This research examines the relationship between social vulnerability factors and reported needs following Hurricane Florence. Weighted least squares regression models were used to identify predictor variables for valid registrations that reported needs pertaining to emergencies, food, and shelter. Data consisted of zip codes in North Carolina and South Carolina that received individual assistance for Hurricane Florence (N = 406). The results suggest that when controlling for event-specific factors and flood mitigation factors, the proportions of the population that is female, the population over 65, the population aged 5 and under, the population older than 5 years not speaking English, and the minority population were all predictors of the per capita reported emergency needs. When controlling for the same variables, the proportions of the population over the age of 25 with a Bachelor’s degree, the female population, the population aged 5 and under, the population above 5 years old that does not speak English, and the minority population were all predictors of the per capita reported food needs. With the same variables controlled for, three variables—the proportions of the population over 65, the population aged 5 and under, and the non-English-speaking population above 5 years of age—were all predictors of the per capita reported shelter needs. The results suggest that more attention should be given to these vulnerable populations in the pre-disaster planning process.

这项研究研究了飓风佛罗伦萨后社会脆弱性因素与报告的需求之间的关系。加权最小二乘回归模型用于识别有效注册的预测变量，该变量报告了与紧急情况，食物和住所有关的需求。数据由北卡罗来纳州和南卡罗来纳州的邮政编码组成，这些邮政编码分别获得了飓风佛罗伦萨（N = 406）。结果表明，在控制特定于事件的因素和防洪因素时，女性人口的比例，65岁以上的人口，5岁及以下的人口，5岁以上的人口不讲英语，以及少数群体人口都是人均报告的紧急需求的预测因素。在控制相同变量时，具有学士学位的25岁以上人口，女性人口，5岁及以下的人口，5岁以上的不会说英语的人口以及少数民族人口的比例是人均预测指标报告了粮食需求。在控制了相同变量的情况下，三个变量是65岁以上人口的比例，5岁及以下人口的比例，以及5岁以上的非英语国家人口，都是报告的人均住房需求的预测因素。结果表明，在灾前规划过程中应更加关注这些脆弱人群。