Brian G McAdoo, Nicholas School of the Environment
Joao Vissoci, School of Medicine/Duke Global Health Institute
Catherine Staton, School of Medicine
Anjni Jointer, School of Medicine
Kate Hoffman, Nicholas School of the Environment
John Fay, Nicholas School of the Environment
Feroz Khan, Dillard University
Climate change alongside unprecedented land use change disproportionately stresses the health and well-being of marginalized indigenous, rural and urban communities and the healthcare institutions that serve them remain woefully unprepared to respond. A better understanding of which health conditions are triggered by these shocks will help policymakers direct investment toward healthcare preparedness, targeting interventions to reduce impacts of climate-related disasters on people’s lives. We propose to develop health-climate data access capacity and explore how climate change-related hazards impact acute disease burden in rural Brazil and marginalized communities in the US South. To achieve this goal, we will: (a) develop a repository combining healthcare data and climate data, following the FAIR principles (Findability, Accessibility, Interoperability, and Reuse); and (b) evaluate the association of climate-change characteristics, change in the burden of acute disease and gaps in healthcare capacity to address this impact. Our repository will include climate data (heat waves, cold snaps, extreme precipitation, etc.) from the National Oceanographic and Atmospheric Administration and health outcome data from the Duke University Health System and the Brazilian National Health Systems database (DATASUS). Our health data will focus on Emergency Care Sensitive Conditions (ECSC), defined as acute conditions that require timely access to care, which serve as good markers for the change in burden of care with weather/climate events (e.g. pulmonary associated conditions with heat, air quality, etc.). The repository will be built using a Knowledge Graph structure, improving its reusability and interoperability beyond the scope of this project.
With the repository developed, we will evaluate the frequency of ECSCs, as well as the capacity of the healthcare system to respond during climate-related events with a range of magnitudes and durations. This will include assessing for potential breaks in the continuum of care of emergency response facilities, in addition to measuring utilization and strain on the 9-1-1 system, Emergency Medical Services and Emergency Department resources. We will conduct similar evaluations in the US South (Durham/NC) and in Rural Brazil (Maringá/Paraná). We will conduct a set of time series analyses along with spatial variations in a Geographic Information Systems framework to account for significant changes in landscape and demographics to assess the impact on communities that are both more exposed to climate hazards and more economically/socially vulnerable. Once trends and correlations between climate impacts and disease burden are identified, we will 1) scale the analysis up to consider regional climate hazards/health outcomes in the Southeastern US and Amazonia, then nationally and 2) employ a set of Geospatial Artificial Intelligence, working with medical professionals to determine what resources should be pre-positioned in which communities to better treat ECSC during disasters.
