated testing and counselling (PITC) is a priority strategy for increasing access for HIV-exposed children to prevention measures, and infected children to treatment and care interventions. This article examines efforts to scale-up paediatric PITC at a second-level hospital located in Zambia’s Southern Province, and serving a catchment area of 1.2 million people. Methods and Principal Findings: Our retrospective case study examined best practices and enabling factors for rapid institutionalization of PITC in Livingstone General Hospital. Methods included clinical observations, key informant interviews with programme management, and a desk review of hospital management information systems (HMIS) uptake data following the introduction of PITC. After PITC roll-out, the hospital experienced considerably higher testing uptake. In a 36-month period following PITC institutionalization, of total inpatient children eligible for PITC (n = 5074), 98.5 % of children were counselled, and 98.2 % were tested. Of children tested (n = 4983), 15.5 % were determined HIVinfected; 77.6 % of these results were determined by DNA polymerase chain reaction (PCR) testing in children under the age of 18 months. Of children identified as HIV-infected in the hospital’s inpatient and outpatient departments (n = 1342), 99.3 % were enrolled in HIV care, including initiation on co-trimoxazole prophylaxis. A number of good operational practices and enabling factors in the Livingstone General Hospital experience can inform rapid PIT

Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest