Comprehensive Study of a Diabetes Mellitus Mathematical Model Using Numerical Methods with Stability and Parametric Analysis
Bibliographic Data
| ID | 15510079 |
|---|---|
| Authors | Mohammad AlShurbaji (American University of Sharjah), Lamis Abdul Kader (American University of Sharjah), Hadia Hannan (American University of Sharjah), Md Maruf Mortula (0000-0003-4974-2833, American University of Sharjah), Ghaleb A Husseini (0000-0002-7244-3105, American University of Sharjah, corresponding author) |
| Year | 2023 |
| Volume | 20 |
| Issue | 2 |
| Pages | 939-939 |
| Publication date | 2023-01-04 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph20020939 |
| PMID | 36673694 |
| OpenAlex | W4313559544 |
| Language | EN |
| References cited | 3 |
Diabetes is sweeping the world as a silent epidemic, posing a growing threat to public health. Modeling diabetes is an effective method to monitor the increasing prevalence of diabetes and develop cost-effective strategies that control the incidence of diabetes and its complications. This paper focuses on a mathematical model known as the diabetes complication (DC) model. The DC model is analyzed using different numerical methods to monitor the diabetic population over time. This is by analyzing the model using five different numerical methods. Furthermore, the effect of the time step size and the various parameters affecting the diabetic situation is examined. The DC model is dependent on some parameters whose values play a vital role in the convergence of the model. Thus, parametric analysis was implemented and later discussed in this paper. Essentially, the Runge-Kutta (RK) method provides the highest accuracy. Moreover, Adam-Moulton's method also provides good results. Ultimately, a comprehensive understanding of the development of diabetes complications after diagnosis is provided in this paper. The results can be used to understand how to improve the overall public health of a country, as governments ought to develop effective strategic initiatives for the screening and treatment of diabetes
Convergence (economics · Diabetes mellitus · Economics · Environmental health · Machine learning · Macroeconomics · Parametric statistics · Population · Public health · Stability (learning theory · Statistics · Computer Science · Diabetes Management and Research · Diabetes, Cardiovascular Risks, and Lipoproteins · Liver Disease Diagnosis and Treatment · Mathematics · Medicine · Nursing
| Highly cited | No |
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