Search Results (652)

Rural roads are critical for connecting isolated communities to essential services such as education and health and administrative services, as well as production and market opportunities in low-income countries. More than 70% of movements of people and goods in Sub-Saharan Africa are heavily reliant on rural transport systems, using both motorised but mainly alternative means of transport. However, rural roads often suffer from poor construction due to the use of low-strength, in situ soils and limited financial resources, leading to premature failures and subsequent traffic disruptions with significant economic losses. This study investigates the use of rice husk ash (RHA), a waste byproduct from rice production, as a sustainable supplement to Ordinary Portland Cement (OPC) for soil stabilisation in order to increase durability and sustainability of rural roads, hence limit recurrent maintenance needs and associated transport costs and challenges. To conduct this study, soil samples collected from Mulungushi, Zambia, were treated with combinations of 6–10% OPC and 10–15% RHA by weight. Laboratory tests measured maximum dry density (MDD), optimum moisture content (OMC), and California Bearing Ratio (CBR) values; the main parameters assessed to ensure the quality of road construction soils. Results showed that while the MDD did not change significantly and varied between 1505 kg/m³ and 1519 kg/m³, the OMC increased hugely from 19.6% to as high as 26.2% after treatment with RHA. The CBR value improved significantly, with the 8% OPC + 10% RHA mixture achieving the highest resistance to deformation. These results suggest that RHA can enhance the durability and sustainability of rural roads and hence improve transport systems and subsequently improve socioeconomic factors in rural areas. Full article

This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). By integrating error-driven task sequencing and real-time error feedback with the PSBFO algorithm, we developed a comprehensive framework tailored to the unique challenges of gearbox assembly. The PSBFO algorithm combines the global search capabilities of PSO with the local refinement of BFO, creating a unified framework that efficiently explores task sequencing, minimizing misalignment and torque misapplication assembly errors. The methodology results in a 38% reduction in total assembly errors, improving both process accuracy and efficiency. Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. The 50 to 5 error reduction represents a significant decrease in assembly errors from an unoptimized (50) to an optimized (5) sequence, achieved through the PSBFO algorithm, by minimizing dimensional deviations, torque mismatches, and alignment errors across 26 critical gearbox components. While the primary focus is on wind turbine gearbox applications, this approach has the potential for broader applicability in error-prone assembly processes in industries such as automotive and aerospace, warranting further validation in future studies. Full article

The intensifying global competition for cobalt resources and the increasing likelihood of trade decoupling and disruption are profoundly impacting the global energy transition. In a globalized trade environment, a decline in cobalt supply from exporting countries can spread through the trade network, negatively affecting demand countries. Quantitative analysis of the negative impacts of export supply declines in various countries can help identify early risks in the global supply chain, providing a scientific basis for energy security, industrial development, and policy responses. This study constructs a trade network using trade data on metal cobalt, cobalt powder, cobalt concentrate, and ore sand from the upstream (mining, selection, and smelting) stages of the cobalt industry chain across 155 countries and regions from 2000 to 2023. Based on this, an impact diffusion model is established, incorporating the trade volumes and production levels of cobalt resources in each country to measure their resilience to shocks and determine their direct or indirect dependencies. The study then simulates the impact on countries (regions) when each country’s supply is completely interrupted or reduced by 50%. The results show that: (1) The global cobalt trade network exhibits a ‘one superpower, multiple strong players’ characteristic. Congo (DRC) has a far greater destructive power than other countries, while South Africa, Zambia, Australia, Russia, and other countries have higher destructive power due to their strong storage and production capabilities, strong smelting capabilities, or as important trade transit countries. (2) The global cobalt trade network primarily consists of three major risk areas. The African continent, the Philippines and Indonesia in Southeast Asia, Australia in Oceania, and Russia, the United States, China, and the United Kingdom in Eurasia and North America form the primary risk zones for global cobalt trade. (3) When there is a complete disruption or a 50% reduction in export supply, China will suffer the greatest average demand loss, far exceeding the second-tier countries such as the United States, South Africa, and Zambia. In contrast, European countries and other regions worldwide will experience the smallest average demand loss. Full article

The Sustainable Development Goals seek to achieve universal, adequate, and equitable access to drinking water and sanitation by the year 2030. Yet, significant and persistent disparities in water and sanitation access exist, with rural and low-income households in Sub-Saharan Africa exhibiting some of the lowest levels. This paper uses household surveys from rural villages in Zambia’s Western Province to identify, highlight, and examine spatial barriers to improved water and sanitation. Most households included in the study area drink unimproved water, including surface water, and either use unimproved sanitation facilities or practice open defecation. Access to improved water sources and improved sanitation in the study area lags behind the rest of rural Zambia. Beyond the distance to urban areas that makes piped water and sanitation expensive, the location of these villages in the Barotse Floodplain necessitates seasonal migration, which creates barriers to universal access to improved water and sanitation. Full article

Rural areas around the world are increasingly dealing with energy and environmental challenges. These challenges are particularly acute in developing countries, where persistent reliance on traditional energy sources—such as wood fuel—intersects with concerns about forest conservation and energy sustainability. While wood fuel use is often portrayed as unsustainable, it is important to acknowledge that much of it remains ecologically viable and socially embedded. This study explores the role of rural entrepreneurs in shaping low-carbon transitions at the intersection of household energy practices and environmental stewardship. Fieldwork was carried out in four rural Zambian communities in 2016 and complemented by 2024 follow-up reports. It examines the connections between household energy choices, greenhouse gas emissions, and forest resource dynamics. Findings reveal that over 60% of rural households rely on charcoal for cooking, with associated emissions estimated between 80 and 150 kg CO₂ per household per month. Although this is significantly lower than the average per capita carbon footprint in industrialized countries, such emissions are primarily biogenic in nature. While rural communities contribute minimally to global climate change, their practices have significant local environmental consequences. This study draws attention to the structural constraints as well as emerging opportunities within Zambia’s rural energy economy. It positions rural entrepreneurs not merely as policy recipients but as active agents of innovation, environmental monitoring, and participatory resource governance. A model is proposed to support sustainable rural energy transitions by aligning forest management with context-sensitive emissions strategies. Full article

Job satisfaction in sub-Saharan Africa is crucial as it directly impacts employee productivity, retention, and overall economic growth, fostering a motivated workforce that drives regional development. In sub–Saharan Africa, poor remuneration, limited professional development opportunities, and inadequate working conditions impact satisfaction. This study examined job-satisfaction predictors among health workers in primary healthcare settings across eight countries: Ethiopia, Kenya, Malawi, Senegal, South Sudan, Tanzania, Uganda, and Zambia. A cross-sectional study surveyed 1711 health workers, assessing five dimensions: employer–2employee relationships, remuneration and recognition, professional development, physical work environment, and supportive supervision. The study was conducted from October 2023 to March 2024. The job-satisfaction assessment tool was adopted from a validated tool originally developed for use in low-income healthcare settings. The tool was reviewed by staff from all the country offices to ensure contextual relevance and organization alignment. The responses were measured on a five-point Likert scale: 0: Not applicable, 1: Very dissatisfied, 2: Dissatisfied, 3: Neutral, 4: Satisfied, and 5: Very satisfied. The analysis employed descriptive and multivariable regression methods. Job satisfaction varied significantly by country. Satisfaction with the employer–employee relationship was highest in Zambia (80%) and lowest in Tanzania (16%). Remuneration satisfaction was highest in Senegal (63%) and Zambia (49%), while it was very low in Malawi (9.8%) and Ethiopia (2.3%). Overall, 44% of respondents were satisfied with their professional development, with Uganda leading (62%) and Ethiopia having the lowest satisfaction level (29%). Satisfaction with the physical environment was at 27%, with Uganda at 40% and Kenya at 12%. Satisfaction with supervisory support stood at 62%, with Zambia at 73% and Ethiopia at 30%. Key predictors of job satisfaction included a strong employer–employee relationships (OR = 2.20, p < 0.001), fair remuneration (OR = 1.59, p = 0.002), conducive work environments (OR = 1.71, p < 0.001), and supervisory support (OR = 3.58, p < 0.001. Improving the job satisfaction, retention, and performance of health workers in sub-Saharan Africa requires targeted interventions in employer–employee relationships, fair compensation, supportive supervision, and working conditions. Strategies must be tailored to each country’s unique challenges, as one-size-fits-all solutions may not be effective. Policymakers should prioritize these factors to build a motivated, resilient workforce, with ongoing research and monitoring essential to ensure sustained progress and improved healthcare delivery. Full article

The study examines changes in household food security and identifies their key determinants in Zambia by comparing the pre-pandemic period to the COVID-19 pandemic period. Using nationally representative surveys from 2015 and 2021 and the coarsened exact matching (CEM) approach, 8650 households were matched for comparison. Two complementary food security measures are analysed using multinomial logit regression models: household expenditure share, representing economic vulnerability, and household dietary diversity score (HDDS), representing diet quality. The results show that household food expenditure share significantly increased from 53.8% to 61.4%, indicating increased economic vulnerability. Notably, household dietary diversity improved from 7.1 to 8.2 out of 12, indicating better dietary quality. Consistent determinants of food security—such as household size, education level, marital status, region, and employment—remained significant, but their protective effects weakened during the pandemic. Specifically, the protective effect of education declined, urban households became relatively more vulnerable, and wealthier households experienced minimal changes. The study recommends targeted interventions, including expanding social protection programmes for economically vulnerable households, supporting informal food markets, enhancing rural–urban food supply linkages, and promoting nutrition education to ensure diverse, affordable food access during crises. Full article

Background: Adolescent girls and young women (AGYW) who engage in alcohol and substance abuse face more significant health and social consequences compared to the general population. This study evaluated the prevalence and associated factors of alcohol abuse and substance use among AGYW in Namibia. Methods: We conducted a retrospective analysis of programmatic data from AGYW aged 10–24 who participated in the Determined, Resilient, Empowered AIDS-free, Mentored, and Safe (DREAMS) component of the Reducing HIV Vulnerability: Integrated Child and Youth Health (REACH) Project HOPE Namibia from March to December 2024. Data analysis was conducted employing chi-squared tests alongside binomial and multinomial logistic regression. Results: Among the 19,662 participants included in this analysis, 2068 (10.5%) abused alcohol and/or substances in the previous six months. Participants who were HIV-negative or did not know their status (AOR = 1.57, 95% CI (1.15–2.14), and AOR = 1.50, 95% CI (109–2.07), respectively), from outside Windhoek, those who had failed or repeated school in the previous year (COR = 1.77, 95% CI (1.54–2.05)), those not disabled (AOR = 1.27, 95% CI (1.06–1.52)), those who had dropped out of school or had completed their studies, and those with no adult emotional support (AOR = 1.25, 95% CI (1.11–1.40)), were more likely to have abused alcohol and/or substances recently. In contrast, participants who were not depressed were less likely to have recently abused alcohol and substances. Conclusions: The prioritization of strategies to identify AGYW experiencing depression and to provide them with treatment is essential. Moreover, it is important to encourage parents and guardians to provide emotional support to AGYW, as it prevents them from abusing alcohol and substances. Full article

Studies examining the role of chikanda orchids in bolstering rural livelihoods coupled with the associated socio-economic intricacies remain absent, especially in African settings. This study examined the contribution of chikanda orchids in supporting rural livelihoods, taking into account socio-economic influences through a case study of the Mwinilunga District of northwestern Zambia. The study employed a mixed methods approach using 303 semi-structured questionnaires, complemented by three focus group discussions and nine in-depth interviews. Study findings showed that revenue generated from chikanda orchid sales supported rural livelihoods and served a crucial function in addressing food scarcity challenges. Income derived from chikanda orchid sales accounted for 30.8% of total household income and exhibited an income equalization effect of 8% among households. Participation in harvesting chikanda orchids exhibited a significant correlation with gender (χ² = 6; p < 0.05) and marital status (χ² = 8; p < 0.05). This study showed the significance of chikanda orchids in supporting livelihoods, including socio-economic influences, particularly for poorer households that exhibit vulnerability to food deficits. Consequently, the need to develop effective chikanda orchid management strategies that are locally tailored and acknowledge the socio-economic intricacies associated with the chikanda orchids trade is fundamental. Full article

Bisphenol S (BPS), a key ingredient in polycarbonate plastics and epoxy resins, is a known endocrine-disrupting compound that poses significant risks to human health and the environment. As such, the development of rapid and reliable analytical techniques for its detection is essential. In this work, we present a newly engineered electrochemical sensor designed for the sensitive and selective detection of BPS using a straightforward and effective fabrication approach. The sensor was constructed by grafting molecularly imprinted polymers (MIPs) onto vinyl-functionalized multiwalled carbon nanotubes (f-MWCNTs). Ethylene glycol dimethacrylate and acrylamide were used as the cross-linker and functional monomer, respectively, in the synthesis of the MIP layer. The resulting MIP@f-MWCNT nanocomposite was characterized using Fourier-transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM). The MIP@f-MWCNT material was then combined with chitosan, a biocompatible binder, to fabricate the final MIP@f-MWCNT/chitosan-modified glassy carbon electrode (GCE). Electrochemical evaluation showed a broad linear detection range from 1 to 60 µM (R² = 0.992), with a sensitivity of 0.108 µA/µM and a detection limit of 2.00 µM. The sensor retained 96.0% of its response after four weeks and exhibited high selectivity against structural analogues. In spiked plastic extract samples, recoveries ranged from 95.6% to 105.0%. This robust, cost-effective, and scalable sensing platform holds strong potential for environmental monitoring, food safety applications, and real-time electrochemical detection of endocrine-disrupting compounds like BPS. Full article

Background/Objectives: Tuberculosis (TB) and HIV co-infection pose significant challenges in resource-limited settings, contributing to multi-drug-resistant TB when treatment fails. This study aimed to identify determinants of TB treatment outcomes among HIV/TB co-infected patients in Lusaka, Zambia. Methods: A retrospective cohort study was conducted at Chilenje, Chipata, and Chawama level one hospitals, using systematic sampling to select 586 patient files. Data were analyzed with SPSS version 23, employing descriptive statistics, chi-square tests, and hierarchical logistic regression. Results: Among the study population (n = 586), consisting predominantly of working-age adults (25–44 years: 61.6%) and males (56.5%), treatment success was 81.3%, with a 12.5% mortality rate across treatment phases. Baseline smear-negative TB, viral load (100,000–199,999 copies/mL), diabetes without hypertension, and negative smear at follow-up independently predicted treatment outcomes. Higher treatment failure odds were linked to smear-negative TB, high viral load, and hypertension–diabetes comorbidity, while CD4 count and HIV treatment status showed no independent effects. Conclusions: These findings underscore the influence of viral load, TB type, comorbidities, and sputum conversion on treatment success, emphasizing the need for targeted monitoring and integrated care, particularly in the continuation phase, to enhance outcomes in this vulnerable population. Full article

To address the persistent challenge of low recognition accuracy in precious wood species classification, this study proposes a novel methodology for identifying Pterocarpus santalinus, Pterocarpus tinctorius (PTD), and Pterocarpus tinctorius (Zambia). This approach synergistically integrates artificial neural networks (ANNs) with advanced image feature extraction techniques, specifically Fast Fourier Transform, Gabor Transform, Wavelet Transform, and Gray-Level Co-occurrence Matrix. Features were extracted from both transverse and longitudinal wood sections. Fifteen distinct ANN models were subsequently developed: hybrid-section models combined features from different sections using a single algorithm, while multi-algorithm models aggregated features from the same section across all four algorithms. The dual-section hybrid wavelet model (LC4) demonstrated superior performance, achieving a perfect 100% recognition accuracy. High accuracies were also observed in the four-parameter combination models for longitudinal (L5) and transverse (C5) sections, yielding 97.62% and 91.67%, respectively. Notably, 92.31% of the LC4 model’s test samples exhibited an absolute error of ≤1%, highlighting its high reliability and precision. These findings confirm the efficacy of integrating image processing with neural networks for fine-grained wood identification and underscore the exceptional discriminative power of wavelet-based features in cross-sectional data fusion. Full article

Emerging but limited evidence suggests that HIV infection does not affect in-hospital COVID-19 mortality, regardless of the prevalence of HIV infection in most parts of sub-Saharan Africa, especially the southern Africa region, and Zambia, Lusaka District in particular, is not an exception. Therefore, this study aimed to determine the effect of HIV infection, demographics, and clinical factors on mortality among hospitalized COVID-19 patients at Levy Mwanawasa University Teaching Hospital (LMUTH). A cross-sectional study was conducted with a sample size of 698 adults admitted for COVID-19 at LMUTH from 18 March 2020 to 31 December 2021. For all statistical analysis of data, STATA statistical software, version 15 MP (College Station, TX 77845, USA) was used—ensuring that appropriate statistical techniques were applied to the data. Unadjusted and adjusted logistic regressions were conducted to model COVID-19 mortality among COVID-19 patients based on their HIV status while controlling for five predictor variables. Based on the results, the best predictors of in-hospital COVID-19 mortality were HIV status, number of comorbidities, age in years, smoking, and alcohol intake. The results suggest that COVID-19 mortality among those with HIV and those without HIV infection was different. People living with HIV infection had increased odds of COVID-19 mortality compared to those without HIV. The results further suggested that a unit increase in age was associated with increased odds of COVID-19 mortality. Furthermore, drinking alcohol and having two or more comorbidities increased the odds of COVID-19 mortality compared to not drinking alcohol, having no comorbidity, or having a comorbidity. This study, therefore, concludes that HIV infection has a significant effect on COVID-19 mortality among patients hospitalized at LMUTH and that the proportion of COVID-19 mortality in the HIV-infected group is relatively higher than in the uninfected group. Therefore, there is a need for close monitoring of COVID-19 patients with HIV infection. Full article

Agriculture is a key sector for economic growth, food security, and rural livelihoods within the member nations of the Southern African Development Community (SADC). However, the agricultural systems throughout the SADC regions face serious threats from climate change, which is seen through temperature rises, irregular rainfall patterns, and the rising frequency of droughts. The study examines the impacts of climate change on agricultural productivity in four SADC countries: South Africa, Zambia, Zimbabwe, and Malawi. It also assesses the impact of institutional structures, policy initiatives, and technological advancements in enhancing agricultural resilience to climate change. The Panel Autoregressive Distributed Lag (PARDL) model was employed to assess short and long run impact of climate change on agricultural productivity. The findings reveal that precipitation significantly increases agricultural productivity in the long run, but not in the short run. In addition, governance inefficiencies, which are measured by control of corruption index have negative long run impacts on agricultural productivity. The estimated speed of adjustment (ECT: −0.9557) demonstrated a strong long run equilibrium relationship, indicating that agricultural productivity converges to its long run trend regardless of short run fluctuations. In conclusion, the findings of this study provide essential knowledge to assist policymakers, researchers, and development agencies in the creation of evidence-based policies aimed at improving agricultural resilience to climate change across SADC member countries. Full article

Zoonotic diseases present a growing public health challenge, particularly in sub-Saharan Africa (SSA) due to close interactions between humans and animals and poor diagnostic capacity. This pilot study investigated human exposure to zoonotic pathogens in Zambia among 47 suspected COVID-19 patients from whom nasopharyngeal samples were collected between November 2020 and February 2021 at two major COVID-19 referral centers in Lusaka. Using metagenomic next-generation sequencing (mNGS), the study identified a diverse range of pathogens, including bacterial, fungal, viral, and parasitic species. The prevalence of zoonotic pathogens was 57.4%. Noteworthy zoonoses included Bacillus anthracis, Sporothrix schenckii, Listeria monocytogenes, Yersinia pestis, Streptococcus suis, Vibrio parahaemolyticus, Brucella melitensis, Rickettsia prowazekii, Shewanella algae, Rickettsia japonica, Coxiella burnetii, Leptospira borgpetersenii, Erysipelothrix rhusiopathiae, Brucella abortus, Bartonella quintana, Banna virus, Vibrio alginolyticus, Bartonella clarridgeiae, Rickettsia canadensis, Leishmania braziliensis, Trypanosoma brucei, Pasteurella multocida, and Arcobacter butzleri. Despite moderate diversity in the microbial community, no significant demographic or health-related factors, including age, gender, or comorbidities such as HIV, were found to be statistically associated with zoonotic pathogen infection. The findings provide valuable data on the presence of zoonotic pathogens in humans in Zambia and highlight the need for more comprehensive research into zoonotic diseases in both clinical and non-clinical settings. Full article