Community Resilience - Haiti

Developing Community Resilience to Disaster in the Caribbean Region

Louise K. Comfort, Director, Center for Disaster Management,

University of Pittsburgh, Pittsburgh, PA 15260

Email: comfort@gspia.pitt.edu 

Cliquez ici pour la traduction française de la description du projet

Policy Problem: Disaster Risk in the Caribbean Region

The Caribbean Region confronts a challenging set of problems in managing disaster risk. The small nations of the Caribbean and Central America are exposed to recurring risk of hurricanes, earthquakes, flooding, and environmental degradation from short-term agricultural and economic development practices. Given this deepening policy problem, we explore means of building community resilience that will enable small nations to assess their risks as well as their resources in terms of reducing the consequences of disasters that occur with increasing frequency, thereby strengthening their collective capacity for economic and social development over time.

Vision and Goals

Our vision is to foster greater capacity for community resilience and organizational learning both within and among three small nations in the Caribbean Region: Haiti, Honduras, and Nicaragua, with Colombia as a fourth partner in demonstrating more advanced development in disaster management.  We propose to initiate a pilot project in Haiti to stimulate a collective approach to disaster risk reduction in the region. The project would focus on public health as a basic, on-going need that is exacerbated by hazardous events which damage infrastructure and require coordinated response. We propose to establish a working consortium of faculty and students from the State University of Haiti, Quisqueya University, and the University of Pittsburgh to engage in the professional tasks of assessing risks and available resources, and work with local organizations and personnel to develop the knowledge and skills needed to manage risks in the region. We anticipate initiating an interactive forum to facilitate the exchange of information about hazards among organizations and groups in the region, and to enable local leaders and their constituents to address these hazards supported by a sociotechnical information infrastructure.

To realize this vision, we propose three goals for this project.  First, this project will serve as an ‘incubator’ project to build a ‘knowledge commons’ that would enable the residents of three communes in the Department of Artibonite, Haiti to assess and manage disaster risk more effectively. Second, we will use the results from this project to seek funding from other organizations to develop a wider application of this design to other critical policy areas. Third, as the ‘knowledge commons’ develops in effectiveness and performance in Haiti, the program will serve as a model for building capacity and resilience in disaster risk reduction in other nations. 

Decision making in disaster environments

Decision processes before, during, and after disaster shape the consequences and costs of extreme events for communities exposed to risk.  Decisions taken before a hazardous event occurs create the basis for actions taken in response to an actual event which, in turn, enable or constrain actions taken by the community to recover from that event. We propose to focus on the policy area of public health, to demonstrate the feasibility of creating a “knowledge commons” to build local capacity to manage the health consequences of extreme events, while simultaneously increasing performance in daily public health practice.

Measuring Resilience

A key approach to measuring resilience in communities exposed to recurring disaster risk is to integrate knowledge of the spatial characteristics of risk, vulnerability, cost, and ability to pay in the design of policies and practice to reduce disaster risk. We will develop templates for measuring indicators of public health risk in a systematic program of assessment and monitoring to support local decision making regarding public health practice.  These templates will be field-tested and validated in the Artibonite Region.

Theoretical Framework: Resilience as a Complex System of Systems

Framing the problem of disaster resilience as one that is generated by interacting physical, technical, organizational, social, and cultural systems requires an interdisciplinary perspective. Defining disaster resilience as the product of an interacting ‘complex system of systems’ (Ames et al. 2011) offers a promising approach to modeling the emergence of this capacity in communities exposed to risk.  A primary means to facilitate this iterative learning process for communities at risk is to include geospatial analysis, or visual representation of the current state of risk, and to create an open forum for information exchange, interactive learning, and the generation of new knowledge among the key actors in communities prone to hazards.

Research Design: Integration of Sociotechnical Measures with Representation of Risk

The goal of this research is to explore how integration of different measures of severity of exposure to hazards, probability of occurrence, number and types of population at risk, number and types of critical infrastructure at risk, estimated cost of mitigation and preparedness measures for the region, and potential sources of financial support may be used to inform collective decision making processes to support resilience to recurring risks for the region.

We will assess the validity of the design for a knowledge commons by testing its potential role in a simulated emergency operations exercise based on an actual event.  We will integrate existing data from primary actors regarding disaster risk and resources to create a baseline for community action.  Additionally, we will conduct a series of semi-structured interviews with key decision makers at local (municipal and provincial), national, and regional levels of jurisdiction to capture the decision process during periods of preparedness, response, and recovery in actual emergencies to document how and to what extent decisions made in one period shaped or constrained options for decision in the next period. These data will create a profile of emerging resilience or growing disorder for the region under varying conditions of urgency and constrained resources.

This field study will collect data regarding three primary points of decision in assessing resilience: 1) extent to which timely, valid information regarding risk informs collective decision making at the community, provincial, national, and regional levels regarding preparedness; 2) extent to which key decisions taken to prepare for an actual event (2010 earthquake) informed or constrained options in response operations; and 3) extent to which decisions made in response operations facilitated or constrained options for rapid recovery. Characterizing these three decision points in the events surrounding an actual event will provide a measure of resilience achieved in practice, and inform decisions regarding risk reduction for future extreme events.

We will use geospatial analysis of the region at risk to identify and estimate the economic value of existing infrastructure in the region, and network analysis to identify the relationships among principal actors participating in decision processes in each of the three periods of emergency operations. Applying Bayesian network models, we will assess the interdependencies among the key organizations engaged in disaster operations and among the set of interacting technical systems for the region. Using computational modeling, we will construct a system dynamics model for the meta-system of disaster operations to evaluate potential patterns of changing resilience for the region, based on different parameters for interaction among the sub-systems and conditions of operation within the region. The work is planned for twelve months, 4/1/2013-3/31/2014.

This research would transform mitigation, response, and recovery planning for communities at risk from major hazards in their region by integrating network analysis, Bayesian modeling, system dynamics, and estimates of cost/efficiency /robustness into an integrated model to inform coherent, collective decision making across organizations and jurisdictions.

Sebastien Gasquet, University of Pittsburgh, Graduate Student Researcher, e-mail: slg86@pitt.edu

Rebecca Jeudin, University of Pittsburgh, Graduate Student Researcher, e-mail: rhj5@pitt.edu

URL: www.cdm.pitt.edu

Center for Disaster Management
3807 Wesley W. Posvar Hall, Pittsburgh, Pennsylvania 15260