Comparison of stochastic and random models for bacterial resistance

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Merdan M., Bekiryazici Z., KESEMEN T., Khaniyev T.

ADVANCES IN DIFFERENCE EQUATIONS, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume:
  • Publication Date: 2017
  • Doi Number: 10.1186/s13662-017-1191-5
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: stochastic differential equation, random differential equation, Milstein scheme, Euler-Maruyama scheme, antibiotic resistance, ANTIBIOTIC-RESISTANCE, MULTIPLE ANTIBIOTICS, DISCOVERY, HOSPITALS, VIRULENCE, DYNAMICS, DISEASE
  • Recep Tayyip Erdoğan University Affiliated: Yes


In this study, a mathematical model of bacterial resistance considering the immune system response and antibiotic therapy is examined under random conditions. A random model consisting of random differential equations is obtained by using the existing deterministic model. Similarly, stochastic effect terms are added to the deterministic model to form a stochastic model consisting of stochastic differential equations. The results from the random and stochastic models are also compared with the results of the deterministic model to investigate the behavior of the model components under random conditions.