Climate change has the potential to impact on global, regional, and national disease burdens both directly and indirectly. Projecting and valuing these health impacts is important not only in terms of assessing the overall impact of climate change on various parts of the world, but also of ensuring that national and regional decision-making institutions have access to the data necessary to guide investment decisions and future policy design. This report contributes to the research focusing on projecting and valuing the impacts of climate change in the Caribbean by projecting the climate change-induced excess disease burden for two climate change scenarios in Saint Lucia for the period 2010 - 2050, and by estimating the non-market, statistical life-based costs associated with this excess disease burden. The diseases initially considered in this report are a variety of vector and water-borne impacts and other miscellaneous conditions; specifically, malaria, dengue fever, gastroenteritis/diarrhoeal disease, schistosomiasis, leptospirosis, ciguatera poisoning, meningococcal meningitis, and cardio-respiratory diseases. Disease projections were based on derived baseline incidence and mortality rates, available dose-response relationships found in the published literature, climate change scenario population projections for the A2 and B2 IPCC SRES scenario families, and annual temperature and precipitation anomalies as projected by the downscaled ECHAM4 global climate model. Monetary valuation was based on a transfer value of statistical life approach with a modification for morbidity. Using discount rates of 1, 2, and 4%, results show mean annual costs (morbidity and mortality) ranges of $80.2 million (in the B2 scenario, discounted at 4% annually) -$182.4 million (in the A2 scenario, discounted at 1% annually) for St. Lucia.1 These costs are compared to adaptation cost scenarios involving direct and indirect interventions in health care. This comparison reveals a high benefit-cost ratio suggesting that moderate costs will deliver significant benefit in terms of avoided health costs from 2010-2050. In this context indirect interventions target sectors other than healthcare (e.g. water supply). It is also important to highlight that interventions can target both the supply of health infrastructure (including health status and disease monitoring), and households. It is suggested that a focus on coordinated data collection and improved monitoring represents a potentially important no regrets adaptation strategy for St Lucia. Also, the need for this to be part of a coordinated regional response that avoids duplication in spending is highlighted.