Ali Raza, Eugenio Rocha, Emad Fadhal, Rashid I. H. Ibrahim, Eman Afkar, Muhammad Bilal
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引用次数: 0
Abstract
The delayed intervention techniques in real-world problem modelling have a significant role in behavioural, social, physical, and biological engineering, biomathematical sciences, and many more disciplines. Delayed modelling of real-world problems is a powerful tool and nonpharmaceutical technique for understanding the dynamics of disease in a population. This paper considers real-world problems like the Lassa fever model. According to the World Health Organization (WHO), Benin, Ghana, Guinea, Liberia, Mali, Sierra Leone, Togo, Nigeria, and West Africa are the most affected countries with Lassa fever. The most dangerous situation is that eighty percent of the infected persons have no symptoms. To study the dynamics of Lassa fever, two types of populations are considered humans and rats. The human population includes susceptible, infected, and recovered. The rat population includes susceptible and infectious rodents. By introducing a delay parameter and decay exponential term into the existing model in the literature, we got the system of highly nonlinear delay differential equations (DDEs). The fundamental properties such as positivity, boundedness, existence, and uniqueness are verified for the said model. The equilibrium and reproduction number of the model are discussed. The reproduction number for the Lassa fever model is analyzed using the next-generation matrix method. If the reproduction number is less than one, this situation helps eradicate the disease. If the reproduction number is more significant than one, then the virus will spread rapidly in human beings. We have also investigated the effect of the delay factor on reproduction numbers. The local and global stabilities for both equilibria of the model have also been presented. Furthermore, computer simulations are designed to analyze the academic behaviour of the model.
期刊介绍:
Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.