Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

TLDR

Major natural disasters in recent years have caused high human and economic costs, triggered record‑high post‑disaster relief, and highlighted the need to select the most effective disaster risk reduction measures, especially for low‑ and middle‑income countries that suffer disproportionate losses. This article discusses a methodology that uses advanced probabilistic catastrophe models to estimate the benefits of disaster risk reduction measures. The authors apply these models to estimate hurricane risk for residential structures in St. Lucia and earthquake risk for residential structures in Istanbul, calculating costs and economic benefits for selected risk‑reduction measures while accounting for hazard, exposure, and vulnerability.

Abstract

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.