Learning From Success, Not Catastrophe: Using Counterfactual Analysis to Highlight Successful Disaster Risk Reduction Interventions

In the aftermath of a disaster, news and research attention is focused almost entirely on catastrophic narratives various drivers that may have led to disaster. Learning from failure essential preventing future disasters. However, hyperfixation catastrophe obscures potential successes at local scale, which could serve as important examples learning resources in effective risk mitigation. To highlight mitigation actions would otherwise remain unnoticed, we propose use probabilistic downward counterfactual analysis. This approach uses modelling past hazard event with consequences made worse (i.e. counterfactual) by absence intervention. The follows analysis procedures where uncertainties simulated events outcomes are accounted for propagated. We demonstrate method using case study Nepal’s School Earthquake Safety Program, implemented before 2015 M w 7.8 Gorkha earthquake. Using school building database Kathmandu Valley, Nepal, present two applications: 1) quantification lives saved during earthquake result retrofitting schools Valley since 1997, 2) annual expected if pilot program was extended all buildings based seismic model. shift focus realised outcome alternative enables benefits reduction programs amidst or has yet unfold. Such quantified can be used celebrate successful interventions, providing positive reinforcement decision-makers political bravery commit implementation measures.