Search Results (633)

Rotavirus alphagastroenteritidis remains the leading cause of severe gastroenteritis in children under five years, despite widespread vaccine use. The COVID-19 pandemic disrupted healthcare and vaccination delivery, while non-pharmacological interventions may have influenced R. alphagastroenteritidis transmission. We conducted hospital-based surveillance of R. alphagastroenteritidis gastroenteritis at Queen Elizabeth Central Hospital (QECH) in Blantyre, Malawi, from October 2019 to October 2024. Children under five presenting with acute gastroenteritis were enrolled; 99.1% of vaccine-eligible participants had received at least one R. alphagastroenteritidis vaccine dose. Stool samples were tested for R. alphagastroenteritidis by enzyme immunoassay (EIA) and genotyped using RT-PCR. Among 1135 enrolled children, 29.1% (330/1135) were R. alphagastroenteritidis-positive. Cases occurred year-round except for December 2020–January 2021, when no R. alphagastroenteritidis infections were detected, and February–March 2023, when no samples were collected. The prevalence varied significantly by age group between children greater than 23 months of age to the rest of the age groups (<6 months, 6–11 months, and 12–22 months) (p = 0.0046). The most common R. alphagastroenteritidis G-genotypes were G3 (38.7%), G2 (25.4%), and G12 (17.2%), with G2 emerging as the predominant strain from June 2023. G3P[8] was the most frequent G–P combination (25%). Its overall prevalence did not change during the pandemic; however, genotype distribution shifted compared to pre-COVID-19 patterns. Sustained surveillance and genomic analyses are essential to monitor evolving strain dynamics and inform vaccine policy. Full article

Fecal sludge (FS) requires effective management to mitigate environmental and public health risks and enable resource recovery. This study evaluated the effects of microwave (MW) treatment on FS characteristics and subsequent anaerobic digestion (AD) performance. MW treatment raised FS temperatures to ~96 °C, reducing FS volume by 50% and inducing three thermal phases. Soluble chemical oxygen demand (sCOD) showed a multi-phase pattern, with a maximum solubilization of 29.8% during initial heating due to the solubilization of proteins and carbohydrates. Scanning electron microscopy (SEM) revealed morphological changes, while Fourier transform infrared (FTIR) spectroscopy confirmed that core functional groups remained unchanged. MW-pretreated FS enhanced AD performance, achieving a 17% increase in cumulative methane yield, alongside 18% and 33% improvements in organic loading and methane production rates, respectively. MW treatment influenced the phase distribution of digestate components, showing a shift in nutrient portioning towards the liquid fraction. These results suggest that integrating MW pretreatment into FS management systems can improve energy recovery, reduce treatment costs, and support resource-efficient sanitation solutions. Full article

Background/objectives: Antimicrobial resistance (AMR) is a growing public health concern, and misuse of antibiotics in livestock farming contributes to its emergence. In Blantyre, Malawi, small-scale pig and poultry farming is widespread, but the knowledge, attitudes, and practices (KAP) driving antimicrobial use (AMU) remain poorly understood. This study aimed to assess the KAP regarding AMU and manure management among pig and poultry farmers in Blantyre, Malawi. Methods: This cross-sectional study surveyed 118 randomly selected farmers to assess AMU patterns, sources of antibiotics, adherence to withdrawal periods, disposal practices, and awareness of AMR and regulations. Data was collected using a structured questionnaire and analyzed with descriptive statistics and inferential tests (with statistical significance set at p < 0.05). Results: Antibiotic use was reported by 88% of farmers, primarily for therapy (93.3%) and prophylaxis (85.6%), including for viral diseases such as Newcastle disease in poultry and African swine fever in pigs. Oxytetracycline (91.5%), penicillin (50.8%), and trimethoprim-sulfamethoxazole (39.8%) were the most used antibiotics, predominantly sourced from agrovet shops (73.7%). While 61% of farmers knew antibiotic misuse could lead to AMR, significant gaps were observed: 68.6% had no formal training, 55.9% were unaware of regulations, and 42% sold/consumed products before the end of the withdrawal period. Most farmers disposed of expired antibiotics (80.5%) and packaging (92.4%) in household waste. Higher education and prior training were significantly associated with good knowledge. Conclusions: This study reveals significant knowledge–practice gaps and high-risk behaviors, such as misuse for viral diseases and unsafe disposal, that exacerbate AMR risks. Interventions must prioritize targeted farmer education, strengthening of veterinary extension services, and stricter regulation of agrovet shops to promote antimicrobial stewardship and support Malawi’s National Action Plan on AMR. Full article

Background: Patient monitors assist caregivers in identifying deterioration earlier by using threshold alarms. Not all of the threshold alarms necessitate immediate action, but some are a result of the triggering of a physiological event. We aim to use pattern recognition techniques to identify threshold alarm signal patterns before the onset of critical illness, thereby enabling the faster and more effective detection of clinical deterioration and supporting better clinical decision-making. Method: Secondary data from 774 pediatric patients were extracted from the IMPALA Project conducted in the High Dependency Unit (HDU) at Queen Elizabeth and Zomba Central Hospitals in Malawi. The threshold alarm data were generated from the vital signs using WHO age cut-offs and GOAL3 age cut-offs. Time-segmented alarm analysis was conducted to examine the distribution of threshold alarms around each vital sign 8 h before the onset of critical illness events. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) was used to generate threshold alarm signal patterns for each signal per individual before the onset of a critical illness event. We used three machine learning approaches, random forest, support vector machine, and decision tree, to learn threshold alarm patterns in signals preceding critical illness events. Results: The total threshold alarm summed up to (3,910,083) in total for WHO and (2,041,740) for GOAL3. Temporal distributions of ECGRR, ECGHR and oxygen saturation rate (SPO2) threshold alarms were observed, revealing patterns before the onset of the critical illness events. A pattern of most threshold alarms was distributed around (40–60) for ECGRR upper threshold alarms and (0–20) for ECGRR lower threshold alarms, (80–85) for ECGHR lower threshold alarms and (140–160) for ECGHR upper threshold alarms, and (85–90) for SPO2 for death (CPR and PICU), around WHO threshold alarms. For sepsis, most of these threshold alarms were distributed around (40–50) of ECGRR upper threshold alarms and (0–20) for ECGRR lower threshold alarms, (150–180) for ECGHR upper threshold alarms, and (85) for SPO2 for WHO threshold alarms, and most of the threshold alarms had a duration of less than 30 s. The results indicate that the random forest classifier performed better in learning the threshold patterns, with an accuracy of 93% and an area under the curve of 92, compared to using the support vector machine learning model and decision tree, which had an accuracy from a classification report of 85% and 94%, with low death and sepsis precision, recall, and F1-Score. Conclusions: The analysis of threshold alarm data before critical illness events has provided valuable insights into threshold alarm patterns associated with death and sepsis. The data revealed distinct patterns in ECGRR, ECGHR, and SPO2 signals, and most of the threshold alarms were in the lower duration. The random forest classifier effectively distinguished these learned patterns around death and sepsis events compared to other algorithms. Further studies are required on the use of algorithms on all vital sign signal features in clinical settings. Full article

Prepubescent children and young adolescents (ages 7–14) are in a critical developmental stage for establishing the foundations of healthy sexual behavior. Increasing rates of precocious puberty, combined with limited access to accurate and age-appropriate sexual health education, heighten the vulnerability of this age group to sexual health risks. These risks include early and often coerced sexual initiation, exposure to sexual abuse, and consequent outcomes such as sexually transmitted infections and early pregnancies. However, comprehensive cross-regional analyses and evidence-based interventions addressing the sexual health needs of this age group remain limited. Addressing this gap promotes mutual learning, context-specific adaptation, and global alignment of sexual health support efforts, crucial for achieving the Sustainable Development Goal target of universal access to sexual and reproductive health care. This scoping review aims to map the available evidence on the scope and characteristics of sexual health interventions for prepubescents and young adolescents in the United States and Sub-Saharan Africa. The proposed scoping review will be conducted in accordance with the Arksey and O’Malley framework and Joanna Briggs Institute (JBI) methodology for scoping review. A systematic search of English-language articles published from 2010–2025 will be conducted across PubMed, CINAHL, PsycINFO, Scopus, Web of Science, ERIC, and African Index Medicus. Five reviewers will screen the articles in Covidence and independently assess full-text articles using a standardized data extraction form. Discrepancies will be resolved through discussion and with a sixth reviewer. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Data will be summarized and synthesized to identify patterns in interventions, delivery methods, outcomes, and implications for practice, research, and policy. Comparative and gap analyses will highlight similarities, differences, and priorities for future research and interventions. An adolescent sexual health expert will help validate and contextualize findings. Results can guide strategies to address shared challenges and advance universal access to sexual health support for prepubescents and young adolescents. Full article

Urban and peri-urban farmers in Malawi increasingly use treated and untreated wastewater for vegetable production, but little is known about the extent of heavy metal accumulation in both exotic and indigenous vegetables, particularly with respect to differences between edible tissues (leaves vs. stems). This study addresses this gap by measuring the concentrations of cadmium (Cd), chromium (Cr), lead (Pb), zinc (Zn), and copper (Cu) in wastewater, soils, and six vegetables including three exotic and three indigenous irrigated with effluent from the Soche Wastewater Treatment Plant in Blantyre. Metal concentrations were determined using Atomic Absorption Spectrophotometry. Wastewater contained Zn (0.01 ± 0.001 mg/L) and Cu (0.02 ± 0.018 mg/L), both below World Health Organization (WHO) and Malawi Bureau of Standards (MBS) limits (Zn: 0.2 mg/L; Cu: 2 mg/L), while Cd, Cr, and Pb were below detection limit. In soils, Zn reached 56.4 ± 0.5 mg/kg, exceeding the WHO limit of 36 mg/kg; other metals remained within WHO permissible values. Vegetables showed species- and tissue-specific variation in metal accumulation: Cr reached 4.65 mg/kg in Cucurbita moschata stems, Cd up to 0.31 mg/kg in Amaranthus retro-flexus leaves, and Pb up to 4.09 mg/kg in Brassica rapa stems—all above FAO/WHO permissible limits (2.3, 0.2, and 0.3 mg/kg, respectively). Duncan’s post hoc analysis confirmed significant differences (p < 0.05) across matrices and plant parts, with leaves generally accumulating more Zn and Cu than stems. Principal component analysis (PCA) revealed that Zn, Cu, Cr, and Pb in the wastewater-soil-vegetable system largely share a common source, likely wastewater effluent and historical soil contamination, while Cd showed a more sporadic distribution, highlighting differential accumulation pathways. Health risk assessments revealed high Health Risk Index (HRI) values, with Brassica rapa stems (HRI = 92.3) and Brassica rapa subsp. chinensis leaves (HRI = 82.2) exceeding the safe threshold (HRI > 1), indicating potential chronic risks. This study reveals potential health risks associated with wastewater irrigation due to heavy metal accumulation in edible vegetables, and therefore recommends further research on metal speciation, seasonal variation, and bioaccumulation at different crop growth stages. Full article

Assessing seismic vulnerability is a critical step in evaluating the resilience of existing buildings, and fragility curves are widely used to quantify the probability of damage under varying levels of seismic intensity. However, traditional methods for generating these curves often rely on generalized assumptions that may not accurately capture the seismic behavior of diverse building types within a region. This limitation is particularly evident for non-engineered masonry buildings, which typically lack standardized designs. Their irregular and informal construction makes them difficult to assess using conventional approaches. Transformer-based models, a type of machine learning (ML) technique, offer a promising alternative. These models can identify patterns and relationships in available data, making them well suited for developing seismic fragility curves with improved efficiency and accuracy. While transformers are relatively new to civil engineering, their application to seismic fragility assessment has been largely unexplored. This study presents a pioneering effort to apply transformer models for deriving fragility curves for non-engineered masonry buildings. A comprehensive dataset of 646 masonry buildings observed in Malawi is used to train the models. The transformers are trained to predict the probability of four damage states: Light Damage, Severe Damage, Near Collapse, and Collapse based on Peak Ground Acceleration (PGA). The performance of the transformer-based approach is compared with other ML methods, demonstrating its strong potential for more efficient and accurate seismic fragility assessment. Future work could adopt the proposed methodology and extend the approach by incorporating larger datasets, additional regional contexts, and alternative ML techniques to further enhance predictive performance. Full article

Selenium, an essential metalloid, plays a dual role in biological systems: while crucial for maintaining normal biological processes, excessive levels can be toxic. Organisms mitigate selenium toxicity through a biochemical process known as methylation, in which inorganic selenium species are enzymatically converted into less toxic, excretable organic metabolites. This review synthesizes recent biochemical and environmental findings (with an emphasis on the past decade) related to selenium methylation. It outlines the enzymatic mechanisms—particularly involving glutathione reductase, SAM-dependent methyltransferases, and selenocysteine lyase—through which selenite and selenate are reduced and methylated to intermediates such as hydrogen selenide (H₂Se), ultimately yielding MMSe, DMSe, and TMSe⁺. The role of enzymes such as selenocysteine lyase in processing organic selenium and factors affecting the efficiency of these processes, including environmental conditions, are discussed. The role of enzymes such as selenocysteine lyase in metabolizing organic selenium species is also discussed, along with how environmental conditions (e.g., soil composition, redox potential) and genetic variability influence methylation efficiency and selenium speciation. In conclusion, this paper explores selenium methylation in plants, focusing on rice and corn, and how their selenium uptake and metabolism are affected by environmental factors. It examines the conversion of selenium into organic forms like selenomethionine and selenocysteine, and the role of methylation in managing excess selenium. The findings offer insights into selenium chemistry, with implications for food safety, nutrition, and environmental management, addressing key knowledge gaps and enhancing our understanding of selenium’s biological and chemical roles. Full article

Disaster headlines often underscore devastation and loss while overlooking success stories where proactive disaster risk reduction (DRRM) measures have averted catastrophe, saved lives, and reduced economic damage. This study addresses the gap in documentation and analysis of DRRM success stories in Africa, particularly within the Southern African Development Community (SADC), arguing that the absence of such narratives hampers a shift from reactive to proactive disaster risk governance. The research aims to extract critical lessons from success stories for enhancing future preparedness and response frameworks. A qualitative research design was employed, integrating document analysis, expert interviews, field observations, and practitioner workshops. Data was triangulated from diverse sources, including national disaster management agency reports (e.g., South Africa’s NDMC, Botswana’s NDMO, Mozambique’s INGC), peer-reviewed literature, UNDRR reports, SADC policy documents, and first-hand experiences from the authors’ consultancy work in the African Union’s biennial DRRM reporting processes. Case studies examined include Mozambique’s response to Cyclone Idai in 2019, South Africa’s drought and flood risk governance (e.g., the 2023 floods in Eastern and Western Cape), and Malawi’s flood resilience programs. Findings reveal that successful DRRM outcomes are driven by a combination of anticipatory governance, community-based preparedness, integration of Indigenous Knowledge Systems (IKSs), and investment in infrastructure and ecosystem-based adaptation. These cases demonstrate that locally embedded, yet scientifically informed, interventions enhance resilience and reduce disaster impacts. The study underscores the relevance of theoretical frameworks such as resilience theory, narrative theory, and social learning in interpreting how success stories contribute to institutional memory and adaptive capacity. Policy recommendations emphasize the need for institutionalizing success-story documentation in national DRRM frameworks, scaling up community engagement in risk governance, and fostering regional knowledge-sharing platforms within the SADC. Furthermore, the paper advocates for making DRRM success stories more visible and actionable to transition toward more anticipatory, inclusive, and effective disaster risk management systems. Full article

Background: Acute exacerbation (AE) of idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) is fatal. Infection is one of the most important triggers of the AE of IIM-ILD. We evaluated the clinical features and prognosis of idiopathic (I-AE) and infection-triggered (iT-AE) acute exacerbation in IIM-ILD patients. Methods: We retrospectively reviewed 278 consecutive patients with IIM admitted to our hospital between January 2014 and December 2020. Among them, 69 patients experienced AE of IIM-ILD, including 34 with I-AE and 35 with iT-AE. Clinical features and short- and long-term outcomes were analyzed in this preliminary study. Results: Compared with I-AE, patients with iT-AE presented with lower hemoglobin and PaO₂/FiO₂ ratios but higher pulse, body temperature, white blood cell count, neutrophil percentage (NEU), C-reactive protein, erythrocyte sedimentation rates, lactate dehydrogenase, and hydroxybutyrate dehydrogenase levels. They also had more extensive ground-glass opacities (GGOs) on high-resolution computed tomography (all p < 0.05). Mortality was significantly higher in iT-AE than that in I-AE at 30 days (28.6% vs. 5.9%), 90 days (34.3% vs. 14.9%), and 1 year (54.3% vs. 17.6%; log-rank test, p = 0.002). Multivariate logistic regression showed that the combination of NEU and GGO extent could help discriminate iT-AE from I-AE (area under the receiver operating characteristic curve: 0.812; 95% confidence interval: 0.711–0.913; sensitivity: 71.4%, specificity: 73.5%, accuracy: 72.5%). Conclusion: This study found that iT-AE patients exhibited more severe hyperinflammation and markedly worse survival than I-AE patients. Combining NEU and GGO extent may assist in differentiating AE subtypes. Larger prospective studies are required to validate these findings. Full article

Zinc (Zn) deficiency affects over 30% of the global population, with the highest burdens in developing countries reliant on cereal-based diets. As a major dietary staple in regions such as Sub-Saharan Africa and Latin America, common bean (Phaseolus vulgaris L.) represents a promising vehicle for addressing hidden hunger. This review critically evaluates the efficacy of various strategies to enhance Zn concentration in common bean, ranging from agronomic to genetic manipulation, and proposes promising strategies for biofortifying common bean in developing countries that are resource- and technology-limited. Biofortification strategies include agronomic practices, conventional breeding, and genetic engineering, each with distinct strengths and limitations. Agronomic methods such as soil and foliar fertilization can rapidly increase micronutrient content, but they require recurrent costs and may not be sustainable for smallholders without subsidies. Genetic engineering, particularly transgenic approaches, can significantly boost Zn levels; however, regulatory hurdles, cost of production, and public acceptance remain significant obstacles to widespread adoption. Conventional breeding is secure and widely adopted, but is time-consuming and limited by genetic diversity, making it less precise and slower than genetic engineering. We argue for a context-specific and integrated biofortification framework that prioritizes agronomic interventions such as biofertilizer, seed priming, soil Zn application, and foliar Zn application as approaches for quick results. Moderate- to long-term progress towards a biofortified common bean can be achieved using conventional breeding methods by selecting for local germplasm that accumulates higher Zn amounts in grain. On the other hand, genetic engineering is best for rapid, targeted nutrient enhancement where genetic diversity is lacking, but faces regulatory and acceptance challenges. We recommend that policymakers prioritize frameworks that harmonize these approaches, improve communication and education regarding the benefits of biofortified crop produce, subsidize and strengthen biofortified seed systems, and promote soil health initiatives. Full article

Background: Implementing effective interprofessional communication (IPC) in low-resource settings is challenging, primarily due to limited awareness and understanding of the concept. This analysis examined the concept of effective IPC for patient safety in low-resource settings. Its key attributes, antecedents, consequences, and empirical referents were identified. Methods: The Walker and Avant framework was used to analyze effective IPC. A literature review was conducted using PubMed, CINAHL, Embase, and Google Scholar, covering research from 2014 to 13 May 2025. Results: Effective IPC embodies clarity, accuracy, consistency, trust, collaboration, and timely information exchange. Strong leadership commitment, transparent communication, ongoing training, and a systematic incident reporting method contribute to better patient safety (PS) and improved healthcare outcomes. Conclusions: Effective interprofessional communication (IPC) is crucial for enhancing patient safety (PS). The concept and its attributes are unclear and underutilized in low-income countries like Malawi due to inadequate training, lack of standardized tools, weak leadership support, and limited psychological safety. Effective IPC should be integrated into preservice training, standardize PS education, and foster collaboration in clinical settings. Full article

Africa’s Critical Zones experience unprecedented environmental degradation but do not have effective governance modalities for policy implementation coordination across jurisdictional and stakeholder scales. This study addresses three specific scientific challenges: (1) How does policy discordance between national environmental policies and local implementation cultures undermine conservation effectiveness in Critical Zones? (2) What do power asymmetries among stakeholders contribute to governance failure? (3) To what extent do implementation gaps stem from the exclusion of Indigenous knowledge systems from mainstream policy-making processes? In this qualitative multi-case study, the research examines policy reports, technical reports, and interviews with important stakeholders in five African Critical Zones: Central Rift Valley (Ethiopia), Kilombero Valley (Tanzania), Maligunde Dam (Malawi), Lake Chivero (Zimbabwe), and Muizenberg East (South Africa). Evidence shows that shattered institutional imperatives create policy gaps exploited by industrial stakeholders, where policy design from the top down routinely leaves in place established community-based systems of governance that have historically maintained these ecosystems in equilibrium. Excess power held by government ministries compared to local communities results in 73% of environmental policy being enforced with ineffective stakeholder engagement, with non-compliance levels across examined locations exceeding 60%. The study attests to the fact that co-management incorporated governance systems that adopt traditional ecological knowledge systems register 40% greater compliance rates with policies. These findings are empirical evidence of adaptive governance models that can bridge Africa’s most vulnerable ecosystems’ policy–practice gap, and they guide direct implementation of the African Union Agenda 2063 environmental targets. Full article

The paper discusses fish stock assessment methods, emphasising methods for assessing stocks in developing nations. We present the advantages and disadvantages of each method discussed. Approaches to fish stock assessment include single-species, multi-species, multi-gear and ecosystem approaches. We discuss the Gordon–Schaefer (GS) model, a single-species surplus production model, as an alternative method for assessing fishery stocks in developing nations, with Malawi as an example of a developing nation. Although the GS model is not a contemporary method, it is still suitable for the situation in Malawi. We review how the GS model has been applied globally, in general, and in Malawi, in particular. The review shows that most studies have concentrated on the calculation of maximum sustainable yield or maximum economic yield, leaving out open access yield and optimum sustainable yield which is the dynamic reference point. Using all reference points is crucial in making correct management decisions. Bifurcation analysis, calculation of annual sustainable production, and calculation of depletion are missing in most studies. Future research should focus on integrating the use of all four reference points, bifurcation analysis, and calculation of depletion as well as annual sustainable production. Full article