Department of Geography, Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, South Carolina, United States of America.
PLoS One. 2021 Feb 3;16(2):e0246548. doi: 10.1371/journal.pone.0246548. eCollection 2021.
As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in small towns within metro counties, then diffusing to centralized urban areas and rural areas. When mitigation restrictions were relaxed, hotspots reappeared in the major cities. This paper examines the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1st-September 5th, 2020. We first describe the initial diffusion of the new confirmed cases per week across the state, which remained under 2,000 cases until Memorial Day weekend (epi week 23) then dramatically increased, peaking in mid-July (epi week 29), and slowly declining thereafter. Second, we found significant differences in cases and deaths between urban and rural counties, partially related to the timing of the number of confirmed cases and deaths and the implementation of state and local mitigations. Third, we found that the case rates and mortality rates positively correlated with pre-existing social vulnerability. There was also a negative correlation between mortality rates and county resilience patterns, as expected, suggesting that counties with higher levels of inherent resilience had fewer deaths per 100,000 population.
随着 COVID-19 疫情在美国最初受影响严重且城市化程度较高的东北地区以外地区的蔓延,2020 年初,美国其他城市地区也相继出现了病例热点。在南卡罗来纳州,疫情的时空模式有所不同,最初集中在大都市县的小镇,然后扩散到集中的城市地区和农村地区。当缓解限制放宽时,热点又出现在主要城市。本文考察了 2020 年 3 月 1 日至 9 月 5 日期间南卡罗来纳州每县 COVID-19 确诊病例的县际时空模式。我们首先描述了该州每周新增确诊病例的最初扩散情况,这些病例在阵亡将士纪念日周末(第 23 周)之前一直保持在 2000 例以下,然后急剧增加,在 7 月中旬达到峰值(第 29 周),此后缓慢下降。其次,我们发现城市和县之间的病例和死亡存在显著差异,部分原因是确诊病例和死亡的数量以及州和地方缓解措施的实施时间存在差异。第三,我们发现病例率和死亡率与预先存在的社会脆弱性呈正相关。死亡率与县弹性模式之间也呈负相关,这是意料之中的,这表明固有弹性水平较高的县每 10 万人的死亡人数较少。