在SAARC国家预测空气污染导致的死亡率和DALY
Amna Amer1, Nadia Mushtaq1, Olayan Albalawi2
1Department of Statistics, Forman Christian College (A Chartered University), Lahore, Pakistan.
Scientific reports
|October 29, 2024
概括
预计空气污染会增加萨克国家死亡率和DALY,其中环境颗粒物污染和环境臭氧污染是关键驱动因素. 神经网络为这种不断升级的健康负担提供了最准确的预测.
科学领域:
- 环境健康 环境健康
- 流行病学 流行病学
- 数据科学数据科学数据科学
背景情况:
- 空气污染对全球健康构成重大威胁,特别是在南亚区域合作联盟 (SAARC) 地区.
- 量化空气污染相关疾病的未来负担对于有效的公共卫生干预至关重要.
研究的目的:
- 预测空气污染对2020年至2030年SAARC国家死亡率和残疾调整寿命年 (DALYs) 的影响.
- 确定导致这种健康负担的主要空气污染物,并比较不同预测模型的预测精度.
主要方法:
- 时间序列和机器学习技术,包括自行回归集成移动平均 (ARIMA),指数式光滑 (ETS) 和神经网络 (NN).
- 对因环境颗粒物污染 (APM),环境臭氧污染 (AOP) 和家庭空气污染 (HAP) 造成的死亡和DALY预测趋势的分析.
- 使用根平均平方误差 (RMSE) 评估模型性能,以确定最准确的预测方法.
主要成果:
- 在2020年至2030年期间,SAARC国家预计空气污染导致的死亡率和DALYs的持续上升趋势将在2020年至2030年之间出现.
- 环境颗粒物污染 (APM) 和环境臭氧污染 (AOP) 被确定为增加健康负担的主要原因.
- 与ARIMA和ETS相比,神经网络模型显示出更高的预测准确性,RMSE值较低.
- 在SAARC国家中观察到与污染相关的死亡和DALY的流行率存在显著差异,印度和巴基斯坦显示APM的高率,孟加拉国和巴基斯坦显示AOP,尼泊尔显示HAP.
结论:
- 空气污染在SAARC国家构成日益严重的健康风险,需要立即采取有针对性的控制措施.
- 基于准确预测的有效政策制定对于缓解与各种空气污染类型相关的不断升级的死亡率和DALYs至关重要.
- 调查结果强调需要区域合作和量身定制的战略,以解决SAARC国家空气污染的多样性影响.
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