Top-Down and Bottom-Up Measurement to Enhance Community Resilience to Disasters

The “community resilience” ideal breaks with earlier status quo thinking that it is enough for society to respond to disasters as they occur. Mounting human and economic losses and a several-decades-long upward trajectory in the extreme events (i.e., tropical storms, flooding, drought, and wildfire) occurring each year have made such a reactionary position no longer tenable (http://bit.ly/2GZHTWj). Policymakers, practitioners, and populations now aspire more fully for communities to anticipate, withstand, recover from, and emerge even stronger after a disaster.¹

Over the last decade, newly developed models and measurement schemes have given researchers and decision-makers a more systematic way to study community resilience and intervene to strengthen it.^2–4 Because of the problem’s complexity and developers’ and users’ interests, however, these models and measures vary greatly.² For instance, some emphasize physical structures, from an engineering perspective, while others focus on institutional and interpersonal elements, informed by the social and behavioral sciences.⁵

MEASUREMENT AND ASSESSMENT BENEFITS

Whatever their emphases, community resilience indicators achieve important ends. Fundamentally, they “deepen our perception of resilience,” shifting from abstract construct to concrete phenomenon.^3(p160) They serve important communication functions, giving people a shared language and the means to enlist others in the common aim of improving resilience to disasters.⁵ They also aid with strategizing and decision-making by helping to identify where to begin work and apply limited resources.^1,4

Community resilience assessment serves important administrative and motivational purposes, allowing a community to establish a baseline, monitor and evaluate efforts, and celebrate progress.² Measurement schemes that allow communities to compare themselves with others motivate change through a different dynamic, whether by promoting healthy competition or acquiring knowledge about successful interventions applied elsewhere.⁵ Measurement also helps communities make the business case for resilience investments and attract new backers.¹

TOP-DOWN OR BOTTOM-UP?

Communities can now adopt a top-down or bottom-up approach for assessing resilience.² Typically, top-down methods are the product of an organization outside the community, intended for use by an oversight or expert-driven body and reliant upon standardized and centralized data to quantify resilience.² Designed for greater objectivity and precision, top-down methods enable more legitimate comparisons across a common unit of analysis. In contrast, bottom-up assessments—which usually employ qualitative data and input from experts and nonexperts alike—are more sensitive to the local meanings of resilience and the particular conditions that bear on it.^2,6

Despite producing variable data, participatory processes that involve diverse stakeholders in assessing community resilience have important benefits. They can promote broad understanding of risk and resilience in a community, enhance local ownership and legitimacy of the assessment, and foster resilience at multiple levels (e.g., individual, household, organizational).⁶ Moreover, inclusive, collaborative processes for assessment can help generate social capital and cohesion as well as build up the capacity to solve problems collectively—traits often associated with greater community resilience.^1,6

COMBINING PERSPECTIVES

A new initiative to provide communities with the benefits of both top-down and bottom-up resilience assessment is the Composite of Post-Event Well-Being (COPEWELL), developed through research funded by the Centers for Disease Control and Prevention (Figure 1), informed by a broad set of stakeholders, and piloted in two local communities. COPEWELL resources consist of a conceptual framework for community resilience that integrates social, physical, and natural systems; a computational model for predicting community functioning and resilience after disasters; and a toolkit (or “rubric”) to enable a collaborative, participatory assessment of community resilience.

FIGURE 1—

Composite of Post-Event Well-Being (COPEWELL), a Conceptual and Computational Model for Predicting Postdisaster Community Functioning and Resilience: Diagram, Definitions, and Domains

Source. Adapted from Links et al.⁷

The COPEWELL framework (Figure 1) features community functioning domains that need to be preserved through a disaster (e.g., transportation, housing). It also incorporates domains that either mitigate (e.g., natural and engineered systems) or exacerbate (e.g., population inequality and deprivation) the effect an event has on a community’s initial loss of functioning (“resistance”), as well as domains (e.g., social capital and cohesion, preparedness and response) that help replenish community functioning following the event (“recovery”). Together, resistance and recovery constitute resilience, a latent property.

By not conflating baseline community functioning with resilience, and by separating resilience into resistance and recovery, the COPEWELL framework provides communities a new way to think about resilience. Moreover, in field testing, the illustrated framework itself served as a concrete vehicle to spark meaningful cross-sector conversations and networking activities essential to community resilience. In one pilot community, for instance, social service providers struggling to meet local day-to-day needs had previously seen little common cause with disaster managers. A literal picture connecting their areas of expertise and interests helped to elevate their discussions and solidify a broader, shared aim.

NATION AND NEIGHBORHOOD

Based on system dynamics, the COPEWELL computational model relies upon publicly available, quantitative measures at the county level to predict community resistance, recovery, and postevent functioning following disasters. Owing to its top-down design, the computational model enables all of the more than 3000 US counties to see how they compare nationally across specific domain and predicted resilience values. At the outset of organizing their systematic resilience programs, two pilot communities convened diverse stakeholders to review computational model outputs in the form of a frequency distribution histogram with their own county’s value as a bold vertical line. In each case, comparison against the national field—which uncovered deficiencies and strengths—reinforced among participants the desire for change.

Limiting the computational model, however, were shortfalls in nationally available county-level data and “community” being defined at a single geo-scale. Thus, the bottom up COPEWELL rubric was codeveloped with a pilot community; it consists of facilitator guides and self-assessment worksheets that enable group visioning, evaluating, and planning. Each domain worksheet, for instance, includes qualitative descriptions of optimal- and low-capacity levels as well as prompting questions to generate collective ratings and ideas about interventions to strengthen the domain. Taking advantage of the rubric’s pliability, one pilot community employed the social capital and cohesion worksheet at county and municipal levels and explored how individual neighborhoods might assess themselves.

Gauged in place at eye level or comparatively scanned from a bird’s eye view, community resilience benefits from group processes of measurement and assessment, enabling residents to mitigate the impacts of a public health emergency more effectively.