High Impact Low Probability events (HILPs), often referred to as outliers, are becoming more important in disaster management because they are linked to complex risks and tipping points in interconnected systems. Recent events, such as the cascading effects of the coronavirus pandemic, rising uncertainties from global geopolitical instability, and successive and concurrent extremes driven by climate change, underscore the limitations of relying solely on severe but plausible scenarios for risk practitioners and policymakers. Despite the critical need to integrate HILPs into risk assessment models and emergency preparedness, the field is fragmented, with inconsistent definitions and methodologies. We present a perspective developed under the HORIZON AGILE project (AGnostic risk management for high Impact Low probability Events), which introduces two comprehensive definitions of HILPs and a taxonomy designed to enhance risk assessment, resilience analysis, and crisis management. We provide a validated scientific definition for the academic community and an operational definition tailored for practitioners and stakeholders. Additionally, our taxonomy offers a structured framework to address outlier events that often fall below traditional risk thresholds, ensuring that low-probability, high-impact scenarios with cascading and concurrent dynamics are effectively integrated into risk registers, legislation, and standards development. This study shows how this approach improves methods like stress testing and scenario modelling, especially for the loss of critical services. This empowers policymakers, practitioners, and stakeholders to include more scenarios in their strategies, enhancing resilience and preparedness.

BACKGROUND: The Girinka program in Rwanda has contributed to an increase in milk production, as well as to reduced malnutrition and increased incomes. But dairy products can be hazardous to health, potentially transmitting diseases such as bovine brucellosis, tuberculosis, and cause diarrhea. We analyzed the burden of foodborne disease due to consumption of raw milk and other dairy products in Rwanda to support the development of policy options for the improvement of the quality and safety of milk. METHODS: Disease burden data for five pathogens (Campylobacter spp., nontyphoidal Salmonella enterica, Cryptosporidium spp., Brucella spp., and Mycobacterium bovis) were extracted from the 2010 WHO Foodborne Disease Burden Epidemiology Reference Group (FERG) database and merged with data of the proportion of foodborne disease attributable to consuming dairy products from FERG and a separately published Structured Expert Elicitation study to generate estimates of the uncertainty distributions of the disease burden by Monte Carlo simulation. RESULTS: According to WHO, the foodborne disease burden (all foods) of these five pathogens in Rwanda in 2010 was like or lower than in the Africa E subregion as defined by FERG. There were 57,500 illnesses occurring in Rwanda owing to consumption of dairy products, 55 deaths and 3,870 Disability Adjusted Life Years (DALYs) causing a cost-of-illness of $3.2 million. 44% of the burden (in DALYs) was attributed to drinking raw milk and sizeable proportions were also attributed to traditionally (16-23%) or industrially (6-22%) fermented milk. More recent data are not available, but the burden (in DALYs) of tuberculosis and diarrheal disease by all causes in Rwanda has declined between 2010 and 2019 by 33% and 46%, respectively. CONCLUSION: This is the first study examining the WHO estimates of the burden of foodborne disease on a national level in Rwanda. Transitioning from consuming raw to processed milk (fermented, heat treated or otherwise) may prevent a considerable disease burden and cost-of-illness, but the full benefits will only be achieved if there is a simultaneous improvement of pathogen inactivation during processing, and prevention of recontamination of processed products.