Predicting Childhood Anaemia in Nigeria: A Machine Learning Approach to Uncover Key Risk Factors

ABSTRACT Background Childhood anaemia is a major public health challenge in Nigeria, with high prevalence among children under five. This study identifies key determinants and develops a predictive model using advanced machine learning technique. Methods A total of 13,136 children aged 6–59 months from the 2018 National Demographic and Health Survey (NDHS) were analysed. Sixteen machine learning algorithms were evaluated on the basis of their ability to predict childhood anaemia using a wide range of individual, community and environmental factors. The Extra Trees (ET) classifier, demonstrating the highest predictive performance, was used to identify the top 10 predictors of childhood anaemia. A fairness and demographic bias assessment framework was incorporated to evaluate the model's performance across different regions, wealth index categories, ethnic groups and gender. Results The ET classifier achieved an area under the curve (AUC) of 0.8319, an accuracy of 0.7565 and a recall of 0.7565. The top 10 predictors identified by the model included the number of under‐five children in the household, birth order, child age, media access, maternal health‐seeking behaviour, child gender, proximity to water, money problems, day land surface temperature and all population count. The demographic bias assessment revealed variations in model performance across different subgroups, with the lowest AUCs observed in the north‐east region (0.79), the poorest wealth index category (0.80) and the Hausa/Fulani ethnic group (0.81). Conclusion This study shows that machine learning can accurately predict childhood anaemia in Nigeria and identify key risk factors, supporting targeted interventions. Future work should focus on refining models and integrating AI‐based interventions to reduce anaemia.

The State of Public Health in Somalia: Top 5 Challenges and Strategies for Improvement

ABSTRACT As we navigate the evolving public health landscape in Somalia, this study provides a comprehensive analysis of critical challenges, including water, sanitation, and hygiene (WASH); malnutrition and food insecurity; infectious diseases; maternal and child health; and the rising burden of noncommunicable diseases (NCDs). The aftermath of prolonged conflict, economic instability, and environmental crises underscores the urgent need to strengthen healthcare infrastructure, enhance disease surveillance, and improve multisectoral collaboration. The complexities of governance, humanitarian aid, and healthcare access highlight the necessity of coordinated efforts between government institutions, NGOs, and international partners. Given the urgent need to combat infectious disease outbreaks and the persistent challenges of food insecurity and high maternal mortality rates, this study explores multifaceted issues, advocating targeted interventions, sustainable policies, and equitable healthcare delivery. Addressing the root causes of public health disparities requires commitment to resilience‐building, community engagement, and policy‐driven solutions. In this critical period, Somalia must embrace a unified vision that fosters collaboration, policy reform, and strategic investments, ensuring that public health remains a central pillar of national development and the humanitarian response.

Environmental Dissemination of Multidrug‐Resistant Gram‐Negative Pathogens in Djibouti's Wastewaters

ABSTRACT Background The occurrence of multidrug‐resistant (MDR) Enterobacteriaceae‐producing extended‐spectrum β‐lactamases (ESBLs) and/or carbapenemases is increasingly reported in clinical and environmental settings. Here, we aimed to investigate the resistance profile of gram‐negative bacterial isolates from urban and environmental wastewater in Djibouti. Materials and Methods Twenty‐five wastewater samples were collected from eight different locations of Djibouti. After bacterial culture on selective media for gram‐negative bacteria (GNB), obtained isolates were identified using matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐TOF) mass spectrometry. Antibiotic susceptibility testing was performed by disk diffusion and E ‐test methods. Standard PCR and Sanger sequencing were used to investigate antibiotic resistance genes, including β‐lactamases, carbapenemases, and colistin resistance genes. Results Eleven MDR gram‐negative isolates were identified from the 25 water samples collected, including six Escherichia coli , one Enterobacter cloacae , and four Klebsiella pneumoniae isolates. Interestingly, the pandemic ESBL gene bla CTX‐M‐15 was detected in 9 of the 11 (81.8%) from both urban and environmental water samples. In addition, the carbapenemase gene bla OXA‐48 was identified in 4 of the 11 strains (36.4%), including two E. coli , one K. pneumoniae , and one E. cloacae , all from urban wastewater, particularly hospital water samples. Conclusion For the first time, we describe here MDR‐GNB bacterial isolates from urban and environmental wastewater in Djibouti. To date, carbapenem‐resistant isolates have only been present in hospital wastewater. Regular surveillance policies, consistent with the “One Health” approach, are recommended to prevent the spread and monitor the evolution of antibiotic resistance in the environment and within the Djiboutian community.

Factors Affecting Utilization of Healthcare Services Among Nasahablood and Ayah 4 Internally Displaced Persons in Hargeisa, Somaliland

ABSTRACT Background Globally, 4.5 billion people lack full coverage of essential health services, and displaced populations are disproportionately affected. Understanding the specific barriers they face is critical for designing effective health interventions. Objective To identify the factors affecting the utilization of healthcare services among internally displaced persons (IDPs) in Hargeisa, Somaliland. Design A community‐based, cross‐sectional study. Site The Nasahablood and Ayah 4 IDP camps in Hargeisa, Somaliland. Participants A proportionate stratified sample of 271 households. Main Measures The primary outcome was the level of healthcare utilization (low, moderate, and high), analyzed using ordinal logistic regression (OLR). Predictor variables included accessibility, affordability, and socioeconomic factors. Results A majority of respondents (73.5%) reported low healthcare utilization, with only 14.4% reporting high utilization. OLR revealed that affordability was the most significant barrier to care ( p  < 0.001), followed by physical accessibility ( p  = 0.025). Both factors were associated with substantially lower odds of health service utilization. Additionally, after controlling for other variables, gender emerged as a significant predictor, with male respondents having lower odds of utilizing healthcare services compared to female respondents ( p  = 0.030). Conclusion Healthcare underutilization in these IDP camps is primarily driven by powerful structural barriers of cost and distance, compounded by gender‐specific factors. We recommend targeted interventions, including fee‐exemption policies and mobile health clinics, to address these critical gaps and improve health outcomes for this vulnerable population.

Understanding Global Health Inequality and Inequity: Causes, Consequences, and the Path Toward Justice in Healthcare

ABSTRACT Background Health inequality and inequity persist as pressing global challenges that disproportionately affect populations in low‐ and middle‐income countries. These disparities are driven by complex and interrelated factors, including socioeconomic deprivation, educational barriers, commercial determinants of health, inadequate governance structures, and systemic failures in resource allocation. Objectives This study seeks to critically examine the multifactorial causes of global health inequality and inequity, assess their wide‐ranging consequences on population health, and propose ethically grounded strategies for promoting equity and justice within global healthcare systems. Methods A rapid review approach was used to examine global health inequality and inequity. Searches were conducted in PubMed, Google Scholar, and Research Rabbit using key terms such as “global health inequality,” “health equity in global health policy,” and “healthcare disparities across countries.” The literature was selected on the basis of its relevance to structural determinants and systemic patterns of health disparities across countries with varying income levels. The analysis identified recurring themes related to the drivers of inequity and potential pathways toward healthcare systems while acknowledging the limitations inherent in rapid review methodologies, including possible language and selection biases. Results The findings highlight that structural determinants, such as poverty, educational and gender disparities, environmental degradation, conflict, and unequal allocation of health resources, serve as primary contributors to global health inequities. These factors result in disproportionate disease burden, limited access to essential services, and increased mortality rates in disadvantaged populations. Conclusion Addressing global health inequity requires a transformative, ethically grounded framework that emphasizes justice, solidarity, and equity. Key actions include redistributive policy reforms, strengthened health systems in resource‐limited settings, and the decolonization of global health governance. These measures are fundamental for realizing the right to health and achieving meaningful global health justice.

Comparing Patency of Pulmonary Stent Implantation and Balloon Angioplasty in Pulmonary Vein Stenosis: A Systematic Review and Meta‐Analysis

Adsorption Behavior of Phenyl‐Substituted Cyclopropanecarboxylic Acid on Al and Cu Surfaces: A Combined Experimental and First‐Principles Study

ABSTRACT The molecular structure of phenyl‐substituted cyclopropanecarboxylic acid (PSCCA, C 12 H 14 O 2 ; 3‐methyl‐3‐phenylcyclobutane‐1‐carboxylic acid ) was determined using nuclear magnetic resonance (NMR), infrared spectroscopy (IR), and X‐ray crystallography techniques. Following structural confirmation, its molecular geometry was optimized at the Density Functional Theory (DFT) level. The van der Waals interactions were accurately accounted for using the DFT‐D3 method in the CP2K program. Understanding the adsorption behavior of organic molecules on metal surfaces is of great significance for applications in catalysis, sensor design, surface functionalization, and corrosion prevention. In this context, the adsorption properties of the PSCCA molecule on Al and Cu surfaces were investigated in detail using DFT‐based CP2K calculations. By optimizing different adsorption configurations, the binding energies of the most stable structures were calculated and compared. The obtained results indicate that the PSCCA molecule strongly binds to both Al and Cu surfaces, with a higher adsorption energy on the Al surface compared to the Cu surface. In addition, Mulliken population analysis revealed distinct electronic charge transfer characteristics upon adsorption, with substantially stronger electron transfer observed on the Cu(111) surface due to enhanced d‐band–ligand orbital hybridization. This electronic behavior correlates with the adsorption strength and highlights the critical role of metal electronic structure in governing surface interactions. Electron density difference analyses suggest that PSCCA interacts with both surfaces via a physisorption mechanism. Furthermore, assessments in the context of surface inhibitor efficiency reveal that PSCCA has the potential to passivate active surface regions and hinder surface reactions. Analyses conducted under different pH conditions indicate that the inhibitory effect of PSCCA is particularly pronounced in acidic environments. These findings suggest that PSCCA, exhibiting higher adsorption energy and stability on the Al surface, can be considered an effective protective agent and may play a crucial role in the design of metal–organic interfaces.

Staging Aortopulmonary Lymph Nodes With Robotic‐Assisted Bronchoscopy: A Case Report and Literature Review

ABSTRACT Robotic‐assisted bronchoscopy (RAB) has improved lung nodule evaluation, but its feasibility to biopsy aortopulmonary lymph nodes remains underexplored. This study explored the safety and effectiveness of RAB for sampling aortopulmonary lymph nodes suspected of malignancy. We conducted a literature review on RAB for aortopulmonary lymph node biopsy and present a case of a patient with a history of malignancy. Using the Ion Endoluminal System, we navigated to the anterior segment of the left upper lobe to access a subaortic lymph node in a patient with a history of mantle cell lymphoma. Biopsy confirmed disease recurrence. Our literature review identified seven patients who underwent RAB to assess aortopulmonary lymph nodes, with most findings showing small‐cell lung cancer. Our study reports an 88% diagnostic yield, and no complications associated with the procedure. RAB is a safe and effective approach for biopsying aortopulmonary lymph nodes.

Acute Pulmonary Complications Following Cosmetic Hyaluronic Acid Dermal Filler Injections

ABSTRACT Hyaluronic acid (HA) injectable dermal filler is widely used in cosmetic procedures, but it rarely leads to pulmonary complications. We present four patients with acute pulmonary complications after HA filler injections: three with organising pneumonia and one with acute pneumonitis. All presented with dyspnoea and cough; three received bilateral breast injections, and one received both breast and buttock injections. All patients received supportive management, including oxygen therapy, corticosteroids, and empirical antibiotics, whereby three responded well, but one succumbed. Clinicians ought to be vigilant of potential life‐threatening pulmonary complications related to HA filler injections, as most procedures are performed in unassuming healthcare settings where catastrophic complications are not anticipated.

Bank lending amid geopolitical risk: The GCC case

Abstract This study investigates whether local and global geopolitical risks depress credit growth in GCC banks and whether the effect is heterogeneous across banks of different types (Islamic and Conventional), sizes, capital ratios, and liquidity ratios. Using an unbalanced panel dataset of 64 banks over the period 1990–2023, a total of 1967 bank‐year observations, and the local projections method, we find that in general, credit growth declines following the increase in global and local geopolitical risks. Interestingly, the drop in credit growth tends to be larger when facing heightened global geopolitical risk. Looking at the heterogeneous effect of geopolitical risk across bank‐specific characteristics, we find that Islamic banks remain resilient to global risk but are vulnerable to local risks. We also note that local geopolitical risk tends to exert a more persistent impact on smaller and less liquid banks. These results suggest the need for (i) further development of Islamic banking to shield GCC's banking sector from global geopolitical uncertainty, (ii) building banks' balance‐sheet strength vis‐à‐vis bank assets and liquidity ratio, and (iii) preserving regional stability to mitigate regional tensions and conflicts.