The article highlights the necessity of preparing for disasters like hurricanes and their uneven impact on vulnerable populations. Using demographic data, the Environmental Inequality Lab developed a rapid-response analysis framework to provide localized insights to authorities and first responders. By combining socio-economic data with weather forecasts, the framework helps identify at-risk residents before disasters strike, ensuring timely resource deployment. Tested during Hurricane Milton, this approach aims to improve disaster preparedness and response, addressing the challenges faced by elderly and underprivileged communities in emergencies.
Our approach combines demographic and socio-economic data provided by the US Census Bureau with forecasts released by the US National Hurricane Center and Weather Prediction Center.
To help the people most at risk, local authorities and first responders need to know in advance who lives in the areas most affected.
The population data are privacy-protected and consist of aggregated counts by age, race, sex and income decile, mapped in grid cells of approximately one square kilometre.
Not everyone is able to respond to the same degree. Illness, disability, lack of transport and financial constraints can all exacerbate the risk for people in vulnerable groups.
#disaster-preparedness #vulnerable-populations #emergency-response #data-analysis #environmental-inequality
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