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Migration to South Africa is motivated by the pursuit of employment, safety, and improved living conditions. However, immigrants encounter significant challenges, such as restricted access to essential services, which were exacerbated by the COVID-19 pandemic. This paper investigates the impact of the COVID-19 pandemic on Malawian immigrants in South Africa, addressing the lack of attention given to this immigrant population by highlighting their vulnerabilities. Using a qualitative exploratory and descriptive approach, in-depth interviews were conducted with 24 Malawi immigrants who were over 18 years old and had established residency in South Africa before the onset of the COVID-19 pandemic. Five key stakeholders were also interviewed for additional perspectives and to ensure triangulation and improve data reliability. The interviews were transcribed verbatim and analyzed using thematic analysis strategies and coding with Nvivo12 software. The study highlighted the exacerbated struggles of Malawian immigrants in South Africa amid the COVID-19 pandemic, uncovering systemic discrimination in healthcare, marked by longer wait times and reluctance from health workers to treat undocumented immigrants. The study also revealed a dire security situation, with immigrants living in high-crime areas and feeling particularly targeted due to their foreign status, a situation worsened by the pandemic's economic effects. Additionally, the economic downturn induced by COVID-19 significantly impacted employment opportunities, with many immigrants facing prolonged unemployment and job losses, especially in sectors where they traditionally found work. The detailed accounts of participants highlight not only the multifaceted challenges imposed by the pandemic but also the critical need for inclusive policies and support systems that ensure healthcare access, safety, and economic resilience for immigrants, particularly during global health emergencies. Future research should focus on effective interventions for socioeconomic integration and well-being, particularly for immigrants from other African countries. [ABSTRACT FROM AUTHOR]

Stochastic programming has become increasingly vital in energy applications, especially in the context of the growing need for renewable energy solutions. This paper presents a significant advancement in this field by introducing an efficient and robust algorithm for optimally sizing hybrid renewable energy systems. Utilizing a two-stage stochastic programming approach, the proposed algorithm addresses the challenges posed by the unpredictability of renewable energy sources. The proposed solution leverages the three-block alternating direction method of multipliers (ADMM), a cutting-edge technique that facilitates parallel computation and enhances computational efficiency. The distinctiveness of this method lies in its ability to solve complex stochastic optimization problems without compromising the mathematical integrity of the model. This is achieved by applying first-order optimality conditions, ensuring both robustness and efficacy. To demonstrate the practical applicability and superiority of the algorithm, a case study was conducted in a rural area of South Africa. The proposed algorithm was applied to design an optimal hybrid renewable energy system, and its performance was compared against traditional methods such as progressive hedging and Monte Carlo techniques. Results affirm the superiority of the approach, saving approximately 8.16% capital cost when compared to progressive hedging. In addition, the proposed algorithm outperforms the Monte Carlo method both in terms of CPU time and the number of cost function evaluations. [ABSTRACT FROM AUTHOR]

Small ruminant production is one of the most important animal productions for food security in the world, especially in the developing world. Gastrointestinal nematode (GIN) infection is a threat to this animal's production. Conventional drugs that are used to control these parasites are losing their efficacy due to the development of resistant parasites. These drugs are not biologically degradable, taint meat products and are also expensive for communal farmers. Hence, research is now exploring ethnomedicinal anthelmintic plants for an alternative remedy. The objective of this paper was to review ethnomedicinal plants as a potential alternative to unsustainable commercial anthelmintics. This review sought to understand common GINs infecting ruminants, resistance manifestation in GINs to conventional treatment, reasons communal farmers choose ethnomedicine, and modes of action in anthelmintic plants. It also examined the usage of plants and plant parts, dosage forms, methods for improving bioactivity, convectional validation procedures, and restrictions on ethnomedicinal plant use as anthelmintics in ethnomedicine. Such insight is essential, as it highlights the importance of ethnoveterinary medicine and ways to adopt or improve it as a potential alternative to conventional anthelmintics. [ABSTRACT FROM AUTHOR]

Understanding the factors that influence COVID-19 transmission is essential in assessing and mitigating the spread of the pandemic. This study focuses on modeling the impact of air pollution and meteorological parameters on the risk of COVID-19 transmission in Western Cape Province, South Africa. The data used in this study consist of air pollution parameters, meteorological variables, and COVID-19 incidence observed for 262 days from April 26, 2020, to January 12, 2021. Lagged data were prepared for modeling based on a 6-day incubation period for COVID-19 disease. Based on the overdispersion property of the incidence, negative binomial (NB) and generalised Poisson (GP) regression models were fitted. Stepwise regression was used to select the significant predictors in both models based on the Akaike information criterion (AIC). The residuals of both NB and GB regression models were autocorrelated. An autoregressive integrated moving average (ARIMA) model was fitted to the residuals of both models. ARIMA (7, 1, 5) was fitted to the residuals of the NB model while ARIMA (1, 1, 6) was fitted for the residuals of the GP model. NB + ARIMA (7, 1, 5) and GP + ARIMA (1, 1, 6) models were tested for performance using root mean square error (RSME). GP + ARIMA (1, 1, 6) was selected as the optimal model. The results from the optimal model suggest that minimum temperature, ambient relative humidity, ambient wind speed, PM 2.5 , and NO 2 at various lags are positively associated with COVID-19 incidence while maximum relative humidity, minimum relative humidity, solar radiation, maximum temperature, NO, PM load, PM 10 , SO 2 , and NO X at various lags have a negative association with COVID-19 incidence. Ambient wind direction and temperature showed a nonsignificant association with COVID-19 at all lags. This study suggests that meteorological and pollution parameters play a vital independent role in the transmission of the SARS-CoV-2 virus. [ABSTRACT FROM AUTHOR]

Soil crusting (surface sealing) is widespread and serious in ecotouristic game parks and reserves in southern Africa, and especially South Africa. In this study, mineral soil crusts were found to be the problem in the Dinokeng Game Reserve (DGR), South Africa. Large areas of bare soil crusted areas were found in this reserve. The cause of this crusting was found to be historical agricultural practices such as cultivation with maize on non-arable soils and overgrazing by cattle. Negative impacts of soil crusting include reduction of water infiltration, leading to increased runoff and erosion and induced drought; inhibiting soil aeration; inhibiting germination and seedling emergence; and inhibiting root functioning and development. In this study in the DGR, a bare crusted area, where cultivation was abandoned 50 years before and there has been no recovery to rangeland since then, was selected for a field trial to determine the effectiveness of the application of various soil ameliorants on soil crust alleviation and improvement of water infiltration rate. The following ameliorants were evaluated: polyacrylamide (PAM) at levels of 5 and 20 kg/ha, gypsum at 2.5 t/ha, and molasses meal at 5 t/ha, as well as combinations of PAM and molasses meal, PAM and gypsum and gypsum and molasses meal. Brush packing, without any ameliorant applied, was also included as treatment, as well as a control with no treatments. PAM treatments increased final infiltration rate (FIR) by between 100–206%. The high efficacy of the lowest PAM treatment is at a cost of only USD 15 per hectare economically important. On the studied soil gypsum application reduced FIR by 81%, while molasses meal had minimal effect. These ameliorants can therefore not be recommended on such soil. [ABSTRACT FROM AUTHOR]