Nutrition: Africa RISING science, innovations and technologies with scaling potential from the Ethiopian highlands

United States Agency for International Developmen

Current status of schistosomiasis and soil-transmitted helminthiasis in Beyla and Macenta Prefectures, Forest Guinea

A cross-sectional survey was undertaken in children aged 9-14 years in Beyla and Macenta Prefectures, Forest Guinea. Stool samples were examined by Kato-Katz and urine samples were examined by the centrifugation method. The overall prevalence and intensity of infection was 66.2% and 462.4 eggs per gram of faeces (epg) for Schistosoma mansoni, 21.0% and 17.8 eggs per 10ml of urine for S. haematobium, 51.2% and 507.5 epg for hookworm, 8.1% and 89.1 epg for Ascaris lumbricoides and 2.4% and 16.7 epg for Trichuris trichiura. The overall prevalence of schistosomiasis (S. mansoni and/or S. haematobium) was 70.7%. The prevalence of schistosomiasis was similar to those reported in the 1990s in the region; however, the prevalence of soil-transmitted helminths has since fallen. These findings illustrate the need for schistosomiasis control in Guine

High levels of surgical antibiotic prophylaxis: implications for hospital-based antibiotic stewardship in Sierra Leone

OBJECTIVE: Despite the impact of inappropriate prescribing on antibiotic resistance, data on surgical antibiotic prophylaxis in sub-Saharan Africa are limited. In this study, we evaluated antibiotic use and consumption in surgical prophylaxis in 4 hospitals located in 2 geographic regions of Sierra Leone. METHODS: We used a prospective cohort design to collect data from surgical patients aged 18 years or older between February and October 2021. Data were analyzed using Stata version 16 software. RESULTS: Of the 753 surgical patients, 439 (58.3%) were females, and 723 (96%) had received at least 1 dose of antibiotics. Only 410 (54.4%) patients had indications for surgical antibiotic prophylaxis consistent with local guidelines. Factors associated with preoperative antibiotic prophylaxis were the type of surgery, wound class, and consistency of surgical antibiotic prophylaxis with local guidelines. Postoperatively, type of surgery, wound class, and consistency of antibiotic use with local guidelines were important factors associated with antibiotic use. Of the 2,482 doses administered, 1,410 (56.8%) were given postoperatively. Preoperative and intraoperative antibiotic use was reported in 645 (26%) and 427 (17.2%) cases, respectively. The most commonly used antibiotic was ceftriaxone 949 (38.2%) with a consumption of 41.6 defined daily doses (DDD) per 100 bed days. Overall, antibiotic consumption was 117.9 DDD per 100 bed days. The Access antibiotics had 72.7 DDD per 100 bed days (61.7%). CONCLUSIONS: We report a high rate of antibiotic consumption for surgical prophylaxis, most of which was not based on local guidelines. To address this growing threat, urgent action is needed to reduce irrational antibiotic prescribing for surgical prophylaxis

Claims about the Misuse of Insecticide-Treated Mosquito Nets: Are These Evidence-Based?

Thomas Eisele and colleagues dispute reports in the media and elsewhere that insecticide-treated nets are not widely used, or are misused, and say that such misconceptions are not evidence-based and are damaging to malaria control efforts

Bringing the social into vaccination research: Community-led ethnography and trust-building in immunization programs in Sierra Leone

Background Vaccine hesitancy is a complex, contested social phenomenon and existing research highlights the multifaceted role of trust in strengthening vaccine confidence. However, understanding public engagement with vaccination through the lens of (mis)trust requires more contextual evidence on trust's qualitative determinants. This includes expanding the geographic focus beyond current studies' focus on High Income Countries. Furthermore, obstacles remain in effectively integrating social science findings in the design of vaccine deployment strategies, and in ensuring that those who implement interventions and are affected by them are directly involved in producing knowledge about vaccination challenges. Methods We piloted a community-led ethnographic approach, training Community Health Workers (CHWs) in Kambia District, Sierra Leone, in qualitative social science methods. Methods included participant observation, participatory power mapping and rumour tracking, focus group discussions and key stakeholder interviews. CHWs, with the support of public health officials and professional social scientists, conducted research on vaccination challenges, analysed data, tested new community engagement strategies based on their findings and elicited local perspectives on these approaches. Results Our findings on vaccine confidence in five border communities highlighted three key themes: the impact of prior experiences with the health system on (mis)trust; relevance of livelihood strategies and power dynamics for vaccine uptake and access; and the contextual nature of knowledge around vaccines. Across these themes, we show how expressions of trust centered on social proximity, reliability and respect and the role of structural issues affecting both vaccine access and confidence. The pilot also highlighted the value and practical challenges to meaningfully co-designed research. Conclusion There is scope for broader application of a community-led ethnographic approach will help redesign programming that is responsive to local knowledge and experience. Involving communities and low-cadre service providers in generating knowledge and solutions can strengthen relationships and sustain dialogue to bolster vaccine confidence

Future-ai:International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe