Compound Extreme Heat and COVID-19 Risks in the United States

Abstract:

The COVID-19 pandemic has added new challenges to the already difficult management of weather-related hazards. In the United States, cities must modify traditional strategies to protect vulnerable people from weather events (e.g. hurricanes, extreme heat, flooding) in order to fulfill the recommended protections for COVID-19, such as social distancing and mask wearing. Extreme heat events (EHEs), which have been exacerbated over time by climate change and urban heat island, are the largest cause of weather-related mortality in the US. Traditional policy responses including wellness checks and opening cooling centers are not conducive to maintaining the social distancing requirements for managing a pandemic such as COVID-19. As public funds are limited, there is a need to better identify risk factors that make individual communities more susceptible to compounded events, so resources can be allocated accordingly.

Here we create a high spatial-resolution framework to identify regions most vulnerable to the health consequences associated with a coupled infectious disease outbreaks and EHEs. We apply this framework to analyze vulnerabilities associated with EHEs occurring during the COVID-19 pandemic. This presentation will 1) aggregate demographic, public health, and climate data to elucidate spatial differences in the factors that exacerbate compounded risks throughout the US, and 2) iterate on and validate the proposed framework with real data from the summer of 2020 to better understand the factors driving compounded risks, inform future risk analysis, and develop more targeted public policy responses. We found that many areas with more exposure and less infrastructural resources to manage EHE’s were co-located with higher risk factors for COVID-19. We also found that despite the closure of many de-facto cooling resources (i.e. shopping malls, restaurants, movie theaters), many cities limited or closed official cooling centers. These ad-hoc responses suggest traditional risk-management practices are insufficient to predict and prevent the negative impacts of compound events. To complement risk management, this work can inform resilience analysis by reviewing how systems perform in a variety of scenarios to help them recover quicker, agnostic of any specific threat.