在COVID-19传播波中,有风险的社会人口统计特征是否稳定?
Amanda Norton1, Scarlett Rakowska1, Tracey Galloway2
1Department of Geography, Geomatics & Environment, University of Toronto Mississauga, DV3284, 3359 Mississauga Road, Mississauga, ON L5L 1C6, Canada.
Spatial and spatio-temporal epidemiology
|June 10, 2023
概括
与安大略省COVID-19病例相关的社会人口统计因素在大流行期间演变. 了解这些不断变化的模式可以帮助准公共卫生干预措施,以减少疾病不平等.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 社会学 社会学 社会学
背景情况:
- COVID-19对健康的影响显示出跨社会,经济和种族的差异.
- 以前的研究表明风险分布不均,但时间稳定性不清楚.
研究的目的:
- 分析与安大略省COVID-19病例相关的社会人口学因素是否保持一致或在整个大流行浪潮中发生变化.
- 根据区域级特征,确定特定的脆弱人群.
主要方法:
- 根据每周的病例数量定义了五个COVID-19大流行浪潮.
- 利用了可见少数群体 (黑人,东南亚人,中国人) 的前期分类区域 (FSA) 级数据.
- 采用了包含社会人口统计学变量和其他脆弱性指标的空间错误模型.
主要成果:
- 发现与COVID-19感染率相关的基于地区的社会人口统计模式随着时间的推移而变化.
- 特定的少数群体在不同流行病阶段显示出与COVID-19病例率的不同关联.
结论:
- 社会人口特征和COVID-19风险之间的关系是动态的,而不是静态的.
- 根据不断变化的区域级数据识别高风险人群对于有针对性的公共卫生战略和减轻疾病负担至关重要.
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