数学建模和分析COVID-19和伤寒热病与治疗的共同动力学
Daniel S Mgonja1,2, Alfred Hugo3, Asha Hassan3
1Department of Management Studies, Tanzania Institute of Accountancy, Box 9522, Dar es Salaam, Tanzania. mgonja_d@yahoo.com.
Scientific reports
|September 26, 2025
概括
数学建模表明,针对COVID-19和伤寒联合感染的增强治疗和查显著减少了疾病传播. 最佳的控制策略是社区健康的关键.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 公共卫生 公共卫生
背景情况:
- 与COVID-19和伤寒联合感染带来了复杂的公共卫生挑战.
- 了解传播动态对于有效的控制策略至关重要.
研究的目的:
- 开发和分析COVID-19和伤寒联合感染的确定性数学模型.
- 评估治疗干预措施对疾病传播和控制的影响.
主要方法:
- 使用下一代矩阵方法来确定有效的繁殖数.
- 在稳定性分析中采用了利亚普诺夫函数方法.
- 使用部分等级相关系数 (PRCC) 进行了灵敏度分析.
- 应用Pontryagin的最大原则来建立最佳的控制条件.
主要成果:
- 该模型证实,治疗控制有效地减少了这两种疾病的传播.
- 增加治疗和查率被发现可以最大限度地减少传播.
- 确定改善了COVID-19,伤寒热和共感染的治疗方法,作为关键的控制措施.
结论:
- 数学建模为管理共感染提供了有价值的见解.
- 有针对性的治疗和查策略对于控制COVID-19和伤寒发烧的传播至关重要.
相关概念视频
Modeling with Differential Equations
7
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
7
Steps in Outbreak Investigation
492
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
492
Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs
3.0K
The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
On the other hand, integral calculus focuses on...
On the other hand, integral calculus focuses on...
3.0K
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
494
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
494
Pharmacokinetic Models: Comparison and Selection Criterion
335
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
335
Mechanistic Models: Compartment Models in Individual and Population Analysis
249
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
249


