An African-European consortium of 6 SSA countries and 3 European countries, gathering 12 partners is proposing a unique and innovative scalable training program and network that will produce empowered infectious diseases experts to lead and drive research from and for sub-Sahara Africa (SSA), at levels of early-stage career (post-graduate certification and doctoral) and mid-stage career (post-doctoral) in an integrated program of health informatics and data sciences (BRIDGE PROGRAM). The program consortium will set up 5 Centre of Excellence (CoEs) in SSA countries (Benin, Ethiopia, Uganda, Kenya, Rwanda and South Africa). The CoEs will serve as training setting, field research setting and a hub for harmonized infectious diseases data, and all will recruit candidates from their countries for certification program, doctoral and post-doctoral fellowships but only 3 CoEs will be the degree awarding institutions. The degree awarding CoEs have been selected based on the existing university capacity to offer a degree awarding program or built on the existing partnerships between selected SSA public health institutes and local universities with degree awarding programs capacity. The program leverages the established collaborations between European and SSA institutions, utilizing accumulated medical data, including Electronic Health Records, registries, and biobanks. At the end of 54 months, program will have strengthened the institutional research leading capacities with at least 20 trainees per CoE with post-graduate certification, a total of 10 graduates with PhDs and a total of 4 post-doctoral fellows, skilled for harmonizing and analysing fragmented large data to derive data-driven insights and guide health policies. The CoEs embedded within public health institutions, with continuous mentorship from an international scientific community and a ready to use large amount of data, ensure the sustainability of training and collaborative research beyond the program grant.

Two vaccines designed for pregnant women, to protect their unborn infant, are entering late phase development and will prevent infections from group B Streptococcus and respiratory syncytial virus, respectively. For these vaccines to be approved, the vaccine must work effectively without causing any unwanted responses. To implement these vaccines in countries with low resources, healthcare systems must be strengthened by improving vaccine safety monitoring and surveillance of infection, and advancing vaccine delivery, vaccine confidence, and patient participation. The rapid rollout of electronic health records (EHR) in Kenya, Mozambique, Malawi, and Uganda offers an opportunity to use routine data to strengthen reporting of rates of adverse pregnancy, neonatal and infant outcomes, and any adverse events following immunisation; this will be imperative in informing and preparing for future large scale vaccination rollout campaigns. Our approach will address key gaps in EHR to develop pregnancy registries embedded within national reporting systems to establish this data, including baseline rates of pregnancy and infancy outcomes for Tetanus and COVID19 vaccines currently in use. These reporting systems will allow monitoring of potential safety signals once new vaccines are introduced. Experts in EHR, obstetrics and gynaecology, paediatrics, microbiology, clinical trials, and implementation research will develop the motivation and tools needed to monitor and evaluate current and future maternal vaccines. We will work closely with the WHO, African Medicines Agency and Country Stakeholders, co-developing pregnancy registries, sentinel site microbiological surveillance systems, and maternal vaccination communications toolkits in preparation for the decade of maternal vaccines. Our programme of work culminates in a network of maternal vaccine trial sites who can rapidly evaluate vaccines in pregnancy from late-stage trials through to introduction on a national level.

Artificial intelligence (AI) is widely regarded as one of the most promising and disruptive technologies for future healthcare. As AI algorithms such as deep neural networks are suited for the processing of large and complex datasets, radiology is the medical speciality that has seen some of the most important applications of AI in the recent years. However, despite these advances, a major limitation of current AI developments in medical imaging is that they have overwhelmingly, and almost entirely, targeted applications in high-income countries. There is a concern, if the current trend continues, that AI will increase the already pronounced inequalities in global health, in particular for resource-limited settings such as rural Africa, where the majority of the African population lives. AIMIX will develop the first scientific framework for inclusive imaging AI in resource-limited settings. The project will greatly advance the current state-of-the-art, from existing AI methods mostly developed for high-income settings, towards new imaging AI algorithms that are fundamentally inclusive, i.e. (1) affordable for resource-limited clinical centres, (2) scalable to under-represented population groups, and (3) accessible to minimally trained clinical workers. Furthermore, AIMIX will investigate the socio-ethical principles and requirements that govern inclusive AI, and examine how they compare, conflict or complement those of trustworthy AI developed thus far in high-income settings. These innovations will be demonstrated for affordable and accessible AI-powered obstetric ultrasound screening by minimally trained clinicians such as midwives in rural Africa. Ultimately, AIMIX’s scientific breakthroughs will enhance the democratisation of imaging AI in resource-limited settings, which will result in an important social impact, by empowering local communities, promoting inclusion, and reducing disparities between populations from low- and high-income societies.

Changemaker objective: To implement & evaluate a sustainable health intervention program on health, nutrition, & environmental outcomes for the primary prevention of adolescent obesity & related non-communicable diseases (NCDs) together with adolescents in three rapidly urbanizing cities in Burkina Faso, Kenya, Tanzania. Background: There is an increasing epidemic of adolescent obesity that can contribute to adult obesity, morbidity & NCDs in a broader sense. Sustainable health interventions in urban low- and middle-income countries are critical in addressing lifestyle factors that contribute to obesity, diabetes & hypertension in later life, such as unhealthy dietary habits, inactivity & sedentary behaviors while shaping urban environments. Considering obesity is a complex issue that is influenced by wide range of interconnected factors, such as policy, environment, social, economic, cultural, behavioral, commercial, & biological determinants, a whole-systems approach that converges multiple sectors (i.e., health, education, environment, and agriculture) and stakeholders (i.e., adolescents, caregivers, staff, local government, communities, policymakers & implementers) are needed for obesity prevention in LMICs. Our strategy: Four evidence-based strategies, which will be adapted to context through a co-design process: 1) urban farming in schools with satellite farms and organic waste composting, 2) sustainable health modules for classrooms, 3) linking to healthcare workers through health talks using motivational interviewing techniques and 4) WHO Best Buys: Mass media campaign. Our evaluation: 3 cluster-RCTs in secondary schools, within the framework of urban Health & Demographic Surveillance Systems, implementation, process evaluation & cost-effective evaluation. Our expected results: Evidence of how to implement and scale a sustainable health intervention. Estimate a mean difference in BMI of 0.175 which could lead to reduction of 5% in the prevalence of obesity.