Social vulnerability is the susceptibility of a community to be adversely impacted by natural hazards and public health emergencies, such as drought, earthquakes, flooding, virus outbreaks, and the like. Climate change is at the root of many recent natural hazards while the COVID-19 pandemic is still an active threat. Social vulnerability also refers to resilience, or the ability to recover from such adverse events. To gauge the many aspects of social vulnerability the US Center of Disease Control (CDC) has subdivided social vulnerabilities into distinct themes, such as socioeconomic status, household composition, and others. Knowing a community's social vulnerabilities can help policymakers and responders to recognize risks to community health, prepare for possible hazards, or recover from disasters. In this paper we study social vulnerabilities on the US county level and present research that suggests that there are certain combinations, or patterns, of social vulnerability indicators into which US counties can be grouped. We then present an interactive dashboard that allows analysts to explore these patterns in various ways. We demonstrate our methodology using COVID-19 death rate as the hazard and show that the patterns we identified have high predictive capabilities of the pandemic's local impact.
翻译:社会脆弱性是一个社区易受自然危害和公共卫生紧急情况(如干旱、地震、洪水、病毒爆发等)不利影响的可能性。气候变化是最近许多自然灾害的根源,而COVID-19流行病仍然是一个积极的威胁。社会脆弱性还涉及抗御能力,或从这些不利事件中恢复的能力。为了衡量社会脆弱性的许多方面,美国疾病控制中心将社会脆弱性细分为不同的主题,如社会经济地位、家庭组成和其他。了解社区的社会脆弱性有助于决策者和应对者认识社区健康的风险、防备可能的危害或从灾害中恢复。在本文件中,我们研究了美国县一级的社会脆弱性,并提出研究表明,存在某些社会脆弱性指标的组合或模式,可以将美国各州归类。然后,我们提出了一个互动的仪表板,使分析者能够以各种方式探讨这些模式。我们用COVID-19死亡率作为危害的方法,并表明我们所查明的模式具有高的对流行病当地影响的预测能力。