International Health最新文献

Background: In Cambodia, limited conceptual understanding of antimicrobials and the wide availability of over-the-counter medications increases antimicrobial resistance (AMR) threats. Community-based campaigns are critical to foster fundamental concepts of antimicrobials, their appropriate use and potential consequences of AMR.

Methods: A circus-based drama on AMR was co-designed with a non-profit arts school and local youth groups, in coordination with two provincial health authorities.

Results: Events held across three venues were attended by >1200 people and the accompanying social media campaign received >0.5 million views.

Conclusions: Following the success of the campaign, the circus drama's key messages are being developed into educational materials for school children nationwide.

Background: The World Health Organization (WHO) has approved the use of a verbal autopsy (VA), a survey-based approach to generate out-of-hospital causes of death (CoDs). Through this study, an adaptive Bayesian networks machine learning model was developed and tested. The model is scalable and adaptable for predicting new causes as the dataset expands.

Methods: The 2016 WHO questionnaire was used to collect data from Iringa, Tanzania, and data augmentation was performed using the Synthetic Minority Oversampling Technique for nominal features to increase the dataset size and reduce bias in the CoD classification. The model development was guided by a CoD decision flow that integrates essential factors and steps for accurate CoD prediction. To our knowledge, no previous study has provided this operational guide for VA cause of death prediction.

Results: The model was evaluated using accuracy, sensitivity, specificity and F1 score metrics and compared with Support Vector Machine and Naïve Bayesian models. Results indicated an average accuracy of 97%, specificity of 97%, sensitivity of 94% and F1 score of 94%, which are superior compared with Naïve Bayesian and Support Vector Machine models.

Conclusions: The reported performance of the developed model demonstrates the potential for this model to enhance VA-based CoD data by integrating a machine learning approach with physician expertise. The results highlight the effectiveness of combining Bayesian networks with physician Symptom Cause Information as a valuable tool in advancing the performance of CoD predictions.

Neonatal death in sub-Saharan African countries accounts for 80% of the global burden. An estimated 30 deaths per 1000 live births occurred in Ethiopia in 2019. Neonatal necrotizing enterocolitis (NEC) is the most common contributing factor to these deaths. Nevertheless, there is no strong evidence of neonatal NEC in Ethiopia. Therefore, this study aimed to determine the pooled prevalence of neonatal NEC and its predictors among neonates admitted to neonatal intensive care units in Ethiopia. Databases (Scopus, CINAHL, CAB Abstract, Embase, PubMed, Web of Science, Google and Google Scholar) and lists of references were used to search literature in Ethiopia. Stata version 17 (StataCorp, College Station, TX, USA) was used for analysis and the odds ratios (ORs) of the outcome variable were determined using the random-effects model. Heterogeneity among the studies was assessed by computing values for I2 and p-values. Also, sensitivity analysis and funnel plots were used to assess the stability of pooled values to outliers and publication bias. A total of 12 studies with a sample size of 7675 were included in this study. The overall prevalence of neonatal NEC was 16% (95% confidence interval 11 to 22). Meta-analyses and sensitivity analyses showed the stability of the pooled ORs and the funnel plots did not show publication bias. Preterm birth, very low birth weight and duration of stay in a neonatal intensive care unit (NICU) were identified as predictors of neonatal NEC. In Ethiopia, one in six (16%) neonates admitted to NICUs had NEC, with preterm birth, very low birth weight and duration of stay in the NICU identified as key predictors. Moreover, these findings imply the need for targeted interventions to reduce the risk of this condition in vulnerable neonates using large-scale prevention strategies through high-quality healthcare for mothers and children.

Background: Poor iron status is a common nutritional condition affecting preschool-age children (PSC) in low-income countries like Malawi. This study aimed to examine the determinants of iron deficiency (ID), functional iron deficiency (FID) and iron deficiency anaemia (IDA) among Malawian PSC.

Methods: The study analysed data from the 2015-2016 Malawi Micronutrients Survey, which collected information from a nationally representative sample of PSC across Malawi. Iron status was evaluated through biochemical markers, including serum ferritin, soluble transferrin receptors and haemoglobin levels. Logistic regression analyses were performed to identify independent factors associated with iron status.

Results: The prevalence of ID was 19.6%, FID was 50.3% and IDA was 4.7%. Males had higher odds of both ID and FID compared with females. Children <36 months of age were at significantly greater risk for ID, FID and IDA compared with children ages 48-59 months. Additionally, children referred for clinical malaria or those with inflammation were more likely to have ID and FID compared with those children who did not. Underweight children had a higher risk of both ID and IDA compared with children who were well nourished. Living in rural areas or the southern region of Malawi further increased the likelihood of developing ID compared with children from urban areas and the northern region.

Conclusions: The study emphasizes the need for comprehensive healthcare initiatives addressing nutritional deficiencies and malaria prevention in vulnerable groups, particularly young children in rural areas.

Background: Despite significant progress, trachoma persistence and recrudescence in Ethiopia pose a challenge to global elimination of trachoma as a public health problem. Developing evidence-based, expert-informed strategies is crucial for achieving global elimination targets by 2030. Our aim was to develop strategies to address persistent and recrudescent trachoma using Delphi techniques.

Methods: The study reviewed literature and studies from districts in southern Ethiopia where trachoma prevalence remains above the elimination threshold. A modified Delphi technique was employed to achieve consensus on strategies. Initially, 78 interventions were identified and reviewed by eight experts, resulting in 46 interventions and 6 strategies advancing to Delphi round 1. In round 1, 16 experts evaluated the strategies and interventions for relevance. In round 2, 32 experts from various institutions assessed them for relevance, feasibility and scalability. In round 3, 20 experts scored the final strategies and interventions for adoption or rejection. Data analysis was conducted using Microsoft Excel, with frequencies, percentages and summaries presented. Stability and descent analysis ensured the quality and consistency of the results.

Results: Six strategies and 28 interventions were recommended, including enhancing service delivery, addressing workforce gaps, overcoming technological and supply chain barriers and ensuring robust data systems. Additionally, healthcare financing and enhanced leadership, management and stakeholder engagement were recommended.

Conclusions: The study identified strategies and interventions to address trachoma persistence and recrudescence in Ethiopia, reinforcing efforts to strengthen the surgery, antibiotics, facial cleanliness and environmental improvement strategy.

Background: One in two people with diabetes in sub-Saharan Africa remains undiagnosed, which has contributed to the region's high rates of diabetes-related morbidity and mortality. While the COVID-19 pandemic likely exacerbated diabetes prevalence, limited data from the region, including Uganda, hampers our understanding of this impact. To address this gap, we analysed the diabetes prevalence and correlates among adults from three rural districts of Uganda using data from a community-based screening programme conducted by community health workers (CHWs) during the pandemic.

Methods: We used anonymised data of 2587 records to analyse the prevalence and correlates of diagnosed and undiagnosed diabetes. Prevalence was presented as proportions with 95% CIs. Correlates of diabetes and undiagnosed diabetes prevalence were analysed using logistic regression and presented as ORs.

Results: The overall prevalence of diabetes was 11.3% (95% CI 10.2 to 12.5%), with a 7.2% (95% CI 6.2 to 8.1%) prevalence for diagnosed diabetes. A high proportion (36.4%) of diabetes cases were undiagnosed. Older age, high body mass index and pre-existing hypertension were associated with high diabetes prevalence.

Conclusions: There was a high proportion of undiagnosed diabetes among rural adults during the pandemic. Engaging CHWs in routine diabetes screening and awareness programmes can reduce the burden of undiagnosed diabetes.

Background: Malaria is a severe and endemic disease, remaining one of the most prevalent tropical illnesses and a leading cause of death among children aged <5 y. Anopheles gambiae, the primary vector of malaria in Benin, plays a critical role in its transmission. This study aims to contribute to the health protection of populations in Benin by assessing the risk of vector-borne diseases, particularly malaria, in the context of climate change.

Methods: Using the Maxent algorithm for ecological niche modeling, we mapped the distribution of A. gambiae, a highly effective vector of Plasmodium parasites.

Results: Our findings revealed that high-risk areas for malaria cover nearly all departments of Benin, with the majority of southern departments-Mono, Littoral, Couffo, Ouémé, Plateau and Zou-identified as high-risk zones. Projections for 2055 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 climate scenarios indicate a significant expansion of high-risk areas, extending to Collines and parts of Donga, Borgou and Atacora.

Conclusions: Climate change is expected to exacerbate the spread of A. gambiae, increasing the disease risk across the country. These results are crucial for guiding policymakers in Benin to mitigate the current impact of malaria and implement preventative measures to address future risks.

Background: Five million children <5 y of age died globally in 2021, the majority (56%) in sub-Saharan Africa (SSA). Many of the deaths in children <5 y of age could be prevented through early detection and treatment. However, healthcare utilization for childhood illnesses remains low in the region. The aim of this study was to assess the relationship between women empowerment and healthcare utilization for childhood illnesses.

Methods: The main predictor variable for this study was women's empowerment and the outcome variable was healthcare utilization for childhood illnesses. The data source for the study was the 2016 Ethiopia Demographic and Health Survey dataset. Complex sample ordinal regression analysis was employed, controlling for confounders. Adjusted cumulative odds ratios (cuORs) and 95% confidence intervals were computed to estimate effect size.

Results: A total of 2101 (weighted) cases of children <5 y of age were included in this study. Children whose mothers were empowered with a wife-beating attitude were 59% more likely to get healthcare for all illnesses in children <5 y of age (β=0.46, cuOR 1.59, p<0.01). Children whose mothers had no problems with healthcare access were also more likely to receive health services for all illnesses in children <5 y of age (β=0.42, cuOR 1.52, p=0.01).

Conclusions: Women's empowerment has a significant effect on healthcare utilization for illnesses in children <5 y of age. The finding indicates empowering women, sooner or later, is empowering the family.

Background: This study assesses the prevalence of contraception-use intentions and evaluates the associated factors among non-users in sub-Saharan Africa (SSA).

Methods: Data from 2014-2023 Demographic and Health Surveys of 30 countries in SSA consisting of 332 986 women aged 15-49 y not already using contraception were used.

Results: The overall prevalence was 41.18% (95% CI 41.01 to 41.34%). Zimbabwe had the highest prevalence (72.34%; 95% CI 71.11 to 73.57%), whereas Ethiopia had the lowest (15.96%; 95% CI 15.40 to 16.51%). Women aged 25-49 y had lower odds of intending to use contraception compared with those aged 15-19 y, and this was striking among those aged 45-49 y (adjusted OR [AOR]=0.06, 95% CI 0.06 to 0.07). Those with a higher level of education displayed a greater likelihood of intending to use contraception (AOR=1.93, 95% CI 1.82 to 2.05) compared with those with no education. The odds increased with the number of children born, particularly for those with ≥4 children (AOR=1.59, 95% CI 1.52 to 1.67) compared with those with no children.

Conclusions: Promoting the use of contraception requires tailored, multi-pronged interventions that account for the diverse sociodemographic, fertility and informational needs of women in this population.

Debates on AI ethics in global health often privilege professionalized authority over those most exposed to harm. We argue for the need to consider redistributing ethical authority to affected communities, particularly in low- and middle-income countries, potentially through participatory councils with decision power over evaluation metrics, equity constraints, and deployment. Centering lived experience can strengthen safety, accountability, and decolonial governance, may aid in addressing algorithmic bias and financial toxicity, and could align with WHO guidance for public-interest AI. We offer potential practical mechanisms to co-lead design, trials, and post-deployment monitoring so AI advances health and rights rather than simply reproducing inequities.