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Assessing the Cumulative Climate-related Health Risks in the Eastern United States

Liu, Yang1; Remais, Justin1; Zhou, Ying1; Kitron, Uriel1; Fu, Joshua2; Drake, John2; O'Neill, Marie3; Schwartz, Joel4; Zanobetti, Antonella4

doi: 10.1097/01.ede.0000391713.93251.8c
Abstracts: ISEE 22nd Annual Conference, Seoul, Korea, 28 August–1 September 2010: Climate Change and Environmental Health

1Emory University, Atlanta, GA; 2University of Tennessee, Knoxville, TN; 3University of Michigan, Ann Arbor, MI; and 4Harvard University, Boston, MA.

Abstracts published in Epidemiology have been reviewed by the societies at whose meetings the abstracts have been accepted for presentation. These abstracts have not undergone review by the Editorial Board of Epidemiology.


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Climate change is likely to impose sizeable future health costs even in highly developed countries, such as the United States, caused by various adverse outcomes including elevated air pollution level. Previous research has focused on the health impact of individual stressors without considering their interactions and confounding factors. Yet a comprehensive approach is needed because environmental and public health authorities and affected communities must address a range of climate-sensitive health outcomes and their causative exposures in developing adaptation and mitigation programs.

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We will model health risks associated with 3 groups of climate-related stressors: heat waves, air pollution, and Lyme disease. We will couple the Community Climate System Model and WRF/CMAQ system to generate exposure estimates under current condition and in the 2050s under various IPCC greenhouse gas emission scenarios.

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We will rely on epidemiological evidence to quantify the conresponse relations of each stressor on the general population and various susceptible subpopulations while controlling for the confounding or effect modification from other stressors. We will apply advanced NASA satellite data to verify simulated current exposures, and analyze the impact of each analytical step to the overall uncertainty in risk estimates.

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Our analysis will serve as a model cumulative risk assessment characterizing the combined risks of 3 important climate-related stressors with complex interactions in geographic and demographic space. We will develop spatial representations of both hazard overlap and risk overlap. The spatial distribution of vulnerable populations will be examined with an emphasis on identifying potential response locations using geophysical, climatological, and demographic characteristics. Through current collaborations of our team members with local governments, we will not only advance climate-health science, but also develop relevant tools to guide policy decisions regarding the response and preparedness to climate change.

© 2011 Lippincott Williams & Wilkins, Inc.