Perspective on secondary disasters: a literature review for future research


Sahın K. Y., Kavus B. Y., Taşkın A.

Environment, Development and Sustainability, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Review
  • Publication Date: 2024
  • Doi Number: 10.1007/s10668-024-05577-3
  • Journal Name: Environment, Development and Sustainability
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, International Bibliography of Social Sciences, PASCAL, ABI/INFORM, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Business Source Elite, Business Source Premier, CAB Abstracts, Geobase, Greenfile, Index Islamicus, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Climate changes, Multi-hazard, Natural disasters, Secondary disaster
  • Yıldız Technical University Affiliated: Yes

Abstract

Secondary disasters are catastrophic events that cause social and economic damage triggered by primary disasters. The need to reduce the increasingly destructive impact combined with primary disasters attracts researchers despite the difficulties of complex relationships between disasters and uncertain parameters. This study analyses 92 studies on applications in the field of secondary disaster, consisting of articles and books published in various journals and conference proceedings from 2010 to 2024. The existing literature is categorized according to the types of disasters and methodologies used to highlight trends and gaps in the secondary disaster field. In addition, the relationships between disasters and the diversity and limitations of the methodologies used are also included in this study. The findings of the study reveal the following: (i) post-earthquake landslide disaster applications dominate the secondary disaster field, while other disasters, such as geophysical, meteorological, biological, etc., have not been sufficiently analyzed, (ii) applications for secondary disasters are largely based on susceptibility modeling, (iii) artificial intelligence-based and probabilistic models dominate applications in the existing literature. Eventually, various possible future research paths are provided that may be valuable to decision-makers in decreasing catastrophe loss and damage.