From risk to resilience: Examining the intersection of extreme weather events, community vulnerability, and health impacts

Objectives: Our study will characterize the immediate and cumulative health impacts associated with extreme weather events and will identify the key determinants that make communities vulnerable or resilient to these impacts. It will do so by focusing on communities within the Gulf and southeastern Atlantic United States (US) coastal and adjacent regions, where the adverse consequences of such events are particularly severe. Our study has three primary aims: to (1) perform a comprehensive vulnerability assessment that describes the hazards, as the time, location, magnitude and severity of each extreme weather event, and community vulnerability, based on the infrastructural, environmental, and socio-economic characteristics of each ZIP code within our study region, (2) assess the health impacts from extreme weather events and to identify community factors that modify these impacts, and (3) characterize the speed and degree to which the health of communities recover post-extreme storm events and examine whether overall and component-specific vulnerability indicators predict health recovery class membership. Approach: Our approach is inter-disciplinary, leveraging expertise from civil and environmental engineering, epidemiology, and biostatistics. Using data from 1990 to 2021, we will develop a multi-dimensional vulnerability framework to (1) assess the hazards posed by extreme weather events using data on biophysical factors and probabilistic modeling, (2) characterize the vulnerability of communities to these events using machine learning techniques that incorporate information on the infrastructural, socio-economic, and environmental characteristics of these communities, and (3) identify clusters of communities that share similar vulnerability profiles using k-mean and hierarchical clustering techniques. We will examine health risks and characterize community recovery profiles post-extreme weather events and their modification by event type and vulnerability indicators. Importantly, our examination will focus on all Medicare and Medicaid beneficiaries living in the southeastern US. We will do so using individual-specific, all-cause mortality and cause-specific hospital admissions data for these beneficiaries and using epidemiologic models, such as mixed effect logistic regression models with distributed lag effects and linear segmented regression models. Expected Results: Our study is expected to yield new evidence and critical insights into the complex interplay of factors that influence the vulnerability and health of coastal communities facing extreme weather events. This knowledge will inform strategies related to emergency planning, healthy recovery efforts, and the enhancement of resilience among these communities. Project Number: 1R01ES036731-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Institute of Environmental Health Sciences (NIEHS) | Principal Investigator: Helen Suh | Institution: TUFTS UNIVERSITY MEDFORD, Boston, MA | Award Amount: $793,443 | Activity Code: R01 | Study Section: Social and Environmental Determinants of Health Study Section[SEDH] View on NIH RePORTER: https://reporter.nih.gov/project-details/11131925