在中国使用混合ARIMA-GM模型预测抗菌药物耐药性[1,1]
Feng Liu1,2, Caixia Dang1,2, Hengliang Lv1,2
1Chinese People's Liberation Army Center for Disease Control and Prevention, Beijing, China.
BMC infectious diseases
|August 15, 2025
概括
该ARIMA-GM(1,1) 模型准确地预测了中国的关键耐药细菌率,显示了下降趋势. 这有助于优化针对MRSA和CTX/CRO-R-KP等感染的抗微生物策略.
科学领域:
- 流行病学 流行病学
- 传染性疾病 传染性疾病
- 数学建模的数学建模
背景情况:
- 抗微生物耐药性是一个日益增长的全球健康威胁.
- 准确预测耐药率对于有效的抗菌药物管理至关重要.
研究的目的:
- 评估ARIMA-GM(1,1) 组合模型,用于预测中国关键耐药细菌的耐药性率.
- 为优化抗微生物管理策略提供科学基础.
主要方法:
- 利用中国抗菌耐药性监测网络 (2014-2023) 的数据.
- 使用6种关键耐药细菌构建ARIMA-GM(1,1) 模型,包括MRSA和CTX/CRO-R-KP.
- 使用MSE,RMSE,MAE,MAPE和R2评估模型性能;预测了2024-2028年的趋势.
主要成果:
- 该ARIMA-GM(1,1) 模型显示出强大的预测性能 (R2>0.8为五个菌株).
- 预计2024年MRSA和CTX/CRO-R-KP的耐药性率分别为27.46%和26.47%.
- 预计到2028年,所有研究细菌的耐药性率将显著下降.
结论:
- 该ARIMA-GM(1,1) 模型已被验证用于预测主要耐药细菌的耐药性率.
- 观察到抵抗率的显著下降趋势,与国家行动计划有关.
- 未来的研究应该纳入抗生素使用数据,以加强干预策略.
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