<p>Tuberculosis (TB) is a airborne contagious disease that results in numerous deaths worldwide each year whereas scrub typhus, a zoonotic disease transmitted by vectors, poses significant public health implications. The main purpose of this research is to formulate a mathematical model to understand the transmission of co-infection of TB and scrub typhus. To ensure the biological properties are well-defined for the mathematical model, the boundedness, positivity, and invariant region of the solution were determined. The qualitative analysis for the basic TB model, the basic scrub typhus model and co-infection model is thoroughly discussed. In addition, we examined the occurrence of bifurcation in the co-infection model, followed by sensitivity analysis. To illustrate and strengthen the findings of the study, several numerical simulations were conducted. The results indicate that enhancing the recovery rate for co-infected individuals and reducing the contact rate of TB are effective strategies for reducing the prevalence within the population. Furthermore, it is crucial to eliminate reservoirs from the ecosystem to decrease the infected reservoirs and infected mites.</p>

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Mathematical model for the analysis of co-infection of tuberculosis and scrub typhus

  • Komal Chauhan,
  • Shubham Jasrotia,
  • Rakesh Kumar

摘要

Tuberculosis (TB) is a airborne contagious disease that results in numerous deaths worldwide each year whereas scrub typhus, a zoonotic disease transmitted by vectors, poses significant public health implications. The main purpose of this research is to formulate a mathematical model to understand the transmission of co-infection of TB and scrub typhus. To ensure the biological properties are well-defined for the mathematical model, the boundedness, positivity, and invariant region of the solution were determined. The qualitative analysis for the basic TB model, the basic scrub typhus model and co-infection model is thoroughly discussed. In addition, we examined the occurrence of bifurcation in the co-infection model, followed by sensitivity analysis. To illustrate and strengthen the findings of the study, several numerical simulations were conducted. The results indicate that enhancing the recovery rate for co-infected individuals and reducing the contact rate of TB are effective strategies for reducing the prevalence within the population. Furthermore, it is crucial to eliminate reservoirs from the ecosystem to decrease the infected reservoirs and infected mites.