LOUISE K. COMFORT, UNIVERSITY OF PITTSBURGH, PITTSBURGH, PA 15260, DESIGNING RESILIENCE FOR COMMUNITIES AT RISK.
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LOUISE K. COMFORT, UNIVERSITY OF PITTSBURGH, PITTSBURGH, PA 15260, COMFORT@GSPIA.PITT.EDU DESIGNING RESILIENCE FOR COMMUNITIES AT RISK
RISK AND RESILIENCE Changing status of communities: Greater exposure to hazards Aging infrastructure Changing demographics Increasing demand for services, but declining resources Deepening vulnerability to extreme events
POLICY DILEMMA Reduce risk vs. increase resilience Risk: exposure to harmful events outside one’s control Resilience: capacity to absorb damaging event, but maintain basic operations to support the community Tension between allocating scarce resources to reduce vulnerability to risk…. ….or developing capacity to manage risk more efficiently
KEY FACTORS THAT UNDERLIE RISK Insufficient monitoring of changing environment Heterogeneity in populations exposed to risk Inability to recognize threats in different arenas of action Asymmetry in information processes among different constituent groups Inability to mobilize collective action to counter threat
KEY FACTORS THAT UNDERLIE RESILIENCE Capacity to hold and exchange information Flexibility to adapt to changing situation Commitment to a shared goal for the community Systematic assessment of changing state of community Capacity to update information about risk and to act on timely, valid information
BUILDING RESILIENCE Three basic tasks: Build a knowledge base of region and its exposure to risk Identify the parameters in the system that can and will vary under threat, e.g.: Number of personnel engaged in operations Degree of commonality among actors in terms of training, experience, available resources Number of demands placed on the system Identify the threshold for intervention in system to inject new resources, material, information to enable system to adapt
HAITI FOLLOWING THE 12 JANUARY 2010 EARTHQUAKE Initial conditions before the earthquake: Extreme vulnerability in built environment: buildings, roads, water, sanitation, communications, power systems Extreme vulnerability in social environment: 80% unemployment; 55-60% illiteracy; mean life expectancy: 43 years. Impact of a sudden, extreme event is exacerbated by vulnerability Conditions limit capacity of community for adaptation with internal resources Severity of event requires external assistance
IMPACT OF EVENT, WITHOUT RESILIENCE Severe losses: at least 230,000 lives lost 1.5 million people homeless, 80% of the buildings in Port au Prince destroyed Eleven out of twelve governmental ministries collapsed, as well as the Presidential palace Presidential Palace Ministry of Public Works
CATASTROPHIC DAMAGE 80% of the schools’ infrastructure was destroyed or damaged; Three of the four universities were severely damaged, General Hospital, the primary medical institution in the city collapsed
Figure 1. Network Diagram of Interacting Organizations in the Haiti Earthquake Response System, January 12 – February 3, 2010
Network Measure Clustering Coefficient (CANA)0.393 Average Distance (CANA)3.251 Average Clustering (Random Graph)0.052 Average Distance (Random Graph)2.817 Clustering Ratio7.569 Distance Ratio1.154 Small World Ratio 6.559 Table 2 Small World Network within Haiti Response System, January 12- February 3, 2010
STRATEGIES FOR RECOVERY, RECONSTRUCTION Reconstruction requires a “systems approach” System is made up of interacting, interdependent components that adapt to changing environments Design a “knowledge commons” to support decision- making in regions exposed to risk. (Hess & Ostrom, 2007) “knowledge commons” includes a shared knowledge base, but also the technical infrastructure and organizational processes to support information search, exchange, updates, storage, transmission Users of the knowledge commons contribute to updating and revising profiles of “status of the community” in dynamic environments.
STRATEGIES FOR RECONSTRUCTION Characteristics of a knowledge commons: Interdisciplinary: technical, organizational, cultural content Interjurisdictional: International, national, state/provincial, local Intersectoral: Public, private, nonprofit organizations as participating users Scalable in function: System is anchored at local level where first action occurs, but scales rapidly to wider arenas as dynamics of interaction shift among participants.
CONCLUSIONS Lack of local knowledge exacerbates disaster risk Design and development of a knowledge commons reduces disaster risk Information technology, carefully designed and implemented, facilitates information search, exchange, and organizational learning. Powerful resource in process available to a community exposed to long term risk is the capacity of its people to learn