Computational analysis of a mathematical model of hookworm infection
Abstract According to the Centers for Disease Control and Prevention (CDC) estimates that 576 to 740 million people globally are infected with hookworms. It remains a significant public health threat in tropical and subtropical regions. Especially in low-income countries, hookworm infection continue...
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-83123-x |
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| author | Umar Shafique Mohammed Mahyoub Al-Shamiri Ali Raza Nauman Ahmed Muhammad Rafiq Emad Fadhal Baboucarr Ceesay |
| author_facet | Umar Shafique Mohammed Mahyoub Al-Shamiri Ali Raza Nauman Ahmed Muhammad Rafiq Emad Fadhal Baboucarr Ceesay |
| author_sort | Umar Shafique |
| collection | DOAJ |
| description | Abstract According to the Centers for Disease Control and Prevention (CDC) estimates that 576 to 740 million people globally are infected with hookworms. It remains a significant public health threat in tropical and subtropical regions. Especially in low-income countries, hookworm infection continues to affect millions, even with the availability of modern medical advancements. The present study is based on the transmission dynamics of hookworm infection in a population by using the strategy of mathematical modeling with computational methods. The population has been categorized into the following subpopulations such as susceptible humans, infectious humans, infectious humans with heavy infection, humans recovered, worm eggs, non-infective larvae, and infectious larvae and exposed humans. Firstly, the fundamental properties like positivity and boundness are studied. The equilibrium points like hookworm-endemic equilibrium (HEE), hookworm-free equilibrium (HFE), and basic reproduction numbers for the model were computed. Secondly, the stochastic formation of the model was studied with well-known properties like positivity, and the boundedness of the hookworm model. The model has no analytical solution due to the highly complex nonlinearity of the stochastic delay differential equation (SDDEs) of the model. Methods like Euler Maruyama, stochastic Euler, stochastic Runge Kutta, and stochastic nonstandard finite difference are used for its solution and visualization of results. Also, the comparison of standard with nonstandard methods is presented to verify the efficiency of the computational method. Furthermore, the stochastic nonstandard finite difference approximation is a good agreement to restore the dynamical properties of the model like positivity, boundedness, and dynamical consistency. Also, it is shown as efficient, low-cost, and independent of the time step size. In conclusion, the theoretical and numerical results support understanding the transmission dynamics of hookworm infection in the population. |
| format | Article |
| id | doaj-art-d2f66e6354b2429584df5196ec7e8c4e |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-d2f66e6354b2429584df5196ec7e8c4e2025-08-20T03:00:39ZengNature PortfolioScientific Reports2045-23222025-02-0115111410.1038/s41598-024-83123-xComputational analysis of a mathematical model of hookworm infectionUmar Shafique0Mohammed Mahyoub Al-Shamiri1Ali Raza2Nauman Ahmed3Muhammad Rafiq4Emad Fadhal5Baboucarr Ceesay6Department of Mathematics, National College of Business Administration and EconomicsDepartment of Mathematics, Applied College, Mahayl Assir, King Khalid UniversityDepartment of Physical Sciences, The University of ChenabDepartment of Computer Science and Mathematics, Lebanese American UniversityDepartment of Mathematics, Namal University, 30KM Talagang RoadDepartment of Mathematics & Statistics, College of Science, King Faisal UniversityMathematics Unit, The University of The GambiaAbstract According to the Centers for Disease Control and Prevention (CDC) estimates that 576 to 740 million people globally are infected with hookworms. It remains a significant public health threat in tropical and subtropical regions. Especially in low-income countries, hookworm infection continues to affect millions, even with the availability of modern medical advancements. The present study is based on the transmission dynamics of hookworm infection in a population by using the strategy of mathematical modeling with computational methods. The population has been categorized into the following subpopulations such as susceptible humans, infectious humans, infectious humans with heavy infection, humans recovered, worm eggs, non-infective larvae, and infectious larvae and exposed humans. Firstly, the fundamental properties like positivity and boundness are studied. The equilibrium points like hookworm-endemic equilibrium (HEE), hookworm-free equilibrium (HFE), and basic reproduction numbers for the model were computed. Secondly, the stochastic formation of the model was studied with well-known properties like positivity, and the boundedness of the hookworm model. The model has no analytical solution due to the highly complex nonlinearity of the stochastic delay differential equation (SDDEs) of the model. Methods like Euler Maruyama, stochastic Euler, stochastic Runge Kutta, and stochastic nonstandard finite difference are used for its solution and visualization of results. Also, the comparison of standard with nonstandard methods is presented to verify the efficiency of the computational method. Furthermore, the stochastic nonstandard finite difference approximation is a good agreement to restore the dynamical properties of the model like positivity, boundedness, and dynamical consistency. Also, it is shown as efficient, low-cost, and independent of the time step size. In conclusion, the theoretical and numerical results support understanding the transmission dynamics of hookworm infection in the population.https://doi.org/10.1038/s41598-024-83123-xHookworm infection modelStochastic delay differential equations (SDDE’s)Positivity and boundednessComputational methodsResults |
| spellingShingle | Umar Shafique Mohammed Mahyoub Al-Shamiri Ali Raza Nauman Ahmed Muhammad Rafiq Emad Fadhal Baboucarr Ceesay Computational analysis of a mathematical model of hookworm infection Scientific Reports Hookworm infection model Stochastic delay differential equations (SDDE’s) Positivity and boundedness Computational methods Results |
| title | Computational analysis of a mathematical model of hookworm infection |
| title_full | Computational analysis of a mathematical model of hookworm infection |
| title_fullStr | Computational analysis of a mathematical model of hookworm infection |
| title_full_unstemmed | Computational analysis of a mathematical model of hookworm infection |
| title_short | Computational analysis of a mathematical model of hookworm infection |
| title_sort | computational analysis of a mathematical model of hookworm infection |
| topic | Hookworm infection model Stochastic delay differential equations (SDDE’s) Positivity and boundedness Computational methods Results |
| url | https://doi.org/10.1038/s41598-024-83123-x |
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