Global and Public Health Nutrition
Big data and analytics, along with innovative trial designs, provide the opportunity to change how we conduct global health and nutrition research. Despite the proliferation of these approaches in different disciplines over the past decade, there are relatively few examples in the global health or nutrition fields. This session will feature new methodologies and research based on big data and advanced predictive analytics. Speakers will share their work to: develop a global nutrient database reflecting three decades worth of worldwide data, identify infants at increased risk of mortality following hospitalization for severe acute malnutrition, incorporate omics data to gain novel insight in maternal and newborn health, and identify who benefits most from population-based nutrition interventions. We will also review innovative, adaptive clinical trial designs which rely on big data for trial design simulations and continuous sample size re-estimation. Experts will debate whether these adaptive clinical trial designs are sufficiently rigorous, maximally efficient, and feasible for Global Health research.