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The first case of COVID-19 in Eswatini was first reported in March 2020, posing an unprecedented challenge to the country’s health and socio-economic systems. Using geographic information system (GIS) data comprising 15 socioeconomic, demographic and environmental variables, we model the spatial variability of COVID-19 transmission risk based on case data for the period under strict lockdown (up to 8th May 2020) and after the lockdown regulations were gradually eased (up to 30th June 2020). We implemented and tested 13 spatial data-driven Bayesian network (BN) learning algorithms to examine the factors that determine the spatial distribution of COVID-19 transmission risk. All the BN models performed very well in predicting the COVID-19 cases as evidenced by low log loss (0.705–0.683) and high recall values (0.821–0.836). The tree-augmented naïve (TAN) model outperformed all other BN learning algorithms. The proximity to major health facilities, churches, shopping centres and supermarkets as well as average annual traffic density were the strongest predictors of transmission risk during strict lockdown. After gradual relaxation of the lockdown, the proportion of the youth (15–40 years old) in an area became the strongest predictor of COVID-19 transmission in addition to the proximity to areas where people congregate, excluding churches. The study provides useful insights on the spatio-temporal dynamics of COVID-19 transmission drivers thereby aiding the design of geographically-targeted interventions. The findings also point to the robustness of BN models in spatial predictive modelling and graphically explaining spatial phenomena under uncertainty and with limited data.

This study develops models of electricity access and use in Eswatini (formerly Swaziland) using census data on household use of electricity for cooking and lighting. Nighttime light (NTL) data fro...

The spinal cord is the primary pathway of communication between the brain and peripheral nervous system. Knowledge of the spinal cord anatomy and recognition of typical common spinal cord syndromes are important as many of these diseases have a predilection for targeting specific areas or tracts within the spinal cord.

BACKGROUND: TB diagnosis in patients with HIV is challenging due to the lower sensitivities across tests. Molecular tests are preferred and the Xpert® MTB/RIF assay has limitations in lower-income settings. We evaluated the performance of loop-mediated isothermal amplification (LAMP) and the lipoarabinomannan (LAM) test in HIV-positive, ART-naïve clinic patients.METHODS: A total of 783 eligible patients were enrolled; three spot sputum samples of 646 patients were tested using TB-LAMP, Xpert, smear microscopy and culture, while 649 patients had TB-LAM testing. Sensitivity, specificity, and negative and positive predictive values were estimated with 95% confidence intervals.RESULTS: Sensitivities for smear microscopy, TB-LAMP and Xpert were respectively 50%, 63% and 74% compared to culture, with specificities of respectively 99.2%, 98.5% and 97.5%. An additional eight were positive on TB-LAM alone. Seventy TB patients (9%) were detected using standard-of-care testing, an additional 27 (3%) were detected using study testing. Treatment was initiated in 57/70 (81%) clinic patients, but only in 56% (57/97) of all those with positive TB tests; 4/8 multidrug-resistant samples were detected using Xpert.CONCLUSION: TB diagnostics continue to miss cases in this high-burden setting. TB-LAMP was more sensitive than smear microscopy, and if followed by culture and drug susceptibility testing as required, can diagnose TB in HIV-positive patients. TB-LAM is a useful add-in test and both tests at the point-of-care would maximise yield.

We report measurements of the exclusive neutral pion electroproduction cross section off protons at large values of $x_B$ (0.36, 0.48 and 0.60) and $Q^2$ (3.1 to 8.4 GeV$^2$) obtained from Jefferson Lab Hall A experiment E12-06-014. The corresponding structure functions $d\sigma_L/dt+\epsilon d\sigma_T/dt$, $d\sigma_{TT}/dt$, $d\sigma_{LT}/dt$ and $d\sigma_{LT'}/dt$ are extracted as a function of the proton momentum transfer $t-t_{min}$. The results suggest the amplitude for transversely polarized virtual photons continues to dominate the cross-section throughout this kinematic range. The data are well described by calculations based on transversity Generalized Parton Distributions coupled to a helicity flip Distribution Amplitude of the pion, thus providing a unique way to probe the structure of the nucleon.

Agricultural extension is a communication network linking different stakeholders in agriculture to improve their productivity and Information Communication Technology (ICT) has been utilised as an extension tool for enhancing information flow between agricultural extension services and their clients. The application of ICT in agricultural extension and rural development has significantly increased in several countries where it has provided an adequate access to agricultural information. Efforts are, therefore, needed to scale up investments in physical ICT infrastructure and services across developing country. This could be realised through the implementation of interventions aimed at speeding up assimilation and adoption of improved agricultural technology and management practices of the less productive smallholder farmers. Drawing on relevant published works, this paper argues that agricultural knowledge and information management within an extension system can improve productivity of smallholder farmers. The role of ICTs in agricultural extension is discussed together with its challenges towards the improvement of productivity among smallholder farmers. Smallholder farmers need to develop and utilize ICT based knowledge management techniques to implement strategies and interventions to transform the agricultural sector and improve their productivity. Agricultural extension is the ideal mechanism that can facilitate the introduction and subsequent adoption of ICTs for effective knowledge and information management.

Ethnopharmacological relevance Piptadeniastrum africanum is widely used in treating oxidative stress related diseases. Oxidative stress, defined as the disturbance in the balance between the production of free radicals and antioxidant defenses, is the root cause of many pathophysiological conditions. Based on the dual properties of prooxidants as toxic and beneficial compounds, both prooxidants and antioxidants may be effective in the treatment of these conditions when the right dose is given to the right subject at the right time for the right duration. Aim of the study This study was aimed at investigating the in vitro and ex vivo anti- and pro-oxidative effects of P. africanum. Materials and methods Total phenolic and flavonoid contents of methanol and aqueous extracts of P. africanum stem back were quantified spectrophotometrically. The methanol extract, ascorbate radicals and reactive oxygen species in brain and liver homogenates of mice treated with the methanol stem bark extract were analyzed by electron paramagnetic resonance (EPR) spectroscopy. Free radical scavenging of DPPH was determined by spectrophotometric and EPR assays. Results The methanol extract was richer in both phenolic and flavonoid contents compared to the aqueous extracts and also showed better DPPH radical scavenging capacity. The EPR spectroscopy in vitro analysis exhibited high DPPH scavenging capacity before and after UV irradiation (99.5% and 98.76%) at 40 μg/ml extract. The ex vivo EPR spectroscopy studies demonstrated increased levels of ascorbate radicals (•Asc) in liver and brain homogenates of healthy mice treated with P. africanum in comparison with those of the non treated controls (0.6141 ± 0.026 vs 0.1800 ± 0.0073 arb. units for liver homogenates and 0.9605 ± 0.0492 vs 0.3375 ± 0.0062 arb. units for brain homogenates, correspondingly). Considerably, higher levels of reactive oxygen species (ROS) were measured in mice liver and brain homogenates after treatment with P. africanum extract compared to the control group, as well (1.9402 ± 0.1200 vs 0.6699 ± 0.062 arb. units for liver homogenates and 1.7325 ± 01503 vs 0.3167 ± 0.0403 arb.units, respectively). Conclusion Therefore, P. africanum exhibited antioxidant and pro-oxidant properties which may explain its broad spectrum use in a wide variety of ailments.

Quasielastic C12(e,e′p) scattering was measured at spacelike 4-momentum transfer squared Q2=8, 9.4, 11.4, and 14.2 (GeV/c)2, the highest ever achieved to date. Nuclear transparency for this reaction was extracted by comparing the measured yield to that expected from a plane-wave impulse approximation calculation without any final state interactions. The measured transparency was consistent with no Q2 dependence, up to proton momenta of 8.5 GeV/c, ruling out the quantum chromodynamics effect of color transparency at the measured Q2 scales in exclusive (e,e′p) reactions. These results impose strict constraints on models of color transparency for protons.

The influence of the naturally occurring population of microbes on various human diseases has been a topic of much recent interest. Not surprisingly, continuously growing attention is devoted to the existence of a gut brain axis, where the microbiota present in the gut can affect the nervous system through the release of metabolites, stimulation of the immune system, changing the permeability of the blood–brain barrier or activating the vagus nerves. Many of the methods that stimulate the nervous system can also lead to the development of cancer by manipulating pathways associated with the hallmarks of cancer. Moreover, neurogenesis or the creation of new nervous tissue, is associated with the development and progression of cancer in a similar manner as the blood and lymphatic systems. Finally, microbes can secrete neurotransmitters, which can stimulate cancer growth and development. In this review we discuss the latest evidence that support the importance of microbiota and peripheral nerves in cancer development and dissemination. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is crucial for surveillance, control and response to the disease. Knowing the geographic distribution of health resource scarcity areas is necessary if a country is to adequately anticipate and prepare for the full impact of infections. We explored the potential to undertake a spatial risk assessment of an emerging pandemic under data scarcity in Eswatini. We used a set of socio-economic and demographic variables to identify epidemic risk prone areas in the country. Three risk zone levels for COVID-19 were identified in the country. The analysis showed that about 29% (320 818) of the population were located in the high risk zone and these were people who could potentially be infected with COVID-19 in the absence of mitigation measures. A majority of cases and deaths attributed to COVID-19 would likely remain unknown but our estimate could be used to gauge the full burden of the disease. Approximating and quantifying the number of people who may be potentially infected with COVID-19 remains impossible under data scarcity and limited healthcare capacity especially in sub-Saharan Africa. We provided an estimation method that could support the pandemic risk forecasting, preparedness and response measures in the midst of data scarcity. The resultant map products could be used to guide on-the-ground surveillance and response efforts., Highlights • About 321 000 people are located in the COVID-19 high risk zone in Eswatini. • A majority of COVID-19 cases and deaths are likely to remain unknown due to poor testing in Eswatini. • Minimizing movement from high risk zones to low risk areas could help control the spread of COVID-19.

Quasielastic ^{12}C(e,e^{'}p) scattering was measured at spacelike 4-momentum transfer squared Q^{2}=8, 9.4, 11.4, and 14.2 (GeV/c)^{2}, the highest ever achieved to date. Nuclear transparency for this reaction was extracted by comparing the measured yield to that expected from a plane-wave impulse approximation calculation without any final state interactions. The measured transparency was consistent with no Q^{2} dependence, up to proton momenta of 8.5 GeV/c, ruling out the quantum chromodynamics effect of color transparency at the measured Q^{2} scales in exclusive (e,e^{'}p) reactions. These results impose strict constraints on models of color transparency for protons.

$^{2}\mathrm{H}(e,e'p)n$ cross sections have been measured at 4-momentum transfers of $Q^{2} = 4.5 \pm 0.5$ (GeV/c)$^{2}$ over a range of neutron recoil momenta, $p_{\mathrm{r}}$, reaching up to $\sim1.0$ GeV/c. The data were obtained at fixed neutron recoil angles $\theta_{nq} = 35^\circ$, $45^\circ$ and $75^{\circ}$ with respect to the 3-momentum transfer $\vec q$. The new data agree well with previous data which reached $p_{\mathrm{r}}\sim500$ MeV/c. At $\theta_{nq} = 35^\circ$ and $45^\circ$, final state interactions (FSI), meson exchange currents (MEC) and isobar currents (IC) are suppressed and the plane wave impulse approximation (PWIA) provides the dominant cross section contribution. The new data are compared to recent theoretical calculations, where we observe a significant discrepancy for missing momenta $p_{\mathrm{r}}>700$ MeV/c., Comment: main article: 6 pages, 2 figures | supplemental material: 7 pages, 13 figures | numerical tables of cross sections for data and theory are provided as ancillary material | This version has minor additions in the concluding paragraph to address the light-cone / EFT formalisms in the context of this experiment. The supplemental materials have new Fig. 10, and modified Fig. 9

Veld fires have become a frequent and devastating phenomena in the predominantly savanna ecosystems of the Kingdom of Eswatini. While fire damages have become more common and recurrent in recent years, their causes and impacts in the Kingdom of Eswatini are less understood, with very limited literature. This study aimed at filling up this existing information gap by investigating the causes, socio-economic and environmental impacts of veld fires, as well as highlighting the challenges and/or limitations in fire management and control in the Kingdom of Eswatini. The study used mixed methods approach to collect both primary and secondary data. These included household questionnaires and face-to-face interviews with key informants. The results showed that the major causes of fires are mainly anthropogenic, and these include arson and conflicts, controlled burning, ignorance of proper fire management practices, collision of electric cables, and acts of negligence, among others. Major impacts of veld fires in Eswatini were found to include disruption of rural (and urban) livelihoods, infrastructure damage, loss of biodiversity and destruction of important environmental resources, to mention but a few. The study concluded that fires contribute to biodiversity loss and that fires continue to be a major treat to the country’s economy. Lack of fire management resources is one contributing factor to the widespread fire damage in the country, while quantifying the direct economic loss resulting from fire remains a challenge due to lack of standardized fire damages data collection and reporting tools. The study recommended a development of a standardized tool for reporting fire damages, improvement of fire prevention and management, and development of an early warning system (in addition to capacity assessment of fire emergency operators) in an effort to improve fire management and to minimize fire-related damages in the country.

Organic and inorganic nanocomposites have been successfully used in the preparation of thin film organic solar cells with the view either to enhance the harvesting of solar energy or to assist in the charge transport processes. The optical absorption, conductivity and environmental stability of the nanocomposite are the main criteria that determine the suitability of the material for solar energy application. This chapter discusses the properties of a number of nanocomposite which are widely used in the preparation of various types of thin film solar cells.

SETTING In South Africa, KwaZulu-Natal is the epicentre of the human immunodeficiency virus (HIV) epidemic, where approximately 70% of people with tuberculosis (TB) are co-infected with HIV. Undiagnosed TB contributes to high mortality in HIV-infected patients. Delays in diagnosing TB and treatment initiation result in prolonged transmission and increased infectiousness. OBJECTIVE To evaluate the LoopampTM MTBC Detection kit (TB-LAMP; based on the loop-mediated isothermal amplification assay), smear microscopy and Xpert test with the gold standard of mycobacterial culture. METHODS Sputum samples were collected from 705 patients with symptoms of pulmonary TB attending a primary health care clinic. RESULTS The TB-LAMP assay had significantly higher sensitivity than smear microscopy (72.6% vs. 45.4%, P < 0.001), whereas specificity was slightly lower (99% vs. 96.8%, P = 0.05), but significantly higher than Xpert (92.9%, P = 0.004). There was no significant difference in sensitivity of smear-positive, culture-positive and smear-negative, culture-positive sputum samples using TB-LAMP vs. Xpert (respectively 95.9%/55.9% vs. 97.6%/66.1%; P =0.65, P = 0.27). The positive predictive value of TB-LAMP was significantly higher than that of Xpert (87.5% vs. 77.0%; P = 0.02), but similar to that of smear microscopy (94.2%; P = 0.18). The negative predictive value was respectively 91.9%, 92.5% (P = 0.73) and 83.1% (P = 0.0001). CONCLUSION Given its ease of operability, the TB-LAMP assay could be implemented as a point-of-care test in primary health care settings, and contribute to reducing treatment waiting times and TB prevalence.

There has been growing concern regarding the pollution of the aquatic environment with synthetic organic chemicals. Antiretroviral drugs, such as efavirenz and nevirapine, are pharmaceutical drugs and are referred to as emerging contaminants. Such drugs can be environmentally persistent and may be expected to pose potential risks to drinking water supplies. Sources of pharmaceutical drugs include effluents from Wastewater Treatment Works (WWTPs), hospital and pharmaceutical production facilities and the incorrect disposal of unused and expired medicines. Currently there are no monitoring programs and legislative guidelines for their regulations in South Africa. The aims of this study were firstly to develop a semi-quantitative method to extract and analyse efavirenz and nevirapine in the primary settling tank sludge. Secondly to use that method, and an existing method for liquid wastewater samples, to monitor the concentrations of efavirenz and nevirapine as the wastewater passes through the different stages of purification (anoxic; aerobic; pre and post chlorination) in the WWTP. This was repeated weekly over a period of 4 weeks. Thirdly, to determine if binding of efavirenz and nevirapine to the solids in the WWTP played a role in the removal of these compounds from the WWTP liquid phase. No references to the analysis of ARVDs in WWTP sludge were found in the literature. Grab samples of wastewater and sludge samples were collected from a WWTP (activated sludge treatment process) weekly for 4 weeks. Liquid samples were extracted solid phase extraction, solid samples were extracted using sonication followed by a QuEChERs clean-up. Sample extracts were then subjected to gas chromatography-time of flight mass spectrometry for analyte determination. Efavirenz concentrations entering the WWTP ranged between 5500 to almost 14 000 ng/L. The removal of efavirenz by the WWTP ranged between 27 and 71%. The largest removal occurred in the anoxic zone, smaller amounts were removed in the aerators. Slight increases in efavirenz concentrations were found after chlorination and the final effluent into the river post maturation ponds again were slightly lower. Solids were found to contain efavirenz at concentrations between 17 and 43 mg/kg dried primary settling tank sludge and it is proposed that this binding to the solids is the main mechanism of removal of efavirenz from the wastewater stream as it passes through the WWTP. Although an order of magnitude lower nevirapine concentrations displayed the opposite behaviour and gradually increased through the various stages of purification in the WWTP. Minor fluctuations occurred but the concentrations of nevirapine were higher at the effluent (between 92 and 473 ng/L) than those entering the WWTP. No nevirapine was detected in the PST sludge. The increase in nevirapine concentrations are likely to be the result of the de-conjugation of the hydroxylated metabolites of nevirapine in the WWTP, its resistance to degradation and the lack of binding of the nevirapine to the PST sludge.

Forests and woodlands are a very important part of the global ecosystem through their provision of ecosystem goods and services. However, conversion to other land uses is one of the biggest threats to their existence. Remote sensing presents opportunities for monitoring such changes over wide and inaccessible areas including those areas that have no field data. In this study, we use the Carnegie Landsat Analysis System-lite (CLASlite) software and Landsat imagery to make the first spatially explicit national estimate deforestation in Swaziland. This was compared with deforestation data derived from the Global Forest Change (GFC) dataset for the period 2000–2014. The CLASlite analysis identified an estimated 46,620ha of forest and woodland lost between 1990 and 2015 resulting in a mean deforestation rate of 1704 ha yr−1. The GFC dataset, on the other hand, indicates a mean deforestation rate 1563 ha yr−1 when excluding forest regrowth. Validation of the results based on multi-year Google Earth and Landsat imagery indicated that both approaches are feasible for monitoring deforestation. The GFC data captured more forest loss within the dense plantation and wattle forests whilst underestimating deforestation within natural forests and woodlands. Although there are inter-annual variations, the rate of deforestation is generally increasing and widespread in many parts of the country mainly concentrated in the eastern half of the country and a few western parts where agriculture (particularly sugarcane), human settlements and other infrastructure developments are dominant land uses. Acacia and broadleaf savanna are being depleted at higher rates with up to 8.1% of forest area lost since the year 2000. Forest policies and legislation need to be reviewed to respond to the observed trends and patterns with a focus on forest conservation, climate change mitigation and adaptation.

The study investigated smallholder sugarcane farmers and extension officers' perceptions of readiness towards the use of Information and Communication Technology (ICT), especially cell phones, as a source of technology for accessing information within the Swaziland sugar industry. The study was a census involving all active smallholder sugarcane farmers in Swaziland (N=172) and their extension officers (N=17). Quantitative data were collected through face-to-face interviews using a valid and reliable structured questionnaire. Descriptive statistics and one way analysis of variance (ANOVA) were applied to analyse the data. The results revealed that sugarcane farmers and extension officers perceive the Swaziland sugar industry to be ready for the introduction and subsequent use of ICTs to access sugarcane production information. The sugar industry infrastructure and other facilities that are necessary for the use of cell phones were perceived to be ready. All respondents possessed cell phones which they personally owned. The entire sugar industry had access to cellular network and electricity. It was also shown that some demographic variables of respondents did have an influence on their perceptions regarding the industry's readiness towards the use of cell phones to access information. The results of this study can provide guidance to the government and the sugar industry of Swaziland when considering implementing improved information dissemination based programmes.

Riparian vegetation in the Okavango Delta has extensive economic, social and environmental benefits. However, despite its importance, it is threatened by changes in variation in hydrology, anthropogenic activities, and other environmental conditions. Some riparian vegetation communities may change rapidly in response to both long term and short term disturbances. Long term monitoring of riparian woodland vegetation can help reveal changes in these woodland species, enabling timeous management interventions. In this study we classified, mapped and conducted change detection analysis of the spatial extent of different communities of riparian woodland in the Okavango Delta. Woodland species were identified in the field and their percentage cover estimated. Agglomerative hierarchical cluster analysis in PC-ORD was used to classify woodland vegetation into four communities. These communities were Croton megalobotrys-Hyphaene petersiana, Vachellia erioloba-Gymnosporia senegalensis, Phoenix reclinata-Syzygium cordatum and Vachellia tortilis-Combretum imberbe. Multi response permutation procedures (MRPP) was used to test if there was any significant difference in plant species composition between different vegetation communities. MRPP showed that communities varied significantly (p

The construction industry is negatively affected by cost and time overruns which further negatively impacts the contractual stakeholders. Construction delays and cost overruns are a global phenomenon since one of the major problems in the construction industry involves unexpected incurred costs and late delivery of projects. The success and failure of any project depends upon many factors and the Project Manager is considered to be the key contributor to the success of any project, as well as to guide the team members to achieve the client satisfaction. In addition, the roles, responsibilities, duties, and competencies of Project Managers have a direct impact on successfully completing construction projects on time and within budgeted cost. The study aimed to find the key competency skills that the Project Manager must possess to mitigate time and cost overruns. A quantitative research approach was adopted to determine the key competency skills of a Project Manager with respect to cost and time delays. A web-based questionnaire was published in the Eastern Cape Masters Builders Association (MBA) bulletin aimed at contractors registered with the association. The results revealed that the key competencies required to mitigate for cost overruns are comparable to those required to mitigate against time overruns. The study investigated the need for project managers to better equip themselves with key competency skills to perfom optimally to reduce the occurrence of cost and time delays on construction projects. The aim of this research was to assist Construction Managers to choose the right candidate as a Project Manager. It would also assist inspiring Project Managers to acquire the key competency skills. The paper responds to the conference theme given that the reduction of cost and time overruns promotes the sustainability of the Built Environment.

Deforestation is a global phenomenon that threatens not only biodiversity but also the livelihoods of people who depend on them. Recent global analyses indicates that this problem is growing, hence the growing need to identify the underlying drivers in order to develop more responsive policies. We present a machine learning-based method which automatically identifies key drivers and makes predictions from available spatial data in Swaziland during the post millennium period. The efficient Bayesian multivariate classifiers (EBMC) are used to learn feature-selected Bayesian network (BN) models of deforestation from multisource data. The EBMC models, learned using the K2 and BDeu algorithms, were also used to predict the probability or risk of deforestation in addition to providing a directed acyclic graphical view of the key interacting factors. These were compared with constraint and knowledge-based BNs developed using the common EBMC-selected variables. All the models performed consistently well (log loss 0.8) when evaluated against observed deforestation patterns. The knowledge-based and constrained-based BNs performed well highlighting the need for developing a causal structure of interactions between variables. The findings indicate that deforestation patterns are determined by an interaction of proximate and underlying factors primarily fuelwood use, human population density, human settlements, protection and land ownership status. The findings indicate that, unless robust conservation measures are put in place, deforestation is likely to continue as more areas become vulnerable. The models produced plausible results that can be used for preventive planning and policy making.

Children comprise a large proportion of the population in sub-Saharan Africa. The burden of paediatric surgical disease exceeds available resources in Africa, potentially increasing morbidity and mortality. There are few prospective paediatric perioperative outcomes studies, especially in low- and middle-income countries (LMICs).We conducted a 14-day multicentre, prospective, observational cohort study of paediatric patients (aged16 yrs) undergoing surgery in 43 government-funded hospitals in South Africa. The primary outcome was the incidence of in-hospital postoperative complications.We recruited 2024 patients at 43 hospitals. The overall incidence of postoperative complications was 9.7% [95% confidence interval (CI): 8.4-11.0]. The most common postoperative complications were infective (7.3%; 95% CI: 6.2-8.4%). In-hospital mortality rate was 1.1% (95% CI: 0.6-1.5), of which nine of the deaths (41%) were in ASA physical status 1 and 2 patients. The preoperative risk factors independently associated with postoperative complications were ASA physcial status, urgency of surgery, severity of surgery, and an infective indication for surgery.The risk factors, frequency, and type of complications after paediatric surgery differ between LMICs and high-income countries. The in-hospital mortality is 10 times greater than in high-income countries. These findings should be used to develop strategies to improve paediatric surgical outcomes in LMICs, and support the need for larger prospective, observational paediatric surgical outcomes research in LMICs.NCT03367832.

Since its detection in Kenya in 2003, the exotic fruit fly, Bactrocera dorsalis, has rapidly spread throughout sub-Saharan Africa. This study was conducted to predict the potential distribution of B. dorsalis in the southern African region using suitable environmental variables and some feral host plants. Presence data from surveillance information carried out in Mozambique and Swaziland up to 2013 were used for niche modelling to predict the potential geographical distribution of the pest in the southern African region. Prediction for its national distribution within Swaziland was also carried out using distribution data for eight feral host plants. Although variable between countries, predicted habitat suitability for the pest was potentially greater in the eastern parts of southern Africa, with response curves suggesting higher probability of the pest's occurrence in low altitude areas with moderate diurnal temperature and high precipitation during the wettest month of the year. Of the host plants considered, the pest's distribution was associated mainly with Ficus sycomorus. The model's prediction also suggested that human-associated activities, such as irrigation, could influence the distribution and establishment of the pest even in areas of low host-plant richness. Since the presence of B. dorsalis causes restrictions in international trade of its host plants, it is imperative that countries within the region continue surveillance programmes and coordinated strategies to reduce the impact of the pest.

In South Africa, KwaZulu-Natal is the epicentre of the human immunodeficiency virus (HIV) epidemic, where approximately 70% of people with tuberculosis (TB) are co-infected with HIV. Undiagnosed TB contributes to high mortality in HIV-infected patients. Delays in diagnosing TB and treatment initiation result in prolonged transmission and increased infectiousness.To evaluate the LoopampTM MTBC Detection kit (TB-LAMP; based on the loop-mediated isothermal amplification assay), smear microscopy and Xpert test with the gold standard of mycobacterial culture.Sputum samples were collected from 705 patients with symptoms of pulmonary TB attending a primary health care clinic.The TB-LAMP assay had significantly higher sensitivity than smear microscopy (72.6% vs. 45.4%, P0.001), whereas specificity was slightly lower (99% vs. 96.8%, P = 0.05), but significantly higher than Xpert (92.9%, P = 0.004). There was no significant difference in sensitivity of smear-positive, culture-positive and smear-negative, culture-positive sputum samples using TB-LAMP vs. Xpert (respectively 95.9%/55.9% vs. 97.6%/66.1%; P =0.65, P = 0.27). The positive predictive value of TB-LAMP was significantly higher than that of Xpert (87.5% vs. 77.0%; P = 0.02), but similar to that of smear microscopy (94.2%; P = 0.18). The negative predictive value was respectively 91.9%, 92.5% (P = 0.73) and 83.1% (P = 0.0001).Given its ease of operability, the TB-LAMP assay could be implemented as a point-of-care test in primary health care settings, and contribute to reducing treatment waiting times and TB prevalence.

The economy of Swaziland is depended on agriculture. In 2009, it was reported that agriculture, forestry, and manufacturing contributed 42% of Swaziland’s Gross Domestic Product (GDP). Besides economic importance, animal agriculture is important for food production and life sustenance. It is also viewed as a symbol of wealth and high social status particularly for the rural folks. Despite the merits of agricultural activities, agricultural production, particularly animal production, has been incriminated for an accelerated emission of greenhouse gases. These gases are responsible for global warming and climate change. The aim of this study was to determine the contribution of animal agriculture to greenhouse gases production and to elicit adaptation strategies to climate change and the role of modern technologies as mitigating measures. The minor and major greenhouse gases produced by farm animals were computed using the IPCC spread sheet for calculation of greenhouse gases emissions. The minor greenhouse gases produced by farm animals were NOx and CO2 and the major gasses included CH4 and N2O. The greenhouse gas that was emitted the most by farm animals was CH4, 24 Gg or 600 CO2e per annum. Ruminants were the major producers of methane. The producers of the least greenhouse gases emissions were non ruminants. Livestock produced 0.87 Gg of N2O per annum, a global warming potential of 259 CO2e. Feeding ammoniated straw and silage inoculating with transgenic rumen bacteria, animal breeding and manure storage techniques, use of biogas digester with methane gas recovery and emphasis on non ruminant production were possible strategies that could be employed to reduce greenhouse gases production from the livestock sector. It was recommended that feed preservation technologies, selection strategies, water harvesting, storage and recycling strategies and intensive livestock production systems could be used as adaptation strategies to climate change in livestock production.

This paper provides a useful guidance in the interpretation and analyses of the technical impact of power factor correction in a power system. It is intended to raise awareness in order to achieve correct measurements, calculations and the key dynamics of the power system when quantifying the impact of power quality (PQ) in a non-linear power system. This paper is therefore targeting the power producing utilities, municipalities and the bulk end users of electricity.

This article describes the use of a Bayesian network (BN) for the classification of land cover from satellite imagery in northern Swaziland. The main objective of this work was to apply and evaluate the efficacy of a BN for land-cover classification using gap-filled and terrain-corrected Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery acquired on 15 May 2007. The posterior probabilities (parameters) were estimated using the expectation-maximization (EM) and conjugate gradient descent (CGD) algorithms. A comparison of the results obtained from the algorithms indicates similar and excellent overall classification accuracies of 93.01%, and kappa coefficient values of 0.9143. The main result obtained in this study is that both algorithms considered here provide relatively similar and accurate solutions for the classification of the multispectral image although the EM algorithm is marginally competitive relative to CGD algorithm when measured in terms of the Brier score and the logarithmic loss.

This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.

This study uses Bayesian networks (BNs) to simulate the spatial distribution of southern African biomes and bioregions using bioclimatic variables. Two Tree-Augmented Naive (TAN) BN models were parameterized from 23 bioclimatic variables using the expectation-maximization (EM) algorithm. Using sensitivity analyses, the relative influence of each variable was determined using the mutual information from which six bioclimatic variables were selected for the final models. Precipitation of the warmest quarter and extra-terrestrial solar radiation was found to be the most influential variables on both bioregion and biome distributions. Isothermality was the least influential bioclimatic variable at both bioregion and biome levels. Overall correspondence was very high at 93.8 and 87.1% for biomes and bioregions, respectively, whereas classification errors were obtained in transition areas indicating the uncertainties associated with vegetation mapping around margins. The findings indicate that southern African bioregions and biomes can be classified and mapped according to key bioclimatic variables. Spatio-temporal, in particular, monthly and quarterly variations in both precipitation and temperature are found to be ecologically significant in determining the spatial distribution of biomes and bioregions. The findings also reflect the hierarchical relationship of biomes and bioregions as a function of local bioclimatic gradients and interactions. The results indicate the ecological significance of bioclimatic conditions in ecosystem science and offer the opportunity to utilize the models for predicting future responses and sensitivities to climatic changes.

In a spatially explicit climate change impact assessment, a Bayesian network (BN) model was implemented to probabilistically simulate future response of the four major vegetation types in Swaziland. Two emission scenarios (A2 and B2) from an ensemble of three statistically downscaled coupled atmosphere-ocean global circulation models (CSIRO-Mk3, CCCma-CGCM3 and UKMO-HadCM3) were used to simulate possible changes in BN-based environmental envelopes of major vegetation communities. Both physiographic and climatic data were used as predictors representing the 2020s, 2050s and the 2080s periods. A comparison of simulated vegetation distribution and the expert vegetation map under baseline conditions showed an overall correspondence of 97.7% and a Kappa coefficient of 0.966. Although the ensemble projections showed comparable trends during the 2020s, the results from the A2 storyline were more drastic indicating that grassland and the Lebombo bushveld will be impacted negatively as early as the 2020s with about 1 °C temperature increase. The bioclimatically suitable areas of all but one vegetation type decline drastically after about 2 °C warming, more so under the more severe A2 scenario and in particular during the 2080s. The sour bushveld is the only vegetation type that initially responds positively to warming by possibly encroaching to the highly vulnerable grassland areas. Vulnerability of vegetation is increased by the limited ability to migrate into suitable climates due to close affinity to certain geological formations and the fragmentation of the landscape by agriculture and other land uses. This is expected to have serious impacts on biodiversity in the country. Under warmer climates, the likely vegetation types to emerge are uncertain due to future novel combinations of climate and bedrock lithology. The strengths and limitations of the BN approach are also discussed.

This study estimates fire risk in Swaziland using geographic information system (GIS) and remote sensing data. Fire locations were identified in the study area from remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) active fire and burned area data for the period between April 2000 to December 2008 and January 2001 and December 2008, respectively. A total of thirteen biophysical and socio-economic explanatory variables were analyzed and processed using a Bayesian network (BN) and GIS to generate the fire risk maps. The interdependence of each of the factors was probabilistically determined using the expectation-maximization (EM) learning algorithm. The final probabilistic outputs were then used to classify the country into five fire risk zones for mitigation and management. Accuracy assessments and comparison of the fire risk maps indicate that the risk maps derived from the active fire and burned area data were 93.14 and 96.64% accurate, respectively, demonstrating sufficient agreement between the risk maps and the existing data. High fire risk areas are observed in the Highveld particularly plantation forests and grasslands and within the Lowveld sugarcane plantations. Land tenure and land cover are the dominant determinants of fire risk, the implications of which are discussed for fire management in Swaziland. Limitations of the data used and the modeling approach are also discussed including suggestions for improvements and future research.

The impacts of wildfires on ecosystems and the factors contributing to their occurrence are increasingly receiving global attention. Advances in satellite remote sensing and information technology provide an opportunity to study these complex interrelationships. A Bayesian belief network (BBN) model was developed from a set of 12 biotic, abiotic and human variables to determine factors that influence wildfire activity in Swaziland using wildfire data from the Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2001-2007. These were geospatially integrated in the geographic information system (GIS) software ArcView and input into the software Netica for BBN analyses. Land cover, elevation, and climate (mean annual rainfall and mean annual temperature) were found to be strong predictors of wildfire occurrence, while aspect had the least influence on the wildfire occurrence. The model had a high predictive accuracy with an error rate of 9.62%, and an area under the receiver-operating characteristic (ROC) curve of 0.961. The study demonstrates how domain or field knowledge and limited empirical and GIS data can be combined within a BBN model to assist in determining key fire management interventions and lays the foundation for the future development of advanced and dynamic models.

Data from the NASA'S MODIS (Aqua and Terra) and EUMETSAT'S MSG-SEVIRI satellite sensors is analysed to characterise the geographic and temporal (including diurnal) evolution of the July 2007 fire disaster in the Kingdom of Swaziland using a geographic information system (GIS). Significant fire activity was observed during a three-day period beginning on the 27th July 2007. A total of 1358 and 4365 active fire hotpots were detected by MODIS and MSG-SEVIRI, respectively, mainly concentrated in the Highveld (70.91% for MODIS, 89.89% for MSG) and Middleveld (11.27% for MODIS, 5.23% for MSG) with MSG/MODIS active fire count ratio ranging from a high of 3.69 in the Highveld to a low of 0.06 in the Lubombo Plateau. The results indicate complex differences in spatial fire distribution, behaviour and risk within the country and the effect of sensor differences. A pronounced fire diurnal cycle with a broad afternoon peak centred on 14:00 local time is observed, in general agreement with observations from the region. Despite their limitations, the study demonstrates the importance and usefulness of remotely sensed data and GIS technology for fire disaster and risk assessment for a developing country, where fire monitoring resources are scarce.

Little is known about the grass species type, composition and nutritive value in the semiarid savannas that sustain most of Swaziland\'s cattle population through the seven-month-long dry season. This study was conducted to investigate the nutritional characteristics of grasses collected from two grazing areas (Big Bend and Simunye), which differed mainly in soil types. Mature grass species were harvested and evaluated for chemical composition (organic matter, neutral detergent fibre [NDF], acid detergent fibre [ADF], crude protein [CP] and minerals) and in vitro ruminal fermentation ( in vitro gas production, in vitro organic matter degradability and partitioning factors). The most common grass species in the Big Bend grazing area were Bothriochloa insculpta , Cenchrus ciliaris and Urochloa mosambicensis . In the Simunye grazing area the most common species were B. insculpta , U. mosambicensis , Heteropogon contortus , Panicum deustum and P. maximum . For grasses harvested from Simunye, the most ( p –1 dry matter) was B. insculpta , which also had the least fibre (597 g kg –1 NDF and 351 g kg –1 ADF) and the highest CP content (79.8 g kg –1 ). The most common grass species harvested from the Big Bend area did not differ ( p > 0.05) in their Mg, P, Cu, Fe, Zn, CP and NDF content. However, U. mosambicensis had the highest ( p –1 gas) was observed for U. mosambicensis as a result of low DOM coupled with high cumulative gas production. It was concluded that all the grasses investigated in this study show a deficit for Ca, P and protein. Therefore, supplementation is needed to ensure maximum forage utilisation and to satisfy nutrient requirements of ruminant livestock. Keywords: cumulative gas production; organic matter degradability; ruminant livestock; tropical grass species African Journal of Range & Forage Science 2009, 26(1): 9–17

An investigation is undertaken to analyze the human lightning fatalities in Swaziland. A total of 123 victims of lightning-related death were identified from the records of the Royal Swaziland Police Service and the local printed media for the period 2000–2007. An annual average fatality rate of 15.5 people per million, the highest recorded rate in the world, was obtained. The results also reveal that 66% were male, most (67%) of them were within the 10–39 age group with an average age of 28 years. Lightning fatalities occurred from September to May mainly in the afternoon (1400–1800 h). Deaths most commonly occurred indoors inside rural houses (17%), whilst walking (16%) and under a tree (14%). The incidents resulted in multiple fatalities in 22% of the cases with an average of 1.4 casualties per incident. The need for awareness campaigns, protection measures and detailed investigation is highlighted.

The Komati River Basin is a trans‐boundary watercourse shared by the Republic of South Africa (RSA), the Kingdom of Swaziland (KoS) and the Republic of Mozambique. The Komati Basin Water Authority (KOBWA) is charged with the management of the river basin under a treaty signed between RSA and Swaziland of which consent was given by Mozambique in a separate Agreement. KOBWA developed Decision Support Systems (DSS) to manage the system. These include DSS for: (i) long‐term water allocation (yield model) between the countries, (ii) short‐term water allocation (rationing model), and (iii) day‐to‐day water release (hydraulics model). An extensive water‐monitoring program has been put in place to improve the effectiveness of these DSSs. There has been a wide acceptance of the DSS by the users in the basin since the DSSs enable water users and water managers to make transparent water management decisions. This paper describes the three DSSs including the institutional framework on which these are applied.

This paper presents an adaptation of fractional water allocation and reservoir capacity sharing (FWARCS) concepts for application in the Komati Basin, a river system shared between South Africa, Swaziland and Mozambique. Many traditional methods for allocating water are based on volume-per-unit-time allocation that is supplied at some level of assurance and managed using priority-based reservoir and river system operating rules, as well as on the “use it or lose it” principle, which is considered exclusive by water users as it leaves them out of the management of their water allocations. In the Komati Basin, these traditional methods of water allocation led to frequent conflicts among users and with water managers. However, the introduction of the modified FWARCS, which assigns available water in the system to water users according to the proportions of their water entitlements and allows water to be banked in reservoirs, appears to be a solution to some of these problems. This method allows water users to decide when and how much of that entitlement they may use. Since the implementation of the modified FWARCS technique in the Komati Basin in 2002, the regulation, transparency and efficiency of operating the system improved and subsequently the number of disputes over water has declined. South Africa improved from an overuse of 8.2 Mm3 in 2002/03 water year to realize a saving of 29.5 Mm3 in 2005/06. Similarly, Swaziland improved from an overuse of 3.9 Mm3 in 2002/03 to achieve a saving of 14.6 Mm3 in 2005/06. Users have recognised and embraced the transparency and flexibility of the modified FWARCS. They choose, as the need and opportunity arise, when and how much water they utilise, whether to “bank” and/or “trade” the water they save subject to the conditions of their entitlements. The implementation of the modified FWARCS was also made successful by the existence of proper institutional structures, appropriate decision support tools, good water measurement infrastructure and reliable water accounting systems. The establishment, development and utilization of these elements of water management, as well as the challenges encountered in relation to the adoption of modified FWARCS in the Komati Basin are discussed in this paper.