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Five city resilience lessons from the coronavirus

From healthcare to high street retail, transport to food and medical supply chains, the coronavirus (COVID-19) outbreak, has exposed the limited resilience of our cities. Beyond the immediate priority of everyone’s health and livelihoods, the crisis is an opportunity to rethink the way we plan, design, develop and manage our cities, to make sure better prepared to protect everyone when the next emergency arises. 

So, how do we improve our response? Meaningful data and information, easily available for use by local communities, is a first requirement. Only then can we make the right decisions about resources, supplies and operations, prioritising support to the people and areas where it matters most. Responding to emergencies is a concerted effort, where communication and knowledge sharing becomes key to ensure citizen safety. Beyond the value of good data, I want to explore five other early conclusions about what the Covid-19 crisis is teaching us:

1. The multi-hazard problem

A pandemic has many dimensions. Normally disparate issues suddenly connect and form larger problems. That’s why the traditional single hazard focus – whether it’s flooding, earthquake, typhoons, or bush fires – doesn’t prepare us to tackle the current crisis. A resilient city strategy must understand and explore the connections between multiple and cascading hazards. It means moving away from individual departmental responses to collaborative and integrated efforts by professionals and the community at large. 

Take the example of coastal flooding, from a storm surge. In many cities, the inland flood risk from heavy rainfall is usually assessed separately. Yet both hazards converge if a typhoon or hurricane occur. A truly resilient strategy would have to understand how the multi-hazard scenarios will unfold.

2. Resilience must be proactive, not just reactive

The sudden and unpredictable nature of urban crises often drives the emergency services to react rather than respond in a more considered way. A city’s emergency response system is often designed around rescue work in the event of a crisis, before focusing on post-disaster recovery and reconstruction. However, a better definition of urban resilience starts from a deep understanding of a city’s systems and operation. It’s an approach to resilience that can lead to proactive adjustment. Faced with a crisis, leaders need to know that the relevant preparations have been put in place, allowing them to respond effectively and achieve a rapid recovery.


3. City-wide data must generate real insights

In a crisis knowledge is everything. Data sharing platforms aren’t new, neither is the ability to access real-time and dynamic data. Current common data platforms provide a range of data at a national or global level, such as access to United Nations International Strategy for Disaster Reduction (UNISDR) and United Nations Environment Programme (UNEP) data through the United Nations Office for Disaster Risk Reduction (UNDRR) Prevention Web. While these are useful for trend analysis and global prevention, the data lacks the resolution and relevance to be used at the city or local level.

City resilience will increasingly depend on a ‘big data’ approach, using Internet of Things to establish ‘sensory systems’ that accurately capture critical information. This could include population data and essential material flows, to be shared across inter-connected smart city platforms for various applications such as real-time surveillance of epidemic risks, and trend analysis, helping to both prevent and respond to epidemics in realtime. Such a platform would allow leaders to better understand population flow within and across cities, and predict and assess potential risks of disease spread in the event of mass gatherings. The value of that data in a post-social distancing world is clear.

In a health crisis, designated hospitals and quarantine areas could be simultaneously analysed through proximity analysis to establish their safety level. Additionally, with the use of machine learning algorithms, the platform could calculate and predict areas with high probability of being affected by future epidemics. This is the kind of intelligence that would be incredibly valuable during the transition out of the current lockdown.

4. Know which systems are critical (and understand how they connect)

Cities are complex human machines, webs of services, needs, livelihoods and behaviours. The interconnectedness and dependencies of cities’ many systems means coordination is central to achieving effective resilience. It’s essential to review the risks of individual systems as well as to examine the intercorrelation between systems. Resilience strategists must compile a list of critical infrastructures susceptible to malfunctioning under the effects of various natural hazards and extreme scenarios, defining potential enhancements now. They must also identify domino effects under various hazard scenarios.

5. Frameworks solve the complexity problem

Covid-19 demonstrates how major health crises can’t be solved by narrow technical solutions. To achieve the level of interdepartmental or cross-functional coordination a resilient city needs you first need a much broader concept of the city’s overall system-level performance. In recent years, with the support of The Rockefeller Foundation, Arup developed the City Resilience Index (CRI); a powerful tool that is built upon 149 case studies derived from different cities around the world. The CRI provides insights into health and wellbeing, economy and society, infrastructure and environment, and leadership and strategy, developing connections between decision makers, technical experts, physical sciences and the humanities.

Investing in resilience takes us beyond the familiar concerns of cost, quality and time. The current pandemic shows us that only an integrated response will work, one informed by shared responsibility and financial accountability, transparent use of data, strong ethics, public participation, and maintenance of natural capital. A global problem must have a solution that works for everyone.