Scholarlink

<p>The paper presents a novel deductive approach for disaster risk assessment in Asia by quantitative analyses of the EM-DAT database 2000–2023. The literature focuses primarily on indicator-based approaches, drawing from the Pressure and Release model. However, these models are constrained by the data availability and subjective variable choices. Two new metrics, Disaster Impact Indicator (DII) and Disaster Risk Index (DRI), are presented in this study. These can be used to compare the impacts and risks of disasters at the country and disaster-type levels. The paper covered 3,644 Asian natural disasters – in terms of deaths, affected populations, and losses. Results showed high-risk countries: Myanmar, Pakistan, and Türkiye were at high mortality risk; India, China, and the Philippines were high-risk affected populations; Japan, China, and India were at high economic damage risk. Considering disaster type, the paper clarified that earthquakes indicate the highest mortality and economic damage risks, and floods and storms were the highest people affected and economic damage risks. The approach is practical when deciding on disaster mitigation with limited resources and can stand in for traditional indicator-based analyses. This method also bypasses the old methodological bottleneck by providing an objective, simplified, evidence-based assessment framework while only requiring simple same-format data. These results are invaluable for researchers, policymakers, and disaster experts who work on disaster risk reduction strategies for Asian countries.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Disaster risk assessment in Asian countries: a novel deductive approach

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月9日

查看全文
  • Tadashi Nakasu

摘要

The paper presents a novel deductive approach for disaster risk assessment in Asia by quantitative analyses of the EM-DAT database 2000–2023. The literature focuses primarily on indicator-based approaches, drawing from the Pressure and Release model. However, these models are constrained by the data availability and subjective variable choices. Two new metrics, Disaster Impact Indicator (DII) and Disaster Risk Index (DRI), are presented in this study. These can be used to compare the impacts and risks of disasters at the country and disaster-type levels. The paper covered 3,644 Asian natural disasters – in terms of deaths, affected populations, and losses. Results showed high-risk countries: Myanmar, Pakistan, and Türkiye were at high mortality risk; India, China, and the Philippines were high-risk affected populations; Japan, China, and India were at high economic damage risk. Considering disaster type, the paper clarified that earthquakes indicate the highest mortality and economic damage risks, and floods and storms were the highest people affected and economic damage risks. The approach is practical when deciding on disaster mitigation with limited resources and can stand in for traditional indicator-based analyses. This method also bypasses the old methodological bottleneck by providing an objective, simplified, evidence-based assessment framework while only requiring simple same-format data. These results are invaluable for researchers, policymakers, and disaster experts who work on disaster risk reduction strategies for Asian countries.