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模拟COVID-19肺炎和COVID相关的肺:灵敏度分析和最佳控制
Mallela Ankamma Rao1, Emad K Jaradat2, Medisetty Padma Devi3
1Department of Mathematics & Statistics, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Yadadri, Bhuvanagiri, Telangana, 508284, India.
一个新的模型跟踪COVID-19的进展到肺炎和真菌感染 (CAPA). 接种疫苗和早期住院等联合干预措施在减少疾病负担和成本方面最有效.
科学领域:
- 流行病学和数学建模 流行病学和数学建模
- 传染病的动态传染病的动态.
- 公共卫生干预 公共卫生干预
背景情况:
- 严重的COVID-19可以导致肺炎和危及生命的真菌联合感染,如COVID-19相关的肺炎 (CAPA).
- 现有的流行病学模型往往无法捕捉从COVID-19到肺炎和随后的真菌并发症的连续进展.
研究的目的:
- 开发和分析一种新型的隔间模型 (SIIcpIcaHR),整合COVID-19,肺炎和CAPA动态.
- 确定影响疾病传播和严重程度的关键参数.
- 评估各种干预策略的有效性和成本效益.
主要方法:
- 开发一种新的隔间模型 (SIIcpIcaHR) 来研究COVID-19,肺炎和CAPA的协同动力学.
- 模型校准使用印度累积的COVID-19数据.
- 使用稳定性理论,灵敏度分析 (部分等级相关系数) 和最佳控制框架 (Pontryagin的最大原则) 的分析.
主要成果:
- 敏感性分析确定了影响传播和严重性的关键参数.
- 个人干预措施 (疫苗接种,早期住院,加强治疗) 减少了疾病负担.
- 结合的干预措施显著降低了肺炎和CAPA患病率,减少了住院治疗,并证明具有成本效益.
结论:
- 结合制药和临床干预的综合公共卫生战略至关重要.
- 解决严重的COVID-19结果和真菌共同感染需要采取多方面的方法.
- 开发的模型为评估复杂疾病进展和干预影响提供了一个框架.
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