Understanding the long-term effects of hurricanes on cardiovascular health and outcomes

Weill Medical Coll Of Cornell Univ, New York NY

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Linked publications & trials

Abstract

As an emergency/internal medicine physician who has served in several hurricane-impacted zones, my long-term goal is to become an independent physician-scientist whose research informs policies that mitigate the adverse health effects of extreme weather events (EWEs). The focus of this K08 is to receive mentored training to evaluate and improve programs like Department of Health and Human Services emPOWER program – the sole federal program designed to identify individuals at risk of premature morbidity and mortality due to EWEs. In 2021, EWEs adversely affected 1 in 3 Americans. The effects of hurricanes on cardiovascular health (heart failure, myocardial infarction, and stroke) are well-documented, and are likely to disproportionately affect such vulnerable populations as older adults, those with multiple comorbidities, and persons of low socioeconomic status. However, targeting such populations with U.S. federal pre-disaster mitigation is challenging because of difficulties identifying those at greatest disaster-related cardiovascular disease (CVD) risk and uncertainty about the timeframe for which risk is increased. We hypothesize that emPOWER can better identify those at risk by considering disaster-related CVD outcomes, incorporating available clinical, demographic, socioeconomic, and environmental factors into risk assessment, and considering these outcomes over longer time periods. This will enable emPOWER and local health system programs to more accurately identify those at high risk of adverse CVD outcomes, so that future programs can build tailored approaches to evacuate high risk groups before hurricanes strike and address the needs of those at excess CVD risk afterward. With mentored training in spatial analysis, CVD and social epidemiology, machine learning, and disaster science, I will evaluate the impact of Hurricane Sandy in 2012 on NYC because of its large population and neighborhood-level SES disparities-- and because no further hurricanes affected NYC during the study period, accomplishing the following aims using Medicare claims and ancillary datasets: 1) Estimate the hurricane’s impact up to 5 years after landfall on census tract-level CVD point prevalence in the ≥ 65 years old population using spatiotemporal modeling; 2) Compare the hurricane’s impact on CVD event rates for Medicare beneficiaries currently designated as high risk by emPOWER compared to all other beneficiaries using survival analyses and Cox models; and 3) Develop and internally validate a CVD risk prediction tool using machine learning techniques, and determine its implications. Guided by a board of federal and local disaster policy experts and mentored by nationally recognized experts, this K08 will provide me with the training and resources necessary to develop a CVD risk prediction tool to identify the most vulnerable individuals currently ignored by federal disaster planning policy, and allow me to build a career that improves and evaluates disaster policy and interventions across various extreme weather events using science-based approaches to prevent adverse CVD outcomes driven by changing weather patterns.