Antimicrobial resistance is a major global health threat for humans, animals and the environment, with the highest mortality and morbidity rates in sub-Saharan Africa (SSA). The World Health Organization prioritised several carbapenem- and third-generation cephalosporin-resistant Gram-negative bacteria such as Enterobacterales as the most critical pathogens with only very limited treatment options. Bacteraemia, sepsis and other severe infections caused by multidrug-resistant (MDR) Gram-negative bacteria (GNB) give rise to excess mortality. Yet, the causative pathogens are rarely identified in patients in SSA due to a lack of microbiological diagnostics. Carbapenems and the new antibiotics ceftazidime-avibactam, cefiderocol and aztreonam-avibactam are active against different MDR GNB and could significantly reduce morbidity and mortality, but they are not widely available in SSA. The ComBac-Africa consortium has the overall goal to improve the management of severe infections due to MDR GNB in Côte d’Ivoire, Guinea-Bissau and Nigeria through the establishment of a needs-adapted diagnostic and antimicrobial stewardship (AMS) programme that provides equitable access to these novel antibiotics for targeted treatment. This will be achieved through (1) provision of high-quality and accurate microbiological diagnostics for prompt and correct identification of causative agents in bacteraemia and other severe infections; (2) a comprehensive One Health assessment of the epidemiology of GNB in humans, animal and environmental specimens; (3) tailored AMS initiatives, including early outbreak detection and infection prevention measures, to optimise the use of novel antimicrobials; (4) development of clinical algorithms for targeted diagnosis and treatment of infections due to MDR GNB; and (5) establishment of sustainable and affordable access to these antibiotics in SSA. A clinical trial will assess and quantify the impact of this multi-pronged intervention on patient outcome.

EmbeddedAI aims at enhancing the skill set for modelling, design and analysis of artificial intelligence on embedded systems for engineers by strengthening the Nigerian Higher Education (HE) training and curricula with state-of-the-art European standards and technologies. The project aims to strengthen the links between university-enterprise cooperation, entrepreneurship and employability of graduates in Nigeria and encourage the culture of practice-oriented and industry-motivated training in Nigeria HE systems that are historically more theoretically oriented. The project aims to establish and align study programs for a Master of Science in Embedded Artificial Intelligence to facilitate entrepreneurship opportunities and serve the Nigerian industry.EmbeddedAI includes mainly activities such as the development of the embedded AI pedagogy, mapping the requirements and the courses with the bologna system, course development and development of the hands-on lab, activities towards the accreditation of the master's program, knowledge transfer for both technical and industrial skills, and the dissemination to industry and scientific communities.Embedded AI targets multiple groups, including academia, HE staff, students, industry, and Small and medium-sized enterprises. EmbeddedAI targets the 25 million unemployed graduates in Nigeria since the program is designed to integrate embedded artificial intelligence designs in diverse fields such as agriculture, medicine, telecommunication, e.t.c. It is expected to obtain tangible results, including a masters program in embedded artificial intelligence course development and implementation integrated into Nigerian engineering studies, a sustainability plan, and a monitoring report to provide a sustainable integration of the proposed curriculum in the Nigerian educational system.