In response to the January 12, 2010 earthquake and its tragic impacts, billions of dollars of development aid are pouring into Haiti for reconstruction. Due to both the extent of the devastation, and the path-dependency associated with infrastructure systems, (i.e. once built, infrastructure is typically more efficiently expanded rather than decommissioned and replaced), decisions about how to invest these resources will determine how millions of Haitians will acquire water, remove wastes, commute to work, power homes and businesses, and communicate for decades to come.
"Sustainable" reconstruction requires a focused effort to incorporate local knowledge into all levels of infrastructure decision-making. Historically, and especially in developing world settings, infrastructure decisions are typically made by "experts" who compare alternatives in terms of often narrowly defined economic metrics (i.e. what length of roadway, how many gallons of treatment, or BTUs of energy can be produced for each dollar of capital investment). This "planner's" approach has led to a range of unintended consequences spanning the inter-related built, natural, and human domains. Schemes designed and implemented from the top-down often fail or lead to the marginalization and demoralization of the intended beneficiaries.
By contrast, while planners make decisions about how to apply development aid assuming that they already know the answers, "searchers" look for innovative solutions based on an assessment of local opportunities and constraints. This project tests the hypothesis that infrastructure rehabilitation priorities based on local knowledge elicited through stakeholder-driven processes will differ fundamentally from those developed by technical experts based outside of the service area. We focus on water and sanitation issues in Leogane, a town of approximately 40,000 people located at the quake's epicenter.
This project creates a context for immediate local input into reconstruction planning by assisting local stake-holders in articulating local knowledge about infrastructure and social needs, which can then be "merged" with engineering expertise and brought to bear on decision-making by government agencies and external aid donors.