通过机器学习评估孟加拉国尼帕病毒疫苗接种决策的社会经济影响
Abu Zobayer1, Md Mahmudul Hasan Riyad2, Md Jaman Mia1
1Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
Journal of health, population, and nutrition
|September 30, 2025
概括
教育和收入等社会经济因素显著影响人们对尼帕病毒 (NiV) 接种疫苗的意愿. 公共卫生倡议应该解决这些差异,以便在孟加拉国制定有效的免疫战略.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗保健中的机器学习
背景情况:
- 尼帕病毒 (NiV) 在孟加拉国构成了严重的公共卫生威胁,通过密切接触和受污染的来源传播.
- 了解影响疫苗接种意愿的社会人口因素对于在NiV爆发期间进行有效的公共卫生干预至关重要.
研究的目的:
- 调查社会人口特征对孟加拉国尼帕病毒疫苗接种意愿 (WGTV) 的影响.
- 开发和评估机器学习模型,以预测接种疫苗的意愿,并确定关键影响因素.
主要方法:
- 孟加拉国的一项跨部门调查收集了有关社会人口因素,健康信仰和接种疫苗的意愿的数据.
- 统计分析 (基平方测试) 确定了人口学变量与WGTV之间的关联.
- 机器学习算法 (随机森林,决策树,XGBoost) 用于预测,并使用SHAP分析来确定特征的重要性.
主要成果:
- 机器学习模型在预测疫苗接种意愿方面取得了更高的准确性,随机森林在二进制分类场景中达到85%.
- 社会经济因素,特别是教育和收入,被确定为疫苗接种意愿的最有影响力的预测因素.
- 与社会经济特征相比,年龄和日常互动等人口统计因素的影响较轻.
结论:
- 社会经济差异显著影响孟加拉国尼帕病毒疫苗接种意愿.
- 公共卫生战略必须优先解决这些社会经济因素,以提高免疫覆盖率.
- 该研究为决策者提供了有价值的见解,以设计有针对性的干预措施并改善公共卫生结果.
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