The Science and Practice of Resilience

An increasingly globalized world with wide-ranged and uncertain threats to public health, energy networks, cybersecurity, and many other interconnected facets of infrastructure and human activity, has driven governments such as within the United States, European Union, and elsewhere to further efforts to bolster national resilience and security. Resilience analysis has grown in popularity as a mechanism by which states may judge the safety, security, and flexibility of various complex systems to recover from a range of potential adverse events. Preparation for such hazards is generally thought to include measures of both passive and active resilience and have been described as including considerations of necessary actions and risk considerations before, during, and after a hazardous event takes place. Given all of this, resilience is clearly a subject with radical potential consequences in the preparedness of a nation’s energy, water, transportation, healthcare, emergency response, communications, and financial sectors to prepare for and recover from external shocks of a significant magnitude.

As a term, resilience has centuries of use as a descriptor in fields as diverse as military operations, to psychology, to civil and environmental engineering. Its synonyms are vast and varied, ranging from insinuations of toughness to elasticity. While it pulls its roots from these early ideas, the modern application of resilience has centered upon analyzing how systems bounce back from disruption. This seems simple enough at first glance, yet as this book will discuss, the methodological application and analysis of how systems bounce back post-disruption can be quite challenging.

As a concept and disciplinary practice, resilience analysis has evolved rapidly within the twenty-first century. This is driven in large part by the growing complexity in everyday systems that dominate daily life, from energy and transportation networks to medical and even entertainment systems. Such complexity is derived to provide potentially vast benefits to society through innovative technology development and organization, and subsequently makes daily life for individuals easier, more enjoyable, or increasingly integrated.

Resilience has a lengthy history of practice and implementation for events of extreme consequence and high uncertainty. One of the clearest cases of embryonic resilience thinking includes Medieval Venice, which was forced to grapple with the recurring threat of plague that threatened to destroy the fabric of European society and cripple the juggernaut of Venetian maritime trade (Linkov et al. 2014a, b, c, d, e; Lane 1973). This early resilience thinking did not fully inoculate Venetian society from the ravages of disease—on the contrary, limitations of medical knowledge and border control allowed for outbreaks throughout the early modern era—yet it did allow Venetian policymakers to begin to address the question of how to combat deadly disease. The cumulative successes in reducing disease incidence and spread throughout the city and its dependent settlements eventually brought policymakers to embrace resilience thinking for other unrelated projects ranging from climate change to land reclamation efforts—all centered on the idea of strengthening Venetian social, economic, and cultural capabilities in the midst of an uncertain future (Vergano and Nunes 2007; Linkov et al. 2014a, b, c, d, e). This all goes to show that while resilience thinking and resilience analysis are growing buzzwords in the early twenty-first century, their roots go back centuries before even the printing press or functional medicine.

After understanding the definitions and fundamentals of resilience, a natural extension includes how resilience is applied within the theory and practice of governance. As with any philosophy or analytical practice, resilience does not exist in a vacuum, and instead is applied alongside complementary practices of industry requirements and best practices of analyzing and managing risk. In this chapter, we unpack the critical questions of (a) what does resilience governance entail and (b) how has resilience been discussed and onboarded in various governing paradigms and practices in the United States and internationally? While current scholarly discussion in this area is limited, we can deduce governing procedures and priorities from various government agency policy documents and statements, as well as similar guiding principles laid out by industry, to indicate where resilience governance might be headed in the near-term future.

Risk quantification is an essential element of any risk or resilience management tool. Traditionally, chemical risk quantification is undertaken with the assistance of extensive data in an exposure-driven approach, where both human and environmental health risk is evaluated in repeated trials. In infrastructure risk quantification, less common events, such as natural disasters, may be quantified through probabilities reliant on extensive historical data. However, in the absence of rigorous quantitative data, exposure-driven risk assessment may be replaced (however temporarily) by qualitative assessment. Regardless of method chosen, however, the ultimate goal of risk quantification is to classify a material or project as containing no risk, prohibitive risk, or some gradient in between.

As discussed throughout the earlier chapters in this book, many US government agencies have already begun applying principles of resilience analysis to a variety of infrastructures and systems. Often, such use of resilience has focused on systems-wide shocks to the basic functionality of a particular service’s infrastructure. This is due largely to the system’s high degree of complex interconnectivity with other such systems, such as the inherent dependencies between road infrastructure, energy grids, and the behaviors of people using such roads at given periods of time. A disruption or shock to one of these systems can trigger effects upon others that rely upon it. As it becomes more necessary to prepare for events that have the potential to disrupt or destroy critical functionalities to particular practices or areas of action, it is quite likely that these, and other areas with highly complex and integrated infrastructure will increasingly embrace resilience thinking in the coming years.

Continuing from Chap. 7, this chapter applies one method—the resilience matrix—to a selection of cases ranging from energy grids to psychological resilience to electrical engineering. As noted in Chap. 6, the resilience matrix can utilize either qualitative or quantitative input to inform decision-making, making it flexible and adaptable to user needs. Each case below includes a general overview of how resilience might be applied to a given case area, and then continues on to include a real-world, real-data case demonstration through a resilience matrix.

As our last collection of cases, Chap. 9 includes brief demonstrations of how network science may be utilized to explore elements of a system’s resilience. Through the modeling of systems as a series of interconnected nodes and linkages, network science provides a more quantitative assessment that many stakeholders in transportation systems, cybersecurity, or epidemiology would require to assist with decision-making. As with Chap. 8, each case includes a brief introduction of the case and the potential role for resilience, and includes a notation of how a network science approach might be constructed for cases ranging from transportation systems to epidemiological modeling.

The world is experiencing a gradual increase in systemic threats that threaten critical infrastructure, social order, and environmental sustainability. Our capability to address those threats is diminishing, and significant residual risk remains. Risk assessment and management have been used to harden components of the systems affected by specific threats, yet such approaches are often prohibitively expensive to implement, and do not address cascading effects of system failure. Accepting the possibility of system failure and focusing on recovery has been proposed under the umbrella of resilience assessment. Even though resilience has promise in many fields, including psychology, ecology, and engineering, its operationalization has been misapplied in a manner that is easily rectified.