Abstract

Developing countries are disproportionately affected by natural hazards and lack of coping capacities. 15 This combination sets back progress on poverty alleviation and slows long-term development, 16 contributing the aggravation of the many obstacles already faced by these countries and their 17 communities. Probabilistic risk assessment models are increasingly popular tools for estimating 18 potential human and economic loss due to natural hazards. Within such a context, risk modeling for 19 developing countries presents specific challenges in terms of quantity and quality of the available input 20 data at all components of risk: hazard, exposure, and vulnerability. As such, widening the types of 21 hazards and ensuring that models are contextualized to the local needs of these countries is also crucial 22 and may require innovative or, some times, simplified, yet sound, approaches that tackle the well-23 known deficiencies in this context. Some of the above-mentioned challenges include: (i)

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