Combined COVID-19 data, urban climate modeling, and social vulnerability indicators to derive a multi-hazard risk index
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Employed Local Indicators of Spatial Association to identify spatially associated clusters of low and high multi-hazard risk.
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Multi-hazard risk hot spots coincide with low-income areas where both COVID-19 and near surface temperatures were highest.
Abstract
New York City, the most populated urban center in the United States, is exposed to a variety of natural hazards. These range from extratropical storms and coastal flooding to extreme heat and cold temperatures, and have been shown to unevenly impact the various vulnerable groups in the city. As the COVID-19 pandemic hit in March 2020 and the city became an early epicenter, disparities in exposure led to widely uneven infection and mortality rates. This study maps the overlapping heat and COVID-19 risks in New York City with a multi-hazard risk framework during Summer 2020. To do so, we simulate neighborhood scale temperatures using the Weather Research and Forecasting model coupled with a multi-layer urban parameterization. Simulation outputs were combined with zipcode-scale COVID-19 and sociodemographic data to compute a multi-hazard risk index. Our results highlight several regions where high social vulnerability, COVID-19 infection rates, and heat coincide. Moreover, we use the local indicators of spatial association technique to map regions of spatially correlated high multi-hazard risk in the NYC boroughs of The Bronx and parts of Brooklyn and Queens. These high risk locations account for nearly a quarter of the city's population, with households earning less than half than those in the lowest risk zones.
