Identifying disaster risk factors and hotspots in Africa from spatiotemporal decadal analyses using <scp>INFORM</scp> data for risk reduction and sustainable development
Emmanuel Eze, Alexander Siegmund
Abstract
Abstract The incidence and magnitude of hazards in Africa are escalating. Extant knowledge base of disaster risk (DR) trends, factors, and hotspots is lacking for the continent. Here we applied random forest machine learning regressions, spatial stratified heterogeneity, and hotspot analyses on INFORM data to identify DR patterns, factors and interactions, and notable risk hotspots. We show that although DR is generally decreasing in Africa, the Eastern, Southern, and Western regions record increasing DR. Physical exposure to floods, epidemics, and violent conflicts are hazard drivers of DR in Africa. Other significant DR drivers are mostly clustered under vulnerable groups and poor infrastructural coping capacities. Human hazards interact with other factors, exhibiting the highest influences on DR. Precisely, 19 out of 53 African countries in this study are DR hotspots. Eritrea is identified as a new hotspot. Targeted policies, resilience building, vulnerability reduction measures and comprehensive sustainability‐infused solutions are required for DR reduction and sustainable development in Africa.