Structural collapses are a major threat to urban safety and infrastructure resilience and as such there is growing research interest in understanding the causes and improving the prediction of risk to prevent human and material losses. Whether caused by fires, earthquakes or progressive failures due to overloads and displacements, these events have been the focus of investigation over the past 15 years. This systematic literature review looks at the use of formal risk analysis models in structural failures between 2010 and 2025 to map methodological trends, assess model effectiveness and identify future research pathways. From an initial database of 139 documented collapse incidents, only 42 were investigated using structured risk analysis frameworks. A systematic screening of 417 related publications yielded 101 peer-reviewed studies that met our inclusion criteria—specifically, the application of a formal analytical model. This discrepancy highlights a significant gap between the occurrence of structural failures and the use of rigorous, model-based investigation methods. The review shows a clear shift from single-method approaches (e.g., Fault Tree Analysis (FTA) or Finite Element Analysis (FEA)) to hybrid, integrated models that combine computational, qualitative and data-driven techniques. This reflects the growing recognition of structural failures as socio-technical phenomena that require multi-methodological analysis. A key contribution is the development of a strategic framework that classifies models by complexity, data requirements and cost based on patterns observed across the reviewed papers. This framework can be used as a practical decision support tool for researchers and practitioners to select the right model for the context and highlight the strengths and limitations of the existing approaches. The findings show that the future of structural safety is not about one single “best” model but about intelligent integration of complementary context-specific methods. This review will inform future practice by showing how different models can be combined to improve the depth, accuracy and applicability of structural failure investigations.
Medaa et al. (Tue,) studied this question.