States and Multi-Hazard Early Warning Systems

The lack of early warning systems for half of the countries worldwide and poor investments in regulatory frameworks to link early warnings to emergency plans exacerbates the exposure of populations at risk of natural hazards in livable urban environments. This study hypothesizes that the level of democracy, trade openness, economic prosperity, per capita public aid, hazard exposure, lack of coping and adaptive capacities, classification as least developed countries (LDC), landlocked developing countries (LLDC), and small island developing States (SIDS), population in urban areas, cellular mobile, state fragility index, and regional vulnerability impact the efficiency of a country’s early warning system. To check on the truth of this conjecture, the study is designed as quantitative research with the objective of exploring the factors which cause variations in multi-hazard early warning systems (MHEWS) for countries in different regions. The situs comprises 195 countries which are signatories to the Sendai Framework for Disaster Risk Reduction (2015-2030). The selection criteria include countries which positively engaged with the Sendai Framework Monitor (SFM) for the period between 2015-2022. The COM-B behavioral framework and bounded rationality establish that the variables affecting MHEWS quality and coverage present a complex interplay of factors and cannot be interpreted in isolation. Panel logit and linear regression models are used to assess these multiple longitudinal relationships simultaneously. The findings reveal that trade openness, exposure to coastal floods and tropical cyclones, population in urban areas, state fragility index, and regional disparities are significant predictors of global early warning variations. To improve risk knowledge, emergency readiness, and coverage, recommendations are made in the study for prioritization of technology sharing, utilization of mobile-based early warnings, support for weak States, and equitable financial investment and global disaster-aid allocation.