Development of a Risk and Resilience Framework for Health Infrastructure under Multi-Hazard Scenarios in Seismic-Prone Areas

About the Project

In an era of increasing frequency and intensity of natural hazards, the resilience of health infrastructure plays a pivotal role in ensuring effective emergency response, safeguarding public health, and minimizing socioeconomic disruption. In seismic-prone areas, hospitals and health facilities are often at the frontline during and after disasters. However, their functionality is frequently compromised not only by earthquakes but by cascading or compounding hazards such as tsunamis, landslides, floods, and climate-related stresses. Traditional approaches to health infrastructure risk assessment largely consider single-hazard contexts, lacking the comprehensive perspective required to evaluate resilience under complex, multi-hazard scenarios.

This PhD project aims to develop an integrated risk and resilience assessment framework for health infrastructure located in multi-hazard seismic regions. The research will focus on identifying, quantifying, and modelling interactions between seismic hazards and secondary hazards, with the goal of improving the robustness and adaptive capacity of health facilities.

The core objectives of the project are:

1. To identify and classify multi-hazard scenarios relevant to seismic-prone areas, including but not limited to co-occurring and cascading events (e.g., earthquake-triggered landslides, floods, aftershock sequences).
2. To assess the physical, functional, and operational vulnerabilities of health infrastructure under such scenarios using interdisciplinary approaches from structural engineering, operational system, and disaster risk management.
3. To develop a resilience metric framework integrating technical, social, and organizational indicators, capturing both pre-disaster preparedness and post-disaster recovery capacities.
4. To propose a decision-support tool that enables stakeholders and policymakers to evaluate resilience and prioritize interventions based on risk-informed investment planning.

The methodology will combine probabilistic risk modelling, resilience quantification, and scenario-based simulation. Data from case studies in selected seismic hotspots (e.g., Nepal, Indonesia, India, Thailand, Turkey) may be utilized to validate and calibrate the framework. The project may also incorporate GIS-based spatial analysis and machine learning techniques to identify hazard exposure patterns and critical system interdependencies.

The outcome of this research is expected to offer a scalable and transferable framework for global application, particularly relevant to low- and middle-income countries where health systems are already under significant stress. It will contribute to the Sendai Framework for Disaster Risk Reduction, Sustainable Development Goals (especially SDG 3 and SDG 11), and WHO’s health emergency preparedness strategies.

This project is suitable for candidates with a background in civil/structural engineering, disaster risk management, or a related field. Experience in programming, GIS, or system modelling is advantageous. The research will be conducted in collaboration with academic, non-governmental organisations and governmental partners, with opportunities for fieldwork and stakeholder engagement.

Through this PhD, the candidate will contribute significantly to the understanding and practical enhancement of health infrastructure resilience in complex hazard environments, equipping decision-makers with the tools to safeguard health services when they are needed most.

Funding Notes

there is no funding for this project