Use of Population Weighted Density Index for Coronavirus Spread in the United States.

IF 2.3 Q2 ECONOMICS
Journal of Health Economics and Outcomes Research Pub Date : 2024-07-17 eCollection Date: 2024-01-01
Huseyin Yuce, Hannah Stauss, Adrienne Persad
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Abstract

Background: Understanding how population density affected the transmission of COVID-19 is vitally important, since crowded cities were the epicenters for the disease. Since human contact was the main cause of the spread, population-weighted densities have been shown to be a better measure than conventional densities, since the variation in density across subareas matters more than the density in the total area. Objectives: This study investigates the impact of population-weighted density and other demographics on the rate of COVID-19 spread in the United States. Methods: The study considers population-weighted density and many other demographics. The population-weighted density index is the weighted average of density across the tracts, where tracts are weighted by population. Multivariate analysis has been used to determine the elasticity of the spread. Results: Using U.S. county-level data, we calculated the elasticity of COVID-19 spread with respect to population-weighted density to be 0.085 after controlling for other factors. In addition to the density, the proportion of people over 65 years of age, the number of total healthcare workers, and average temperature in each county positively contributed to the case numbers, while education level and income per capita had a negative effect. Discussion: For the spread, understanding the population characteristics and dynamics is as important as understanding the infectious disease itself. This will help policy makers to utilize and reallocate the resources more effectively. If the spread is successfully contained early, there will be less stress placed upon the healthcare system, resulting in better healthcare access for those who are sick. Conclusions: Our analysis suggests that population-weighted density can be a useful tool to control and manage outbreaks, especially within the early stage of the spread. We presented the early dynamics of the spread and recommended a policy measure on how to transfer healthcare workers from low-spread-risk areas to high-spread-risk areas to utilize resources better.

美国冠状病毒传播的人口加权密度指数的使用。
背景:了解人口密度如何影响 COVID-19 的传播至关重要,因为拥挤的城市是该疾病的传播中心。由于人类接触是传播的主要原因,人口加权密度已被证明是比传统密度更好的衡量标准,因为各分区的密度变化比总区域的密度更重要。目标:本研究调查了人口加权密度和其他人口统计学因素对 COVID-19 在美国传播速度的影响。研究方法:本研究考虑了人口加权密度和许多其他人口统计数据。人口加权密度指数是各区密度的加权平均值,其中各区按人口加权。采用多变量分析来确定人口分布的弹性。结果:利用美国县级数据,在控制了其他因素后,我们计算出 COVID-19 传播相对于人口加权密度的弹性为 0.085。除密度外,65 岁以上人口比例、医护人员总数和各县平均气温也对病例数产生了积极影响,而教育水平和人均收入则产生了消极影响。讨论:对于传播而言,了解人口特征和动态与了解传染病本身同样重要。这将有助于决策者更有效地利用和重新分配资源。如果能及早成功遏制传播,医疗保健系统所承受的压力就会减少,患病者就能获得更好的医疗保健服务。结论:我们的分析表明,人口加权密度是控制和管理疫情的有效工具,尤其是在疫情扩散的早期阶段。我们介绍了疫情传播的早期动态,并就如何将低传播风险地区的医护人员转移到高传播风险地区以更好地利用资源提出了政策建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.00
自引率
0.00%
发文量
55
审稿时长
10 weeks
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