Piloting the Next Generation Analytics for Climate-Related Financial Resilience of Critical Infrastructure in Southeast Asia

28 October 2021

Natural disasters cost about US$18 billion a year in emerging markets and developing economies through damage to power generation and transport infrastructure alone. They also trigger wider disruptions for households and firms costing at least US$390 billion a year (World Bank, 2019).

Ensuring reliable, sustainable, and resilient critical infrastructure is a core part of national economic security and climate change adaptation and resilience.  Governments should secure the continuity of essential lifeline services if they are to ensure the safety and prosperity of their citizens.  Ministries of Finance, alongside line ministries responsible for critical infrastructure and local government, play an important role as they are responsible for timely and cost-effective access to funding to reinstate critical assets and services post disaster. Delays in accessing finance after a disruption delays the reinstatement of critical services and can have wider economic and social impacts.  Disaster risk finance – the process of pre-arranging finance to enable timely and targeted financing of post disaster relief and recovery – is an important part of reinstating assets and services quickly.

The World Bank partnered with Oxford Infrastructure Analytics to prototype new tools for disaster risk finance of critical infrastructure.  The World Bank’s Disaster Risk Financing and Insurance Program (DRFIP) and Oxford Infrastructure Analytics (OIA – a spin-out from the Oxford Programme for Sustainable Infrastructure Systems) developed prototype next generation analyses and tools that can support governments to identify critical vulnerabilities in infrastructure systems, quantify financial risks related to critical infrastructure, and explore financial solutions to access immediate funding to speed up the reinstatement of critical services post-disaster.  This initiative was piloted in its first phase in the Southeast Asia region, with financial and technical support from the Japan-World Bank Program for Mainstreaming Disaster Risk Management in Developing Countries.

The pilot study developed a prototype regional, multi-sector and multi-hazard infrastructure network risk analysis methodology and platform.  The study focuses on specific sectors including electricity and transport (road, rail) networks throughout seven Southeast Asia countries (Myanmar, Cambodia, Laos PDR, Indonesia, Philippines, Vietnam and Thailand), and on fluvial and coastal flooding and wind hazard (tropical cyclone). The study assembles, processes and analyzes globally available datasets to estimate risk metrics such as (conditional probability of) network failures and network losses.  The estimated network losses include the direct damage to the physical infrastructure asset itself (quantified as the cost of reinstating or rehabilitating an asset to the state it was in before it was damaged), and the indirect economic losses due to interruption of service to the customers (households, businesses, government) who depend upon the whole infrastructure network.

This regional infrastructure risk analytics platform is accessible through a prototype web interface, including a mapping tool to visualize infrastructure networks exposure and vulnerability to natural hazards and a dashboard displaying aggregate risk metrics.  The web interface shows key risk metrics such as: infrastructure failure probability by sector; expected annual damage at asset level; loss-probability distributions at province level by hazard and sector; expected annual economic losses at asset level; loss-probability distributions at province level by hazard.

This regional infrastructure risk analytics platform can inform operational and financial preparedness of critical infrastructure against climate shocks.  It can help identify critical vulnerabilities and generate estimates of direct and indirect climate related losses to critical infrastructure in order to help governments and infrastructure owners and operators design financial risk management and adaptation strategies.  This can help prioritize the collection of more detailed country-level data for local planning and guide the use of more detailed analytics to design and structure financial solutions. This enables risk informed strategic planning and preparedness.

The study builds on three main innovations. First, it brings together, for the first time, disaster risk finance analytics and infrastructure criticality analytics to assess financial risks and appraise financial risk management options. Second, it explores how global publicly available datasets can be used to deliver information more quickly, at scale and at lower cost. This is a critical step to make such analyses open, accessible and useable to emerging markets and developing economies. Third, it utilizes high-performance computing capabilities enabling analysis of network failures on a very large scale.

Building on this pilot phase, we aim to continue the collaboration with Oxford Infrastructure Analytics and the University of Oxford to refine, improve, and scale up this platform. Next steps include further validation and calibration of the models and tools, strengthen the economic assessment methodology, improve the interface and features of the platform, and expand the platform to other infrastructure networks hazards, and regions.

The study can inform and contribute to other global resilience initiatives.  The study also demonstrates the scalability of this approach, paving the way for the development of a global infrastructure risk analytics platform. The methodology and tools developed under this pilot study have already informed and can further contribute to other global initiatives such as the Global Resilience Index Initiative, aiming to gather and develop a common approach to define and analyze risks to drive resilience and resilient investment.

Figure: Snapshot of the Southeast Asia Infrastructure Climate Risk Analysis Prototype Web Interface.

The figure shows the one of the functionalities of the prototype interface that shows the range of potential economic impacts of failure, consisting of direct damages to infrastructure assets and indirect economic losses resulting from infrastructure service disruption (loss of power, loss of access). (The Prototype Web Interface can be accessed from: https://seasia.infrastructureresilience.org/. More information is available at: https://github.com/GFDRR/oi-risk-vis)


Image credit: Tony Pham / Unsplash


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