Abstract
Extreme weather events — including wildfires and hurricanes — are becoming increasingly hazardous due to climate change, and often result in transient or permanent population displacement. Combined with population displacement, disaster-related disruptions in infrastructure, workforce, wages, and social networks may result in interruptions to healthcare access and prolonged impacts on morbidity and mortality. The data needed to make health systems and emergency management approaches more resilient to these hazards and more responsive to the needs of affected populations are sequestered in silos across private corporations and public agencies.
In two case studies, the CrisisReady team describes how they have negotiated access to privately-held novel data sources, such as anonymized geolocation data from cellphones, while striking a balance between data security and public health utility. The team discusses how the analytic tools at CrisisReady are embedded into disaster response workflows by co-developing their research questions and outputs with responders and policy makers. ReadyMapper, an interactive data visualization tool that tracks population mobility, infrastructure damage, and health system capacity in near real-time, was deployed in the midst of wildfire season in California and during the response to Hurricane Ida in Louisiana. The Data-Methods-Translational framework the team has developed is scalable and relies on sharing science and co-creating products with policy makers and response agencies to ensure real-world applicability. These attributes make the framework particularly useful for formulating evidence-based approaches to protect human health through climate change adaptation.
