Mathematical modeling and analysis of schistosomiasis transmission dynamics

Umar T. Mustapha, Salihu S. Musa, Muhammad A. Lawan, Aliyu Abba, Evren Hincal, Musa D. Mohammed, Bashir D. Garba, Rabiu B. Yunus, Shehu A. Adamu, Daihai He

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Schistosomiasis is a parasitic disease from the family of Schistosomatidae and genus Schistosoma, which is caused by blood flukes. The disease is endemic in many countries and still a serious threat to global public health and development. In this paper, a new deterministic model is designed and analyzed qualitatively to explore the dynamics of schistosomiasis transmission in human, cattle and snail populations. Results from our mathematical analysis show that the model has a disease-free equilibrium (DFE) which is locally asymptotically stable (LAS) whenever a particular epidemiological threshold quantity, also known as basic reproduction number (R0) is less than unity. Further analysis shows that the model has a unique endemic equilibrium (EE) which is globally asymptotically stable whenever R0>1 and unstable when R0<1. Furthermore, we adopt partial rank correlation coefficient for sensitivity analysis to reveal the most important parameters for effective control and mitigation of schistosomiasis disease in a community. Finally, we obtain some numerical results by simulating the entire dynamics of the model, which show that the infections in the compartments of each population decrease with respect to time. This further indicates that avoiding contact with infected human, cattle or infested water is vital to prevent the spread of schistosomiasis disease infection.

Original languageEnglish
Article number2150021
Number of pages19
JournalInternational Journal of Modeling, Simulation, and Scientific Computing
Issue number4
Publication statusPublished - Aug 2021


  • basic reproduction number
  • Schistosomiasis disease
  • sensitivity analysis
  • stability analysis

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications


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