在约旦卡拉克市使用物流回归模型预测COVID-19疾病的感染
Anas Khaleel1, Wael Abu Dayyih2, Lina AlTamimi3
1Department of Pharmacology and Biomedical Sciences, Faculty of Pharmacy, Petra University, Amman, Jordan.
F1000Research
|August 27, 2025
概括
在卡拉克市,女性性别和45岁以上的年龄是COVID-19感染风险的重要预测因素. 这一发现有助于了解COVID-19的传播动态,并为公共卫生策略提供信息.
科学领域:
- 流行病学
- 公共卫生
- 生物统计学
背景情况:
- 2020年3月由世卫组织宣布的COVID-19大流行病迅速在全球蔓延,包括约旦,需要采取紧急措施.
- 尽管进行了广泛的研究,但COVID-19感染的确切预测因素仍然存在争议.
- 这项研究调查了影响约旦卡拉克市COVID-19感染率的关键人口因素.
研究的目的:
- 识别和分析预测COVID-19感染概率的人口变量.
- 根据已识别的决定因素开发COVID-19感染风险的预测模型.
- 为应对疫情的公共卫生资源分配和规划提供信息.
主要方法:
- 用二进制物流回归模型分析了卡拉克市386名参与者的数据.
- 通过Google Sheets收集了COVID-19感染状况和人口特征 (性别,年龄,工作,吸烟,慢性疾病,流感疫苗接种) 的数据.
- 统计分析的重点是确定每个人口特征作为感染预测因素的意义.
主要成果:
- 与男性相比,女性参与者的COVID-19感染风险更高 (OR=2.04,p=0.012).
- 与45岁以下的患者相比,45岁以上的患者感染风险增加 (OR=1. 91, p=0. 020).
- 在研究群体中,性别和年龄被确定为COVID-19感染的最重要的人口预测因素.
结论:
- 开发的物流回归模型利用年龄和性别,可以预测卡拉克市的COVID-19感染概率.
- 调查结果强调了年龄和性别在COVID-19风险评估中的重要因素.
- 该模型可以帮助医疗管理人员和政策制定者优化资源配置和疫情应对计划.
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