Environmental Disasters and Impacts on Health Care Systems

Lavin_Gong – Project Summary How climate-related disasters impact health and regional risk is not fully known. Our long- term goal is to improve health sector preparedness, resiliency, and health outcomes following climate-related disasters. Our objectives are threefold: 1) To assess long-term changes in

health outcomes that have been linked with climate-related disasters; 2) to quantify the relationship between population vulnerabilities in the 7 Vital Cond variables and post-event disease prevalence changes; and 3) to develop and test a geospatial C-DRAPS to visualize the regional risk profiles, identify climate-sensitive health indicators, project impacts on health, and

communicate regional community risks with healthcare workers, educators, and community leaders who care for disaster-affected populations. Our central hypothesis is that incidences of long-term chronic conditions and vector-borne disease following a climate change-related disaster are associated with region-specific well-being and environmental health (EH)

conditions. Our aims are: 1) Determine the existing community risks and consequent extra risks to health arising from climate-related disasters. 2) Determine the independent and joint impacts of climate-related disasters on the prevalence of HTN, DM, asthma, depression, and vector- borne diseases up to five years following disasters. 3) Analyze county samples in Aim1.a as

training data to establish a model that quantifies the relationship between variables in the 7 Vital Conditions of Health and Well-being and post-event disease prevalence changes. This model is subsequently employed to predict changes in the prevalence of HTN, DM, asthma, depression, and vector-borne disease following future climate-related disasters within any given U.S. county

based on county-specific variables. Aim 2. Design and validate a GIS-based dashboard for integrated visualization, analysis, projection, and communication of regional community risks focusing on population vulnerability indicators, climate indicators, and health indicators (prevalence of HTN, DM, asthma, depression, vector-borne diseases) after climate-related

disasters. The research is significant as it will predict long-term health impacts of disasters and exacerbate regional risk profiles that can influence disaster planning and policy, resulting in innovative approaches to health systems and community preparedness that enhance resiliency. The impact of this model will expand the understanding of chronic conditions and vector-

borne disease following FDDs and link the evidence from datasets consistent with the 7 Vital Conditions of Well-being. The innovative holistic model will combine complex data in one easily assessable tool, designed to be user-friendly and openly available.